The Next India India's Digital Leap - The Multi- Trillion ... · The Next India India's Digital Leap - The Multi-Trillion Dollar Opportunity I ndia's digitization drive has raised

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September 26, 2017 08:04 PM GMT

The Next India

India's Digital Leap - The MultTrillion Dollar Opportunity

India's digitization drive has raised our confidence in our long-term growth estimates. We forecast GDP to reach US$6 trillion, equity market cap to risto US$6.1 trillion and the market value of the financials and consumer secto

flict of nt decision.

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to hit US$1.8 trillion and US$2 trillion by 2027.

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M Contents

4 Preface

5 Quantifying the Digital Lift

6 India's Digital Economy - Two Pillars of Ch

10 Investment Implications

14 Key Risks

15 Digital Payments and GST - The Catalysts Change

28 Implication 1: GST Plus Digital Payments =Significant Big Data Opportunity

41 Implication 2: Digitization = Economic GrowBooster

48 Implication 3: A Massive eCommerce Oppo

53 Implication 4: Digital to Drive Equity Bull M

61 Implication 5: Financials – US$1.8 Trillion MCap in 10 Years

78 Risks to our Story

79 Individual Stock Section

112 Appendix 1 - JAM: Catalyzing Digitization

118 Appendix 2 - Paytm - The Disruptor That IsBecoming a Big Player

MORGAN STANLEY RESEARCH 3

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'Take up one idea. Make that one idea your life - think of it, dream of it, live on that idea. Let the brain, muscles, nervevery part of your body, be full of that idea, and just leave every other idea alone. This is the way to success'. Swamananda

Digitization is that idea in India, right now. The government and the Central Bank are on a mission to rapidly formalize and financialize economy. India has introduced a universal biometric identification system (Aadhaar), initiated measures to boost financial inclusion (Jmoved to a new fully online value-added goods and services tax system and implemented real-time payment systems (Unified Paymface and Bharat QR). Coupled with rising smartphone penetration, likely doubling from 300 million to nearly 700 million by 20changes are driving India's digitization. We expect a step change in India's per capita income, banking system and stock market performthe coming years. The channels of change include more financial penetration, greater tax compliance and increased credit to micro enand consumers.

The result could be a multi-trillion dollar investment opportunity. Aside from the near-term teething issues involved in execution ochanges and other cyclical problems faced by the economy, there is scope for visible shifts in economic activity starting in 2018 eleading to India being a) the third-largest economy in the world with a GDP of US$6 trillion, b) among the top five equity markets in with a market capitalization of US$6.1 trillion and c) the country with the third-largest listed financial services sector in the world withcap of US$1.8 trillion by 2027. We also expect India's consumer sectors to add about US$1.5 trillion to their current market cap of US$5over this period.

There are implications beyond India. The concomitant increase in e-commerce, consumption basket, financial products and investmmake India a significant market for global corporations. Most importantly, if India succeeds, it will become the template for othernations. While increasing financial inclusion has been the policy objective across emerging nations, India can provide leadership withmodel. Hence, it is very important for corporates, investors and policymakers across the globe to observe and understand these devein India. Indeed, there may be lessons for developed countries too.

William GreeneDirector of Asia Research

Preface

4

Hong Kong, September 2017

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M Quantifying the Digital LiftExhibit 1:India in F2027: The Power of Compounding Is Likely to Be Seen Across the Economy and Markets
Source: RBI (Reserve Bank of India), NHB (National Housing Board), IRDA (Insurance Regulatory and Development Authority), CEIC, AMFI, NPCI, NSE, BSE, Bloomberg, Morgan Stanley Research (E) estimates

Exhibit 2:The Stock Winners

PriceMarket Cap

(US$ bn)

3M traded value

(US$ mn)

Indian Financials

Bajaj Finance Rs 1,796 16 34

Edelweiss Financial Services Rs 255 3 12

HDFC Bank / HDFC Bank - ADR Rs 1,800 / US$ 94 72 41

ICICI Prudential Life Insurance Rs 389 9 9

Kotak Mahindra Bank Rs 1,000 29 31

LIC Housing Finance Rs 622 5 19

Mahindra & Mahindra Financial Services Rs 404 4 15

Indian Consumption

Asian Paints Rs 1,197 18 16

Eicher Motors Rs 30,980 13 23

ITC Rs 262 49 75

MakeMyTrip US$ 29 3 17

Maruti Suzuki Rs 7,965 37 51

Ultratech Cement Rs 3,902 16 15

Global stocks with Indian optionality

Alibaba US$ 170 434 2,855

Amazon US$ 940 451 3,431

DBS SG$ 21 39 65

Naspers ZAc 296,200 95 261

Softbank JPY 9,160 90 406

TransUnion US$ 45 8 74


Visa Inc US$ 103 236 721

MasterCard Inc US$ 139 148 414

Source: Bloomberg, Morgan Stanley Research. Note: Data as of September 25, 2017

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India's Digital Economy - Two Pillars of Change Exhibit 3:India in the Context of the World

Current Position F2027E Position

GDP Ranks 7th on the basis of nominal GDP 3rd largest based on nominal GDP

Market Cap (Overall)Ranks among the top 10 market caps

globally, market cap to GDP @ 86%

Top 5 market caps, market cap to GDP @

101%

Market Cap

(Financials)

Market cap to GDP at 15% vs. 22% for G-7

countries

At US$1.8 trillion, market cap to GDP at

31%

eCommerceAmong bottom quartile of the top 15

eCommerce markets globally

Within top quartile of the current list of top

15 eCommerce markets

Source: Bloomberg, RBI, IMF, Morgan Stanley Research (E) estimates

JAM and GST - the Forces Driving India's Technological Leap

Over the past seven years India has undertaken two major reforms. The first involved a combination of schemes to biometrically identify all Indian citizens (Aadhaar) and to promote broad financial inclusion (Jan Dhan). The second was the implementation of the indirect tax reform in July this year, which moved India from its former, archaic and complicated, tax system to a unified and completely digital goods and services tax (GST) regime.

These two reforms have "digitized" India and brought the country to an inflexion point in terms of growth, with a concomitant impact on stock returns, financial sector dynamics, consumption growth and e-commerce activity.

1. JAM - The Holy Trinity of Jan Dhan, Aadhaar and Mobile Sets the Stage for India to Leapfrog into the Digital Age

Jan Dhan: This initiative by the government launched in 2014 has essentially ensured that almost every household in India has a bank account and can access their account anywhere. Some 285 million accounts have been opened over the past three years.

Aadhaar: The beginning of India's digital revolution was the launch in 2010 of Aadhaar, which in Hindi means "foundation". The project was an ambitious one involving biometric identification of all India's people (1.3 billion of them). It has taken seven years but now the project is almost complete, with 1.2 billion Indians identifiable with either fingerprints or a retina scan - the scale and scope of this project is probably unmatched in world history for any government.

APIs (application programming interfaces) have been developed using Aadhaar to launch payment systems that allow real time C2C and C2M (customer-to-customer and customer-to-machine) transac-tions without needing any physical infrastructure - except a mobile phone. It also enables the completion of an electronic KYC (Know Your Customer) and the download of digital signatures.

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The benefits of Aadhaar can also be extracted via the private initiative of Indiastack.org. IndiaStack is a set of opensource APIs that allows governments, businesses, startups and developers to utilize India's unique digital infrastructure to solve problems by facilitating pres-ence-less, paperless, and cashless service delivery. Most recently, UPI - the unified payments interface - was added to this stack; it enables instant funds transfer over a smartphone using a virtual address. The government has supplemented the digital infrastructure with laws restricting values of cash transaction and incentivizing digital pay-ments.

Mobile: We estimate that India has around 800 million unique mobile users, and about 430 million have Internet access - a third of India's population. We believe Internet access will double in the next 10 years and we estimate that 915 million Indians will be on the Internet by 2026.

2. GST – Arguably India's Most Important Reform Since the Early 1990s

GST implementation and digitization should help government finances: India's brand new Goods and Services Tax (GST), with its ability to simplify India's complicated indirect taxation system and lift government revenues, has the potential to boost growth. GST com-pletely alters the way government finances are managed in India. Hitherto, tax collection in India was decentralized, while expenditure was centralized through the Planning Commission, which set expenditure priorities for the states. GST centralizes India's taxation in the hands of the Central Government, while the abolition of the Planning Commission in 2014 had already set the stage for decentral-ization of expenditure to the state governments. This shift, in our view, will provide a major boost to Indian government finances.

India’s ratio of tax revenues to GDP is lower than the average for emerging markets and this has been a key reason why the fiscal def-icit has been relatively higher. The implementation of GST will likely increase tax compliance on both indirect and direct taxes even while the tax rates are in and of themselves revenue-neutral. We estimate that if the primary fiscal deficit stays at 1.2% of GDP (as compared with an average of 2.1% over the past five years and 1.6% in F2017 on our estimates), the ratio of public debt to GDP will decline to below 60% by F2027 from 69% currently.

Digitization will help bring down government expenditure too, by helping the government conduct welfare spending with smaller leak-ages. The government has already implemented a direct benefit

transfer (DBT) program, which is a social welfare scheme under which subsidy benefits are directly transferred to the beneficiary’s bank account rather than via the issuance of checks, cash payments or rebates. Cumulatively, the total direct benefit transfer so far has been approximately Rs2 trillion and savings have been ~Rs500bn.

GST has the potential to lift medium-term profit growth: From the corporate sector's perspective, warehousing costs, freight costs, and inventory levels could all fall. Together with a more transparent and efficient input tax credit system and the removal of interstate barriers, these should lead to improved profitability. Over the next two to three years, large companies could also gain share from micro, small and medium enterprises (MSMEs), whose effective tax subsidy (if they do not pay taxes) is likely to vanish under GST. That said, it is not all bad news for MSMEs. Their entry into the formal economy, in addition to the transparency of the GST system, will enable flow-based lending to these entities, eventually lifting their growth as well as India's ratio of aggregate credit to GDP.

Exhibit 4:How Digitisation Will Likely Impact the Economy and Markets

Source: Morgan Stanley Research estimates

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Implications of India's Digital Transformation

a) Greater confidence in future growth

India is likely to be the world's fastest-growing large economy in the next ten years...

India's economy already had strong growth prospects for the next ten years. The trend line in India's annual GDP growth has been accel-erating from 5.8% in the 1990s to 6.9% in the 2000s. We think this trend will likely continue for the next decade given the following structural factors:

Favorable demographics: Over the next 10 years, 122 million individ-uals are likely to enter the work force, which is equivalent to about 20% of India's current work force.

Globalization: This provides the enabling factors of external demand and financing that can be used to boost growth.

Reforms: The government is continuing the reforms that India started in the early 1990s, which relate to the ease of doing business, FDI, government finances, taxation, infrastructure and greater autonomy for states.

…and digitization reinforces our views. We lift our annual long-term growth forecast by 50 bps.

Digitization is integral to two changes: a) policy initiatives that are boosting financial inclusion and b) technology changes that are reducing the cost of delivering financial services to the masses and small enterprises. These, along with the government's focus on employment for all, will make growth more inclusive, which in turn makes us more confident about India's growth outlook. We estimate that digitization will provide a boost of 50-75bps to GDP growth and forecast that India will grow to a US$6.0trn economy and achieve upper-middle income status by F2027. We expect India's real and nominal GDP growth to compound annually by 7.1% and 11.2% (10.2% in US dollar terms) respectively over the coming decade. We project gross FDI inflows amounting to US$120bn by F2027, almost double the current 12-month trailing run rate of US$64bn.

b) Financial Sector Revolution

Historically the banking system has primarily catered to large corpo-rates and well-heeled individuals. The costs of taking banking to the masses was fairly elevated, driving banks to focus on areas where rev-enue generation was high. However, this is changing for four main reasons:

1.Regulations will force banks to lend to segments other than large corporates. Unlike in the past, future funding to large corporates will be shared between banks and bond markets. From F2020 any com-pany with debt of greater than US$1.5 bn will be defined as a large corporate. These large companies will have to meet 50% of incre-mental funding through the bond markets. This will force the banks to look for new avenues of growth.

2.Technology is likely to bring down the cost of providing financial ser-vices significantly and to help grow consumer credit by around a 17% CAGR over the next decade. Even after such growth, total consumer loans will be low at 25% of GDP. There are two ways in which tech-nology is facilitating change:

a) By reducing the cost of opening accounts and hence expanding the reach of banks. Aadhaar and the associated eKYC has cut the cost of opening a deposit account by 90%. A recent example of this is Kotak's 811 initiative based on digital infrastructure, where the bank opened over a million accounts in one quarter on top of an existing customer base of eight million.

b) By enabling faster loan delivery. An example would be HDFC Bank's "loan in ten seconds" for unsecured personal loans. The bank uses its own data base on individuals' transactions along with credit scores from bureaus to offer quick loans to individuals. We expect this system to increase and to be implemented, on the same scale, by other banks too. The other driver of loans to individuals would be government schemes around affordable housing.

3. Cash flow data from the GST network and digital payment systems will boost credit to MSME's: These enterprises account for 80% of employment generation in India. Hitherto, due to a lack of reliable financial data, MSMEs were largely excluded from the formal banking system for credit and thus accounted for around 14% of credit from banks, we estimate. The online infrastructure of the GST network enables any taxpayer to securely share tax payment records (and therefore cash flow data) with anyone else. For the first time, Indian banks will have reliable data on their cash flows. Combined with a rise in usage of digital payments, a credit provider can now make a much more informed decision on the creditworthiness of

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such small borrowers. We expect lenders to reduce spreads on MSME lending by up to 300 bp as they get access to reliable and better quality data. We think this will drive MSME loan growth at a high teen CAGR for the next decade. This in turn could be a catalyst for overall growth, likely adding ~30 bps to real GDP growth on an annualized basis over the next decade, India's digital transformation and employment generation.

4. Gains for the private sector will continue at the expense of the state-owned banks: The starting point is that there is financial under-pene-tration in India, with loans as a percentage of GDP at 67%, consumer credit at 16% of GDP and formal system lending to MSMEs at ~10% of GDP. India's rapid digitization will impact financials negatively by reducing revenue yields across key lines and resulting in lower CASA (current and savings account) and lower distribution fees. That said, for tech-savvy banks, digitization should likely positively alter the growth trajectory in two ways:

i.Volumes - We expect tech-savvy banks to take market share from the data laggards, especially the SOE banks.

ii. Costs- The cost base of India lenders has historically been fairly high compared with that of other banks regionally due to the fragmented banking system and weak economies of scale. However, as tech-nology takes root, we expect costs to drop significantly, compen-sating for lower revenue yields.

c) Strong Household Consumption

There are two major trends driving consumption in India. First is rising consumer credit penetration aided by digitization and the likely cul-ture shift happening as a younger generation becomes less debt averse. Rising consumer credit, which we think will compound at 17% annually over the next decade, could add 20 bps to annual real GDP growth. Second is the shift away from food consumption to non-food consumption. Based on the CPI basket weights, food items account for 47% of Indian consumers' expenditure, which is one of the highest percentages globally. This likely reflects India's current level of low economic development. As per capita incomes rise, the share of expenditure is likely to shift towards non-food consumption, which will therefore grow faster than the economy as a whole. Such growth will be further augmented by the growth in housing, which forms the key platform for non-food consumption growth. Further, digitization will likely lead to an increase in the share of the organized sector in the consumption space. Versus an overall annual GDP growth of 11%, it is quite possible that organized non-food consumption registers mid-teen growth in the coming decade.

d) An eCommerce Boom

With over 900mn Internet users in 2026 and over half of them shopping online, we believe India's eCommerce market could grow to US$200bn by F2027, making it one of the most attractive opportunities globally. This growth is being driven by a combination of rising internet penetration, a drop in data access costs, a shift to smartphones and a flow of credit to consumer and micro enterprises.

1. Strength of MSMEs should help augment the supply chain: Currently, the number of merchants selling on online platforms such as Flipkart is around 150,000. Amazon India currently has 160 million products listed on its platform, versus 400+ million for Amazon in the US. We expect the numbers in India to increase meaningfully as more merchants enter the formal economy and have better access to credit.

2. Faster growth of online shoppers and per capita spending: India had about 60 million online shoppers in 2016, which was ~14% of the total Internet population versus 64% in China. An AlphaWise survey (link here) conducted in December 2014 showed that Internet users with less than two years of activity on the Internet were less prone to transacting. However, users with over five years of experi-ence on the Internet were more likely to transact online.

From F2020, more than half of India's Internet population will have matured, with five years' or more usage, and we think this will likely mark an inflexion point in online shopping. We expect 475mn online shoppers in F2027 and online spending of ~10% of per capita income, underpinning a boom in eCommerce.

3. Evolving payment methods: Cash on delivery is a prominent pay-ment method, accounting for about 55-60% of total eCommerce sales. One of the key reasons for the high dependence on cash is the trust deficit that exists between customers and online merchants. However, with the government's push to increase digitization of pay-ments, we believe cash will lose market share to credit/debit cards and payment wallets. This would improve the online shopping expe-rience.

https://ny.matrix.ms.com/eqr/article/webapp/383cf004-ac90-11e4-946e-d93333148876?ch=rpint&sch=sr

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Investment ImplicationsExhibit 5:Summary of Our Forecasts

Bull Base Bear

Real GDP, YoY % (Avg)* 7.1% 8.4% 7.1% 5.9%

Nominal GDP, F2017 2,279 7,095 6,040 5,368

Nominal GDP, YoY % (Avg)* 11.3% 13.0% 11.2% 9.5%

GNI Per Capita (US$), F2017 1,702 4,809 4,135 3,546

Total Loans, F2017 1,530 5,784 4,698 3,305

loans as % of GDP 67.1% 81.5% 77.8% 61.6%

Mutual Funds AUM, F2017 273 3,415 1,935 879

Domestic Equity Mutual Funds AUM 111 1,530 1,000 481

10-year Domestic Equity Flows 60 706 420 211

Life Insurance Premiums, F2017 62 286 185 93

General Insurance Premiums, F2017 18 80 59 26

Total Internet users (Mn), F2017 432 1,010 915 841

E-commerce, F2017 15 251 200 105

Market Cap (Overall) 2,100 8,500 6,100 3,700

Market Cap (Consumers) 525 2,975 2,000 962

Market Cap (Financials) 460 2,904 1,844 917

BSE Sensex (Points) 31,627 1,30,000 1,00,000 65,000

Aggregate Trading Volumes 21,289 57,375 40,951 23,618

Cash Trading Volumes 1,131 6,375 4,575 2,220

CurrentF2027E

US$ Bn

Source: RBI, CEIC, AMFI, Capitline, NSE, BSE, Bloomberg, Morgan Stanley Research (E) estimates. Note * GDP growth forecast is 10-year average.

a) Ultimately, Stronger GDP Growth = Stronger Equity Market Performance

The concomitant impact of higher GDP growth is that corporate earnings growth is also likely to accelerate. India's history shows a good correlation between nominal GDP growth and earnings. We expect this relationship to persist in the future. Ultimately, earnings growth is what drives share prices – but we also expect Indian multi-ples to expand. We think India's stock market could be among the world's best performers in the next ten years, leading to India's market cap rising from ~US$2 trillion to ~US$6 trillion.

1. Stronger economic growth should drive stronger corporate earnings growth: Strong nominal GDP growth plus a rising ratio of credit to GDP should be good for corporate earnings, and a low starting point of corporate profits / GDP, which sits well below trend, augurs well for corporate profit growth in the coming years.

Profit share in GDP is a function of the investment cycle, the current account, and the saving rate of the government and households. We see the investment cycle turning in the coming months. The govern-ment’s saving rate is rising, which is a likely drag on earnings – but the changing mix of household saving from physical to financial is a big boost for profits. The current account appears to be contained, which is again good for the share of profits in GDP.

2. We also expect equity multiples to expand: Two factors are likely to drive this expansion.

Strong domestic participation: We think India is in the midst of a domestic liquidity supercycle. The starting point of under penetra-tion combined with digitization almost guarantees growth in finan-cial assets and liabilities on the household balance sheet driving up the size of the domestic mutual fund industry and household owner-ship of equities. We project equity saving of US$420bn–US$525bn over the next ten years, versus the respective US$60bn and

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US$120bn that households and foreign portfolios invested over the previous ten years. The three main sources of these flows are mutual funds, pension and provident funds, and insurance companies. ETF AUM could see 30x growth in the next decade, driven by provident fund flows.

The effect of the declining ratio of public debt to GDP: As we argue, robustness in government revenues due to the execution of GST will likely to lead to lower public debt to GDP. This leads to a crowding in of private investments with a positive impact on interest rates and inflation. This will also lead to higher multiples, which is evident from the historically inverted relationship between change in public debt and PE multiples. We see the BSE Sensex crossing the 100,000 mark, albeit the bulk of the returns are likely to be front ended in the coming five years.

b) Financials and Consumption Sectors to Gain Share in the Market at the Expense of Global Sectors

Together the financials and consumer sectors could account for 63% of India's market by 2027, up from 47% currently, largely at the expense of global sectors such as software services, pharma-ceuticals, materials and energy.

We forecast market capitalization of the financials sector to grow 4x from current levels, to US$1.8 trillion in the next ten years: The past two decades have been very strong for Indian finan-cials. Listed market cap has increased from less than 2% of GDP in 1998 to 16% now – an >80x increase in nominal terms. This has been driven by various factors with the setting up of efficient businesses (private banks and well-run non-banking finance companies) as a key anchor. These businesses took away share away from the inefficient state-owned banks that dominated the banking scene until the mid-1990s. We expect the financials sector's share in India's market cap to rise to 30% from 22%, currently.

Prior to the ongoing technological revolution, our view was that Indian banks would struggle to grow credit higher than GDP growth given the expansion in the base. However, we have altered our view due to the advent of fintech, which aids financial penetration, as well as the likely transfer of market share from the capital starved SOE banks that currently control almost 55% of the market - now we think banks will grow faster than nominal GDP in the coming decade. We expect private sector banks, non-banking finance companies, cap-ital market intermediaries, private sector insurance companies and select fintech companies to be the beneficiaries, accentuating the trend that has already been in place for the past five years.

Consumption sector - We forecast market capitalization of the consumption sector to grow 4x from current levels, to US$2 tril-lion in the next ten years: Future consumption is being advanced through leveraging, and non-food consumption itself is likely to grow faster than overall consumption, setting this sector, especially dis-cretionary consumption, up for strong performance in the coming ten years. Consumption-related sectors including consumer discre-tionary and consumer staples are just over 25% of the market. We estimate this ratio could rise to 33%.

c) The Stock Winners

Exhibit 6 outlines the potential winners from the digitization story of India. We cannot claim this is an exhaustive list but it is good starting point for an investor who wishes to participate. The charac-teristic of this list is that it contains companies from across the world, because the benefits of India's digital initiatives will be felt globally.

For global companies on this list, we have focused on their exposure to India as a share of their overall business combined with the foot-print plans. Indeed, the drivers of growth, I.e., financial, consumption and e-commerce for a key filter criteria for us.

For Indian companies, we look for companies with a strong track record of return on capital as well as our estimated return on capital combined with reasonable stock valuations. The macro exposure to consumption and the financial sector is an over riding feature for our selection. We have left out smaller stocks from this list.

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Exhibit 6:Key Stocks: Our Comments on Why Indian Growth Matters


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AlphaWise Survey Results: MSME Survey - Rising Awareness Towards Digital India

We carried out our survey in July and August 2017 with 1,522 micro & small businesses and merchant establishments across 28 cities in India using face-to-face interviews. The survey sought to understand the payment and financing options used and likely to be adopted by these businesses, as well as the drivers and barriers to adoption. The survey represents the micro & small businesses in the large metro and smaller cities in India. Some of the key takeaways from the survey were:

Adoption of digital payments to be driven by eco-system support and convenience: There has been a meaningful increase in awareness and usage of digital payment options – even for newer options like UPI (Unified Payment Interface) / BHIM (Bharat Interface for Money). Businesses have seen a significant drop in cash transactions in the past 6-12 months. The share of new channels is still low and the bulk of demand is still driven by cards. Data suggests that customer demand, support by the eco-system and convenience are the key drivers of adoption, and to that extent the cost of transaction is sec-ondary.

While awareness of UPI / BHIM is quite healthy, its adoption is unlikely to pick up in a big way like cards or wallets since they don’t see much demand from customers for this. There has to be more steps taken to increase awareness and hence usage of these new pay-ment options.

Digital payments to drive access to credit; cost of funding to be key: According to the respondents, currently only a third of working capital is being funded through formal channels (funding is mainly to larger and B2B business). The major share is coming from own funds, followed by personal loans from banks / NBFCs (among those who don’t have bank credit). However, as businesses adopt digital pay-ments and see businesses that have adopted digital payments get better access to formal credit, they are more inclined to explore avail-ability of formal credit – though cost of funds would be the key deciding factor. Businesses do believe GST will help them in getting access to formal credit.

We have incorporated the results of this survey in this note.

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Key RisksInvestors should be cognizant of the things that can go wrong with our thesis:

l Politics and policy: Political instability or shifts in policy away from digitization would present risks to the core thesis.

l Cyber security: Since a large part of this transformation is about the Internet, cyber security presents an active and important risk to the story.

l Privacy debate around Aadhaar: While the Supreme Court in India has made privacy a fundamental right in a recent landmark judgement, private parties will likely con-tinue to question whether Aadhaar violates privacy rights. Any adverse judgement in the courts could derail one the main anchors of our framework.

l Smooth transition to GST: The GST rollout has begun well but it is still work in progress. In the short run there could disruption to smaller businesses causing job losses and a general slowdown in economic growth.

l India’s often discussed macro risks: India's demographic dividend could become a problem if the country is unable to execute on infrastructure, generate enough jobs, and educate the people and keep them healthy.

l Deep global recession: While India's story is idiosyncratic given the size of the economy, it needs a stable global economy to deliver growth. A global crisis like we saw in 2008 could damage India's growth prospects.

What If Digitization Fails?

If India's initiatives face road blocks in any of the aforementioned ways, our forecasts will be challenged. For our bear case to unravel, other things also need to go wrong. But failure of the digitization effort will likely cause our estimates for the economy, markets and financial services to end up somewhere between our base and bear case. This means that:

1. GDP will likely settle at US$ 5.5 trillion, implying a nominal growth rate of 9% over the next ten years.

2. India's market capitalization could grow more modestly at 9% to US$ 5 trillion by 2027.

3. Loan growth by banks will likely be closer to 10% CAGR for the coming decade as MSMEs struggle to get loans and corporates move to bond markets compared to the current base case of ~13% CAGR.

4. Accordingly the financial and consumer sector returns may also be tempered and the respective market capitalizations will likely settle at lower levels somewhere between our bear and base case.

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Key Takeaways1. India is shifting from being a cash-dominated economy to one that is digital enabled, by Aadhaar, large-scale bank account openings, increased mobile penetration and a sharp decline in data charges (JAM). The technology infrastructure includes a real-time mobile payment system (with most banks as participants) that allows C2C and C2B payments, an inter-operable Quick Response or QR code system and a real-time bill payment system.

Bank-backed systems are likely to benefit considerably, but larger mobile payment companies should also do very well given significant customer and merchant acquisitions.

2. In our base case, we assume that digital payments can increase to ~20% of GDP over the next ten years, implying a CAGR of ~30%. Currently Visa and Mastercard are the biggest players in digital payments, with ~80% share. We expect new avenues (such as UPI, Mobile Wallets and Rupay Cards) to quickly account for two-thirds of the digital payments market by 2027.

3. GST, the other leg of India’s digital lift, is a sweeping change to India’s archaic tax laws that will boost government revenues and corporate profits. It will also likely lead to a major change in credit availability for micro firms, in turn formalizing the Indian economy.

Digital Payments and GST - The Catalysts of Change

Why Have Digital Payments Lagged in India?

Exhibit 7:India has Lagged Materially in Digital Transactions (Per Capita Non Cash Transactions)

11 26 32 70

142

355

728

0

150

300

450

600

750

India China Mexico SouthAfrica

Brazil UK Singapore

Non Cash Payments Per Annum Per Capita

Source: Niti Aayog

Cash is the predominant form of payments in India. As per Niti Aayog (an Indian government policy think tank), the number of non-cash transactions per capita is one of the lowest among big economies at ~11 per year.

This has been driven by both aversion to non-cash transactions and a lack of payment infrastructure. To start with, there was reluctance among consumers to use means other than cash. This was accentu-ated by the lack of payment options. This was true in both urban and rural areas. In urban areas, bank branches have been omnipresent - but acceptance of non-cash form of payments has been limited. For instance, if we look at POS terminals in India, as of 2015 the POS den-sity was ~1,000 terminals per million people. The numbers in other EMs have been much higher - for instance, Brazil is almost 25x India.

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This has been driven by various factors:

1. Consumer awareness towards digital payments has been fairly lim-ited in India. Digital payment as a mode was not available to most of them - and even when it was available, they preferred cash given habits and the ease of use. The government drive since late 2016 to increase digital payments has increased awareness and usage, but it will take time for them to proliferate.

2. The dominance of cash in the economy was due to the fact that both merchants and customers wanted to pay in cash, as that would keep transaction records away from formal reporting.

3. The cost of setting up physical infrastructure has been quite high, especially for smaller businesses and merchants. As per Visa, the cost of a POS machine is Rs 8,000-12,000. On top of this, the annual oper-ating cost per machine is Rs 3,000-Rs 4,000. This makes it costly for a small merchant to set the machine and start accepting card pay-ments.

Exhibit 8:The Number of Point of Sale (POS) Terminals per Million People Is Very Low in India

0

7000

14000

21000

28000

35000

42000

India

Mexic

o

So

uth

Afr

ica

Russia

Bra

zil

UK

Sin

ga

pore

Canada

Au

str

alia

POS Terminals per Million population (2015)

Source: Niti Aayog Report

4. While the interchange rate (MDR - Merchant Discount Rate) in per-centage terms is not very high in India (0.5-2.0%), merchants are averse to paying this MDR given the relatively low margins of their operations. A number of small merchants would add the MDR to the bill when a customer paid by card - thereby incentivising cash pay-ments.

5. The low value of transactions at smaller merchants coupled with the capping of MDR by RBI (Reserve Bank of India) meant that banks were averse to expanding POS terminals to smaller merchants.

AlphaWise: Our survey of ~1,500 businesses showed that the share of cash transactions in turnover (for this set) is 59%. About 30% have more than a 75% share of cash, about 25% have a share of cash between 51-75%, and for 45% the share of cash transactions is 50% or lower. Businesses with a lower share of cash are those with a higher turnover and B2B businesses, while the larger segment i.e. B2C businesses have a much higher share of cash transactions, espe-cially in Tier III cities. Habit/ease of use and help in managing pay-ments / cash flow better were mentioned as the key drivers of cash usage.

Exhibit 9:Why Is Usage of Digital Options Lagging?

88%

61%

57%

31%

Habit / Ease

Supplier driven / to manage purchases / cash flow

Due to customer preference

No transaction / equipment costs

Source: AlphaWise, Morgan Stanley Research

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Government and Regulatory Drive Towards Digitisation

Exhibit 10:Government Targets a 6x Increase in the Number of Annual Retail Dig-ital Transactions

0

5000

10000

15000

20000

25000

30000

F13

F14

F15

F16

F17

F18 (

Govt T

arg

et)

Digital Transactions (Volume, Mn)

Source: RBI, Morgan Stanley Research

The situation with digital payments is changing now. Both the gov-ernment and regulators realize the importance of cashless transac-tions and the potential impact on sustainable economic growth.

From a regulatory perspective, there has been a significant push to create a digital payment infrastructure to increase adoption. From the government side also, there has been a continued push towards adoption of digital payments. This will improve the visibility of cash flows in the economy and thereby help the economy grow on a more sustained basis.

The pace of pickup in India has been fairly good (off a low base), with about a 50% CAGR between F2013 and F2017. However, the govern-ment has laid out a very ambitious target of increasing the number of digital transactions to about 25 billion in F18 - around a 6x increase in one year. And it is moving aggressively towards ensuring it reaches the target.

In our report, Global Financials and Payments: Fintech – A Gauntlet to Riches (17 May 2017), the Morgan Stanley research team high-lighted the key drivers for a successful fintech framework. In our view, supportive regulations and availability of data to everybody are among the key factors required for a successful framework - India clearly embodies this.

Exhibit 11:Morgan Stanley Framework for Fintech Success - India Embodies Most of These Factors

Financial Infrastructure Underdeveloped?

Amid Inflection in Consumer Behavior, e.g.

Technology?

Government Actively Driving Change?

Industry Highly Fragmented?

Well-Defined & Accommodating Regulation?

Success in Fintech

No

No

Financial Data Accessible?

Disruption less likely;

Better off partnering with incumbents;

Or slow disruption carried out by incumbents Rapid Disruption/

TAM Creation

No Yes

No

Yes

Yes

No

Disruption possible, but slower to play out

Does this product truly add value? Enough to drive change among

inertial consumer financial behavior? If not, stop here. Yes

Yes

No Yes

Digitization will help improve data

availability materially

Source: Morgan Stanley Research

https://ny.matrix.ms.com/eqr/article/webapp/b70eb5ce-25d9-11e7-b132-327dac2266b1?ch=rpint&sch=sr

https://ny.matrix.ms.com/eqr/article/webapp/b70eb5ce-25d9-11e7-b132-327dac2266b1?ch=rpint&sch=sr

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We believe that it will be tough for India to achieve 25 billion transac-tions in F2018. But given the ambitious target and policy makers' drive to achieve this, we would still expect a 3-4x increase in transac-tions in one year. All the parts of the infrastructure required to drive a strong pickup are falling into place in India.

As mentioned in the AlphaWise survey above, the main reason for the high usage of cash in the economy has been awareness, habit and ease of use of cash compared to various digital payment options. But the government drive to increase awareness and the strides made by mobile wallet companies during the Currency Replacement Pro-gramme (CRP) at the end of 2016 have increased awareness about digital payment options materially.

Exhibit 12:Digital Payment Options: Awareness of Older Options Has Increased Meaningfully - Though This Remains Low As Share of Transactions

80%

50%

65%

30%

52%

21%

28%

3%

16%

4% 5% 0%

Debit / Credit Card Direct transfer Mobile Wallet BHIM/UPI

Awareness Usage Share in transactions

Source: AlphaWise, Morgan Stanley Research BHIM = Bharat Interface for Money

India Has Set Up a State of the Art Digital Payment Infrastructure

Three big trends have emerged in India over the last six to seven years. These have brought about a universal identification / authenti-cation mechanism for the entire population (Aadhaar), ensured that every household in India has access to a bank account (Jan Dhan), and led to a surge in mobile penetration and a rapid pickup in smartphone usage. Government and policy makers realized that combining these trends would be quite powerful, and this has given rise to the JAM (Jan Dhan, Aadhaar, and Mobile) initiative. Appendix 1 explains in detail the various payment networks that have been set up in the country.

Some key indicators about this JAM mega-trend are as follows.

1. In August 2014, India launched a plan to ensure everybody has a bank account. Since then, ~285mn bank accounts have been opened under this scheme. Prior to the launch of this policy, ~35% of house-holds in India did not have a bank account. But now we estimate that most Indian households have access to a bank account.

2. The universal identity programme was launched in 2010. The intent was to ensure that every Indian has a form of identification. Since then, the government has created a biometric digital database (with fingerprints and retina scans) of 1.2 billion people, which is 92% of the country's population. Prior to this, nearly half of the country had no form of identification.

3. There has also been a surge in usage of mobile phones in India, with the number of mobile connections at ~90% of the population. This was enabled by fairly cheap telecom tariffs in the country and the launch of no-frills low-priced phones. There has also been a sharp increase in smartphone penetration, with ~25% of mobile phones in

the country today being smartphones. Since 2012, the share of smartphones in total shipments has increased from 7% then to 50% now, and we estimate it could reach 100% by 2020.

The other factor that is acting as a big driver is the sharp decline in data charges. Data charges were already coming off meaningfully and the launch of Reliance Jio has caused this to fall even more (the blended data charge is down from around Rs. 400 per GB in 2012 to around Rs 60 per GB currently). This means that everybody with a smartphone also has a bank account and digital identity, and that person can now be constantly connected to the internet.

India Stack - Bringing This All Together

The above initiatives are major advances but somebody needs to take the lead and combine them into product offerings. This is being driven by India Stack. This is a set of APIs (Application Programming Interfaces) that leverages this infrastructure to move towards a pres-ence-less, paperless and cashless service delivery - see Appendix 1 for details.

A number of APIs have been launched, with full regulatory backing, that utilise this infrastructure. Some of the key ones are e-KYC (which allows electronic KYC, making customer acquisition quick and very low cost); UPI (which allows mobile based payments on a real-time basis between individuals and businesses); the Bharat QR code (an interoperable QR code system with all the key payment gateways and banks on board); the Bharat Bill Pay System (moving all bill pay-ments in India - telecoms, utilities, government and so on - to one platform); and the Aadhaar Enabled Pay System (which enables people to carry out transactions using an Aadhaar Card and finger-prints for biometric authentication).

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This may feel like a long list of initiatives. But they essentially cover the entire gamut of payments in the country. All one needs to make these payments is a mobile phone and a bank account. These are real time and also, given that these systems are regulator backed, they are interoperable, which should help digital payments to grow quickly in the country. A detailed explanation of these initiatives is in Appendix 1.

Exhibit 13:India: Key Initiatives Using India Stack and JAM


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Fintech companies have been using the increased mobile pene-tration to grow digital payments quickly

Exhibit 14:M-Wallets Transactions Versus POS

10 29

82 206

532

793

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

0

200

400

600

800

1000

F2013

F2014

F2015

F2016

F2017

F1Q

18 (

Annualiz

ed)

M-Wallets Transaction Values (Rs Bn) As % of POS Transactions, RS


As mobile phone penetration has increased in India over the last few years, various fintech start-ups became significant players in the pay-ments eco system. This is similar to the situation in other big markets such as the US and China where a majority of the large fintech compa-nies originated in the payments space given the large market oppor-tunity and the need for a ubiquitous experience for all in the value chain - especially consumers and merchants.

Mobile wallets have been the pioneers of digital payments in India. A number of these were set up over the last few years (PayTM, Mob-iKwik and Freecharge among others). These wallets started off focusing on fairly niche payment streams - like mobile phone recharging - but have evolved into systems straddling the payments space. Transaction values on mobile wallets have also picked up materially - from a slow start in F2012, the transacted value reached Rs532bn in F2017 (~8% of POS transactions) and if we annualize F1Q18 data, it will likely be 1.5x the F2017 figure in F2018.

Exhibit 15:Breakdown of Fintech Funding into Various Sub-categories: Payments Dominate the Total Funds Raised

84%

55%

86% 82%

4% 3% 3%

2%

37%

9% 9%

9% 5% 1% 5%

1% 3% 1% 1%

0%

20%

40%

60%

80%

100%

20

15

20

16

2017 Y

TD

Cum

ula

tive

Payments Mobile POS Lending Wealth Management Insurance

Source: Economic Times, VC Circle, Morgan Stanley Research

Funding into fintech has been very strong - A number of products offered by fintech payment providers have to be seeded by a strong capital base - given fairly large losses in the early years of customer acquisition. This has been helped by strong fund flows into the Indian fintech space from venture capitalists, private equity and strategic partners since 2015. Total funding to fintech companies has been US$3.1bn since 2014.

As these wallets have evolved, their usage have moved to various types of payments. For instance, telecom recharging was a large part of wallet usage until two or three years back. This is now around a quarter of usage and various other uses have picked up, driving the sharp growth seen in the last one or two years. This is similar to China, where usage has evolved quickly over the last decade.

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Exhibit 16:Digital Wallets' Segment-wise GMV Share: Uses for Digital Wallets Have Expanded Over Time

0%

22%

45%

14%

20-25%

3%

8%

15-20%

9%

4%

11%

3% 25-30%

16%

2%

1-2%

16%

47%

20-22%

China (2005) China (2016) India (2016)

P2P, utilities and others

Online gaming

Telecom recharging

B2B eCommerce

Flight ticket/travel

Online shopping

Fund purchasing

On-demand online platforms and Offline (not included in China data)

18-23%

Source: iResearch 1Q-CY2016 press release for China data, Company data and industry sources for India data, Morgan Stanley Research Note: China data in the chart above is for desktop only; segment-wise data (especially for on-demand online platforms and offline transactions) on mobile is not available publicly and hence not included

Roll-Out of Digital Infrastructure Should Cause Greater Acceptance and a Surge in Digital Payments

Digital payments in India grew at a good pace from F2005-F2014, at ~26% a year. However, this was against the backdrop of fairly good nominal GDP growth and a strong pickup in private banks' share in India, implying greater card usage. If we look at digital payments as a percentage of GDP, the move was fairly gradual from ~1% of GDP in F2006 to ~2% in F2014. Since then we started seeing a pickup to 3% of GDP in F2016 and ~5% in F2017 (with the sharp uptick driven by the government's various initiatives).

When we compare India with other markets, digital payments in India (even after the F17 pickup) have lagged those in most markets. We look at payments as a percentage of GDP and also payments as a per-centage of national personal consumption expenditure - on both counts, India has lagged.

Exhibit 17:Cross Country Comparison: Digital Payments as a Percentage of GDP

5% 7%

8% 8% 9%

15% 16%

19% 19%

25%

27%

30% 32% 32%

44%

0%

10%

20%

30%

40%

50%

IND

IA*

GE

RM

AN

Y

RU

SS

IA

ME

XIC

O

ITA

LY

NE

TH

ER

LA

ND

S

SO

UT

H A

FR

ICA

BR

AZ

IL

FR

AN

CE

AU

ST

RA

LIA

TU

RK

EY

US

A

CA

NA

DA

UK

KO

RE

ASource: BIS, Morgan Stanley research; India data is for F17. For others data as of 2015.

Exhibit 18:Cross Country Comparison: Digital Payments as a Percentage of PCE

8.3% 11.6% 12.3%

14.8% 15.9%

26.9% 28.8%

34.5% 35.0%

42.6% 43.8% 45.1%

51.4% 55.9%

91.7%

0%

40%

80%

120%

IND

IA*

ME

XIC

O

GE

RM

AN

Y

ITA

LY

RU

SS

IA

SO

UT

H A

FR

ICA

BR

AZ

IL

NE

TH

ER

LA

ND

S

FR

AN

CE

US

A

AU

ST

RA

LIA

TU

RK

EY

UK

CA

NA

DA

KO

RE

A

Source: BIS, Morgan Stanley research; India data is for F17. For others data as of 2015.

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We expect this to increase to around 20% of GDP by F2027, implying a CAGR of ~30% for the next ten years. What will drive this?

Exhibit 19:India: Millennials as a Percentage of Work Force

36% 39%

42% 45%

48% 51%

54% 56%

59% 62%

64% 67%

69%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

Source: UN Population database, Morgan Stanley Research

1. Continued increase in younger population in the work force - India has among the highest numbers of young people entering the work force over the next two decades. As per UN estimates, in 2027, millennials in the work force will be ~680 million people, an increase of ~350 million compared with the 2016 level - that’s ~70% of the work force. These individuals are not attached to old banking habits and they will have access to mobile phones / smartphones. We would expect them to adopt digital banking much more quickly than past generations.

2. The payment infrastructure that is now available in India is amongst the best in class and completely inter operable (with almost the entire banking system and various payment networks). Hence, the issue of availability has been taken care of.

Exhibit 20:Currency in Circulation as a Percentage of GDP

6%

7%

8%

9%

10%

11%

12%

13%F1999

F2000

F2001

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Sep-2017

Currency in circulation, % of GDP


3. Less currency in the system - Between F2000 and F2016, the amount of currency in circulation went up sharply (~8x), growing at a CAGR of 14%. Also, as a percentage of the formal banking system, the proportion rose materially to 20% from 12% in F2000. This flow of currency enabled cash transactions to flourish.

However, the currency replacement programme has disrupted this trend. Currency in circulation as a percentage of GDP had declined to ~8.5% from 12% in F2016. Although this number has started rising (now ~9.7%), we expect it to stabilise at well below pre-November 2016 levels. This reduction in cash availability will raise the levels of acceptance amongst both consumers and merchants of digital pay-ments.

4. More aggressive tax code will reduce the ability to evade taxes - India also launched the Goods and Services Tax (GST) regime in July 2017. Under GST, a buyer of goods or services will be able to take credit for the tax paid only when the supplier files taxes and gives the data to the GST. The GST Network (GSTN) will maintain the data on tax paid by the entire value chain - and hence, if any part of that chain evades taxes, the cross check will capture this discrepancy. This should dis-incentivise tax evasion.

As tax evasion becomes tougher, one of the deterrents to digital acceptance - that cash transactions are not recorded - will become less important. This should make merchants - big and small - more amenable to the acceptance of digital payments.

5. Lower Merchant Discount Rates (MDR) - A deterrent to accept-ance of non-cash payments historically has also been the relatively high MDR charges, especially on debit cards where the issuing bank is not taking any credit risk. RBI has lowered the rates since 2012 on debit card transactions - from similar to credit card rates to rates based on the value of the transaction (currently this stands at 0.25% for transactions up to Rs. 1,000 in value, 0.5% for Rs 1,000-2,000 and 1% for transactions above Rs 1,000).

Although the pressure to reduce MDR is reasonably high, RBI has to ensure it is economical for merchant acquirers to conduct this busi-ness. Otherwise these banks will stop acquiring merchants. Now RBI has issued a draft paper suggesting MDR on debit cards should be linked to the size of the merchant. The idea is to ensure that payment infrastructure can be adopted by small merchants also.

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Exhibit 21:RBI: New MDR Proposal

For Physical POS For Digital POS

Small / Special category merchants Not > 0.4% Not > 0.3%

All other merchants Not > 0.95% Not > 0.85%

Government transactions

MDR as % of Transaction Value

Flat fee of Rs5 for up to Rs1000. Fees of Rs10 for

Rs1000-2000. MDR not exceeding 0.5% for greater

than Rs2000 with a cap of Rs250.


A likely effective move by RBI has been to differentiate between physical POS and digital POS (UPI, QR and so on) based payments. For the non-physical payments, banks do not have to invest in the POS infrastructure and so on and hence MDRs should be much lower than with physical POS. While RBI has suggested a 10 bps gap between physical and non-physical, we would expect the downward pressure on non-physical to intensify over the next few years.

This will be driven by the fact that the cost of these transactions is relatively low. And also there has been a sharp increase in competi-tion. PayTM has been aggressive in acquiring merchants and is charging no MDR. Since November 2016, it has acquired almost 5 mil-lion merchants (this compares with 2.8 million merchants who accepted card-based payments as of July 2017). Although these are for transactions on its wallet - not interoperable - the surge in mer-chant acquisition will likely cause incumbent players to revisit the MDR charged on digital networks or stand to lose share to fintech alternatives.

6. Access to credit - As we discuss in detail in the next section, the data trail from increased usage of digital technology should have a lot of upside for both merchants and consumers. Lenders will be able to use this data to map their cash flows better. This will enable increased lending to the smaller borrowers at reasonable rates (given improved underwriting). This should also help increase acceptance of digital payments by a significant amount.

Korea could be a case study for IndiaJust as India has launched the government initiatives described above, Korea took steps in the late 1990s to reduce the shadow economy. This drove a sharp increase in digital payments. In the 1990s the Korean government wanted to increase card transactions (away from cash) to increase tax compliance. This drove up tax compliance among businesses in Korea. Some of the steps taken by the government were as follows:

1. The Korean government introduced tax incentive schemes to increase the use of credit cards. In 1999, it introduced a new scheme which offered tax rebates if the total spend through credit cards, as a percentage of annual income, was above a certain threshold (25%). But this was a big driver for the surge in credit card usage.

2. It also introduced a lottery scheme where the game was based on the invoice number of each credit card transaction. There were weekly winners with both the consumer and the merchant (at whose business this transaction was conducted) winning a prize.

3. The government also made it mandatory for businesses to accept card payments if the consumer wanted to pay with a card.

Exhibit 22:

Korean Experience: Credit, Debit and Prepaid Card Transactions as a Percentage of GDP Rose Sharply Following Introduction of TIETP in 1999 Incentivizing Wage and Salary Earners to Use Credit Cards

0%

9%

18%

27%

36%

45%

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Credit Card Debit Card Prepaid Card

Source: World Bank Group Report, Bank of Korea

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There were other factors too - like banks' willingness to lend aggressively on credit cards after the Asian crisis. Credit card transactions grew ~9x in absolute terms and from 4.9% to 34.3% as a proportion of GDP between 1999 and 2002. Korea extended the tax scheme to transactions on debit cards also, which saw a surge in debit card based transactions.

There was a credit card crisis in Korea after 2002, given the sharp loan growth. But for India, the government can offer tax incentives targeted towards digital transactions linked to existing savings accounts (debit cards, UPI, pre paid wallets and so on). The introduction of tax incentives drove up the amount of debit card transactions. Given the plethora of digital payment options available in India now, such incentive schemes can act as a catalyst to quicker digital adoption.

We expect the value of digital transactions to increase over 10 years by ~12x in our base case and ~18x in our bull case

Total digital payments as a percentage of GDP was ~5% in F2017, up from ~3% the prior year. As a proportion of total personal consump-tion (PCE) this stood at ~8%, well below those of other EM countries such as Brazil (30%), South Africa (27%) and Russia (16%). Given all the changes afoot, in our base case we expect this to increase to ~20% of GDP by F2027 - which would imply a CAGR of 30% for the next 10 years. This would take digital transactions as a percentage of PCE to ~36%.

Exhibit 23:Digital Payments (Percentage of GDP)

1% 1% 1% 1% 1% 1% 1% 1% 2% 2% 2% 3% 3%

5% 6%

20%

0%

5%

10%

15%

20%

25%

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F1Q

18

F2027E

Digital Transaction Values / GDP

Source: RBI, NCPI, Morgan Stanley Research (E) estimates

Exhibit 24:Digital Payments (Percentage of Personal Consumption Expenditure)

1% 2% 2% 2% 2% 3% 2% 3% 3% 3% 4% 4% 5%

8% 10%

36%

0%

8%

16%

24%

32%

40%

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F1Q

18

F2027E

Digital Transaction Values, as % of Private Consumption

Source: RBI, NCPI, CEIC, Morgan Stanley Research (E) estimates

Is this a big stretch? We don’t think so. In fact if the government is completely successful in pushing its digital agenda, this target will likely be achieved much more quickly - as we mentioned earlier, its target is to increase digital transactions 6x in this year alone. If suc-cessful, this can cause digital transactions increase to ~30% of GDP by F2027 (a CAGR of ~35% over the next 10 years).

Who will be the winner(s) in digital payments?

Exhibit 25:Digital Payments to Shift to Non-card Transactions

78% 83% 85% 84% 82% 78% 70% 66% 64% 62% 61% 59% 57%

46% 43%

22% 17% 15% 16% 18% 22% 30% 34% 36% 37% 38% 38%

37%

42% 41%

0%

20%

40%

60%

80%

100%

F2

004

F2

005

F2

006

F2

007

F2

008

F2

009

F2

010

F2

011

F2

012

F2

013

F2

014

F2

015

F2

016

F2

017

F1

Q18

Credit Cards POS Debit Cards POS Ex Rupay M Wallet Rupay Cards POS UPI

Source: RBI, NCPI, Morgan Stanley Research

We expect a continued shift in market share away from current leaders - Historically credit cards were the main form of digital pay-ment, but over the last few years debit cards have caught up. Till 2015, credit and debit cards made up almost 100% of retail digital transactions. Visa and Mastercard were the main payment gateways used for digital transactions.

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However, this is changing. Mobile wallets and UPI made up ~11% of total transactions in F1Q18. Within cards also Rupay card (which is a domestic card payment gateway launched three years ago) is gaining ground and accounted for ~10% of total debit card transactions at POS terminals in F1Q18.

In our view, the alternative payment avenues - UPI, wallets and Rupay debit cards - are likely to be the big drivers of the expected sharp increase in digital payments. We expect the share of these new players/payment systems to increase from the current ~15% to 65-70% over the next 10 years. In fact, we will not be surprised if the pace of the market share shift is even quicker.

While we are building in the market share decline for the incumbents - Visa / Mastercard - we still expect them to show reasonably good growth. The launch of Bharat QR, which is interoperable and does not need POS terminals, should help them grow despite transactions moving to mobile-based platforms. The table below shows that even if Visa / Mastercard market share reduces to 35%, they will still likely grow at a CAGR of ~16%.

Exhibit 26:Sensitivity of Visa / Mastercard Share and Ten-Year CAGR

Current Digital Payments in India, F2017, USD Bn 107

V/MA Share 90.0%

MS Estimate on 2027 Digital Payments Market Size, USD Bn 1208

V/MA's share in 2027, scenario 10% 25% 35% 50% 75% 90%

Implied CAGR 2.3% 12.1% 15.9% 20.1% 25.1% 27.4%

Source: RBI, Morgan Stanley Research estimates

Within non-card payments, who will win - wallets or bank-backed sys-tems?

Exhibit 27:Mobile Wallets and UPI as Percentage of Retail Digital Transactions; Both Are Growing, With UPI Catching Up Quickly (It Was ~40% of Wallet Transactions in F1Q18)

1% 1%

3%

5%

7% 8%

0%

1%

3%

0%

3%

6%

9%

12%

15%

F2012

F2013

F2014

F2015

F2016

F2017

F1Q

18

Mobile Wallet UPI

Source: RBI, NCPI, Morgan Stanley Research

Globally tech companies have led the digital wallet space. In both the US and China, traditional banks have been virtually non-existent in the digital wallet space. In the US, PayPal leads the digital wallet space. In China, Alipay leads the space followed by Tenpay. Tech com-panies have been able to establish a dominant position given their unique value proposition of managing card-not-present (CNP) risks for the merchants and a simplified checkout process for the con-sumers.

However, unlike China where wallets dominate the digital payment, in India banks should do well. Mobile wallets have the first mover advantage, but we expect banks to catch up. The reason is that, unlike in China, regulators in India have pushed for a real-time digital pay-ment infrastructure set-up before wallets became ubiquitous. Hence, while wallets will grow, it is unlikely that all of them will prosper. There will be a handful of winners, with the others being consolidated by larger players or banks (for instance in August 2017 Axis Bank bought out Freecharge, one of the bigger wallet players).

Over the last few months, the value of digital payments in India has increased sharply, with digital retail transactions up ~36% in F1Q18 (annualised) compared with F17 - this is despite F1Q being the weakest quarter seasonally. Within this, mobile wallet transactions are up ~50%. UPI on the other hand has moved from negligible to ~3% of total digital transactions. This level is likely to rise fairly quickly as UPI is rolled out to consumers and merchants.

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26

GST Is Arguably India’s Most Important Reform Since the Early 1990s

GST, with its ability to clean up India's messy indirect taxation and lift government revenues, has the potential to boost growth. From the corporate sector's perspective, warehousing costs, freight costs, and inventory levels could all fall. Together with a more transparent and efficient input tax credit system, this should lead to improved profita-bility. Over the next two to three years, large companies could also gain share from MSMEs, whose hidden tax subsidy (if they never paid taxes earlier) is likely to vanish under GST. That said, it is not all bad news for MSMEs. Their entry into the formal economy, in addition to the transparency of the GST system, will enable flow-based lending to these entities, eventually lifting their growth as well as India's ratio of aggregate credit to GDP.

What is GST?

The goods and services tax (GST) implementation marks a major reform in India, as the initiative will transform India's indirect tax land-scape. GST was launched on July 1, after a prolonged discussion in political spheres and several rounds of amendments to the draft law. GST has subsumed all indirect taxes (VAT, excise, cenvat, entertain-ment, octroi, service and so on) and done away with India’s old system of multiple central and state taxes by replacing it with a single tax system. GST is a tax on consumption and will weed out the cur-rent series of cascading taxes on the production chain. GST imple-mentation will gradually shift the informal sector into the formal sector, leading to greater compliance and higher tax collection for the government. Compliance also improves because GST is com-pletely digital and an online platform – arguably the largest digital tax network in the world. The scale of operations is staggering. The GST network is expected to manage 30-40 billion transactions annu-ally paid by almost 10 million tax-paying entities, which implies 100mn transactions daily.

GST’s digital infrastructure

India’s central government has set up a Special Purpose Vehicle – GSTN – to manage the IT infrastructure under GST. GSTN is the front-end IT ecosystem under the GST network and will be an impor-tant part of GST compliance with respect to filing data. GSTN’s man-date is to establish, develop and manage the required infrastructure, systems, technology, partnerships, and eco-system for the imple-mentation of GST. Thus, it enables a uniform interface between the taxpayer and the government (both central and state). The IT sys-tems of the central and state tax departments function as back-ends

and handle tax administration functions such as registration approval, assessment, audit, and so on. For taxpayers, GSTN provides common and shared IT infrastructure and caters to functions facing taxpayers, such as filing registration applications, filing returns, cre-ating challans (invoices) for tax payment, settling IGST payment (like a clearinghouse), and generating business intelligence and analytics. Checking Input Tax Credit (ITC) claims is one of the important aspects of GST, for which data of business to business (B2B) invoices would be uploaded by taxpayers and matched by GSTN. The GST system has a G2B portal for taxpayers to access the GST Systems.

What advantages does GST bring to India?

GST implementation is a likely paradigm shift in the economy and corporate sector. The tax change aims to weed out the cascading effects of taxes on cost at the aggregate level and thus bring down the cost of doing business. While currently there are several tax rate slabs, it is quite possible that in the future the number of tax rates will be reduced. We outline below the impact on the corporate sector:

A single tax will lead to centralization and consolidation of ware-housing facilities for businesses: The removal of inter-state tax bar-riers, combined with seamless input credit, will make India one common market for goods and services, leading to economies of scale in production and improved efficiency in the supply chain. GST implementation implies lower warehousing costs and smoother movement of goods between states.

Productivity gains for the transportation sector: With the giving away of entry or state border taxes, freight movement is likely to speed up, leading to improved cost and time efficiency for the sector. The removal of inter-state barriers is important as roads account for almost three-quarters of freight traffic in India. However, efficiency remains low in the road transportation sector. In a day, trucks in India drive just one-third of the distance of trucks in the US (280 kilome-ters versus 800km) as only 40% of the time is spent in driving. Thus on overall costs, inter-state trade costs in India exceed inter-state trade costs in the US by a factor of six. Eliminating checkpoint delays could keep trucks moving almost six hours more per day, equivalent to 164km per day.

Inventory management to grow more efficient: The net effect of reduced warehousing and reduced transportation time is that inven-tory levels will likely decline. In the short run this hurts growth as well as credit formation (with a one-time decline in both). Beyond the first year, however, it will reduce costs for Corporate India.

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Claiming input credit for GST paid on services: Under GST, companies can set off taxes paid on inputs. For sectors with high competitive intensity, input credit would likely be passed on to the consumer while in cases where competition is not efficient or the industry is fragmented, companies could experience margin expansion.

Formal sector to gain market share from informal sector owing to tax rationalization: The biggest advantage that the unorganized sector enjoys currently is the tax arbitrage (due to being outside of the tax ambit). GST aims to integrate the informal sector into the formal sector over the medium term. The incentive of availing input credit on supplies would force the organized players to deal with suppliers that are registered with GSTN. In the GST regime, it will be almost mandatory to pay taxes because the entire supply chain will now have to be accounted for in the tax chain. The key rationale is that firms up the value chain would only contract with those companies/dealers whose taxes they can set off. This will encourage more com-panies from the informal sector to join the formal sector. As the unorganized sector gets into the formal system and thus gets intro-duced into the tax system, the tax arbitrage (their source of competi-tiveness) is expected to abate, benefitting the formal sector and allowing it to gain market share. The organized sector has a further advantage from lower warehousing costs, freight costs and inven-tory levels. We highlight industries and stocks from our coverage that we believe will benefit from this shift into the formal economy.

GST enabler for credit to the unserviced: Another big change that GST could potentially drive is credit to the unserviced segment. Out of the eight million entities that are potential users of the GST net-work, 65-75% are small and micro businesses that do not have easy access to bank credit. GSTN could act as an enabler for flow-based lending for these businesses as they form part of the GST network. With GST coming on board, tax filing would move from a back-end activity to a front-end activity. The process of GST would require filing of returns thrice a month (36 times a year). With the help of ASPs and GSPs, the government expects the filing process to be simple and convenient. GST records would have a full integration of purchases and sales of GST users. This information could be used by businesses as a means to avail working capital loans. This in our view could lead to unserviced entities coming into the credit system, thereby boosting credit to GDP and the growth of these businesses.

The Government Gains Too

GST completely alters the way government finances are managed in India. Hitherto, tax collection in India was decentralized while expenditure allocations were centralized through the Planning Com-mission, which set expenditure priorities for the states. GST central-

izes India's taxation, while abolishing the Planning Commission in 2014 had already set the stage for decentralization of expenditure. This shift, in our view, could prove cathartic for Indian government finances. India’s ratio of tax revenues to GDP is on the low side as compared to other EMs – and this has been a key reason why the fiscal deficit has been relatively high on a comparative basis. The implementation of GST will increase tax compliance amongst corpo-rates, leading to a boost in tax revenues even while the tax rates are in and of themselves revenue-neutral. Over time, as tax revenues improve, it should lead to a improvement in fiscal deficits and public debt to GDP trends in India. Niti Aayog (India's policy think tank) expects tax revenues to grow 50% over the next three years. Indeed, we estimate that if the primary fiscal deficit stays at 1.2% of GDP (as compared with an average of 2.1% over the past five years and 1.6% in F2017), the ratio of public debt to GDP should decline to below 60% by F2027.

Digitization will help bring down expenditure too. This will help the government conduct welfare spending in a much better way – quicker and more efficient implementation (with little leakage). The government has already implemented a direct benefit transfer (DBT) program, which is a social welfare scheme under which subsidy bene-fits are directly transferred to the beneficiary’s bank account rather than via the issuance of checks / cash payments / rebates. Cumula-tively, the total direct benefit transfer so far has been approximately Rs2 trillion and savings have been ~Rs500bn.

What are the challenges?

Despite the long-term positive implications, there could be short-term problems:

Growth impact: The one-time inventory adjustment has already caused some hiccups to growth.

Is India digitally ready? GSTN is fully digital but not all businesses in India are equipped to undertake digital transactions. This has the potential to create disruptions.

Informal sector set for a shock: The 'subsidy' to the informal sector in the form of tax evasion goes away, with a likely concomitant impact on jobs. The informal sector creates four out of five jobs in India. How long this may persist is difficult to estimate. There could be associ-ated supply chain disruptions that could last for several months.

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28

Implication 1: GST Plus Digital Payments = Significant Big Data Opportunity

Key Takeaways1. Lenders (banks / NBFCs / fintech companies) will get access to cash flow data of MSMEs (micro, small and medium enterprises) through multiple sources - for instance, digital payment platforms but more importantly GSTN (the Goods and Services Tax Network). This will likely help them get access to high-quality, high-frequency data that will allow them to lend to this sector. While MSME is a big part of the economy (over 30% of GDP), formal system lending to the MSME industry is just 10% of GDP - we expect MSME lending to have a ~17% CAGR over the next decade.

2. Consumer loans is the other sector that is likely to do well. As data availability becomes better and quicker, banks will be able to roll out new products (for instance HDFC Bank's "loan in 10 seconds"); in our view this, along with fairly strong economic growth, will help drive consumer loan growth at a 17% CAGR over the next decade. Even after this growth consumer loan penetration will be low at ~25% of GDP.

This growth in MSME and consumer lending will in turn boost economic growth and discretionary spending.

Exhibit 28:Material Shift in System Loan Mix Ahead: Consumer and MSME to Replace the Lower Share of Large Corporates

CAGR (%)

F2017 F2027e F2017-27e F2017 F2027e

Total Loans (Rs Bn) 102,524 344,681 12.9% 67% 78%

Consumer 24% 32% 16.4% 16% 25%

Housing 14% 19% 16.0% 10% 15%

Non Housing 9% 13% 17.0% 6% 10%

Non Consumer 76% 68% 11.6% 51% 53%

Large Industry 29% 17% 6.8% 20% 13%

MSME Industry (Banks) 5% 7% 17.0% 3% 5%

MSME (NBFCs) 4% 5% 17.0% 2% 4%

Services (Banks, including MSME**) 18% 20% 14.4% 12% 16%

Agri & Others 21% 19% 11.7% 14% 15%

Memo:

Overall MSME 15% 22% 17.0% 10% 17%

Mix (%) As % of GDP

Source: RBI, NHB, Company data, Morgan Stanley Research (e) estimates. ** Of bank credit to service sector, we have assumed 40% is towards MSME. NBFCs and HFCs lending to MSME are Morgan Stanley estimates

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The past 15 years for banks have been good - Indian financial system assets have grown at a CAGR of 16%. There was a period of strong growth (F2002-F2012) and then a period of fairly lackluster growth (F2012 onwards given the NPL issues faced by the corporate sector). Overall loan penetration went from 31% of GDP to 67% of GDP during this period.

Corporates were the big driver (first of an acceleration and then of a deceleration) in the past 10 years - First, corporates levered up to create capacity - both in infrastructure and industries such as steel - and then hit a bottleneck on profitability and have been delever-aging. This caused loan growth to be strong for three or four years and then become subdued for the past three years.

Our view is that banks' and NBFC's growth in terms of loans to corpo-rates will be muted (even when the economy picks up, we expect these corporates to access bond markets for funding given RBI's reg-ulations on exposures to large corporates). The sharp slowdown in corporate loans and weakness in most other lending segments (excluding consumer loans) have caused the credit multiplier in India to be <1 - this is a multi-decade low.

Exhibit 30:India Credit Multiplier at Multi-decade Lows

0.0

1.0

2.0

3.0

F1970

F1972

F1974

F1976

F1978

F1980

F1982

F1984

F1986

F1988

F1990

F1992

F1994

F1996

F1998

F2000

F2002

F2004

F2006

F2008

F2010

F2012

F2014

F2016

Source: RBI, Morgan Stanley Research. The above is based on banking system loans

Exhibit 29:India Loans: Corporate Loans as Percentage of Total

28% 28%

31%

32%

33% 33% 33%

32%

31%

29%

20%

24%

28%

32%

36%

40%

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

Source: RBI, Company Data, Morgan Stanley Research Estimates

If corporate demand will be relatively weak, then what will drive asset growth for the lenders? We expect loan growth in India to average around 13% over the next decade. F2018 and F2019 will likely remain slow for three reasons:

1. We think the economy will continue to pick up from relatively low levels, implying fairly muted demand for credit from the non-con-sumer segment.

2. The near-term impact of GST could cause some slowdown in the overall economy / loan growth for a few quarters.

3. SOE banks still make up ~55% of total loans (banks and NBFCs) in the system and, in our view, they cannot grow at more than low single digits for several years. We expect SOE banks to lose share at the rate of ~3-4% a year for the next few years. However, in the near term given that they make up ~55% of loans, their weakness will drag down system growth numbers.

But, what we expect over the next 10 years is a material shift in credit mix for India's lenders. We expect consumer loans to remain big drivers of growth and expect them to increase at a CAGR of ~17% to Rs. 112 trillion over this period. The other big driver, in our view, will be the MSME sector. Banks have been reducing exposure to this seg-ment over the past few years given weaker underwriting and growth in other businesses. But as data availability on these businesses improves, we expect a strong pickup. We expect MSME loans to grow at a CAGR of ~17% (compared with low double-digits in the past decade).

Historically, banks were unable to cater to vast segments of the economy fully. The bulk of the banking focus has historically been on the elite, the affluent and the middle class. The economics of expanding distribution and the relatively low value of transactions from the strata below the middle class has meant that access to banking services has been tougher for this part of the population. Like other parts of the financial system, the segment below the middle class has been left relatively unaddressed by banks.

We expect this to be the big driver of loan growth - in both the con-sumer and MSME segments. As the economy grows, more of these families will become middle class or affluent. Also, the digital initia-tives will help the financial system to get access to more data on underlying cash flows for these areas. This will allow lenders to underwrite businesses on the basis of cash flows.

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30

Exhibit 31:India's Banking Pyramid – The Banked, Underbanked, and Unbanked

Source: India Software Product Industry Round Table (iSPIRT)

Exhibit 32:Sources of Formal Credit for Businesses

25%

25%

15%

5%

12%

11%

6%

4%

Bank Limits / Credit / Overdraft facility

Loan against property

Loan against order

Loan against investments

Usage Share


AlphaWise - In our survey also, almost half of the respondents said that they don’t have access to formal credit. The biggest source of funds for these businesses is own funds or funds from family / friends. For the smaller businesses which can get formal credit, the biggest component is Loan Against Property (LAP), which is obviously a collateral backed loan. Another takeaway was that businesses with less share of cash in revenues get easier access to credit.

Exhibit 33:Who Has Access to Formal Credit

35%

56%

61%

26%

32%

37%

Share of cash - 76%+

Share of cash - 51-75%

Share of cash - 0-50%

Access to formal credit Share of formal credit


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Exhibit 34:Large Private Bank: Personal Loans for a Similar Profile Borrower but Working at Different Firms

11.0% 12.0%

14.0%

19.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Employee of a large ITcompany

Employee of a Mid SizedBank

Employee of aManufacturing Firm

Employee of a MSMECompany

CAT A CAT B CAT C CAT D

Source: Bank Bazaar, Morgan Stanley Research. Note: Interest rates are on an annualized basis

Why does data matter?

Historically, India has been a data-poor country from the perspective of credit underwriting. Until about a decade back, there was no credit bureau for consumer loans, which exacerbated the problem of NPLs in consumer lending, especially unsecured loans in 2008/2009 (along with unfettered growth without proper credit assessment). On corporate lending too, banks did not have proper data about mul-tiple borrowings by the same corporate across banks. This accentu-ated the problem with corporate NPLs that we have seen over the last five years.

However, as proper data has become available, underwriting deci-sions have become much better. An example would be consumer lending and CIBIL [Credit Information Bureau (India) Limited], the consumer credit score provider. This was set up in the mid 2000s and became increasingly important after the consumer credit cycle in 2008-2009. Now, it is the primary data provider for consumer loans in India (with over 2,400 members including banks, NBFCs, HFCs [housing finance companies] and so on, and maintaining credit records on over 550 million individuals and businesses). This has allowed CIBIL to generate proper credit scores on retail borrowers and information that banks can access.

This improvement in data allows banks to 1) lend properly to partic-ular areas - like unsecured - and 2) have differentiated pricing. For instance, if we look at data for a large private bank, there is significant divergence in interest rates offered on the basis of credit profile of a customer. Historically, this was tough to achieve especially for a bank with a weaker data base.

Exhibit 35:HDFC Bank: YoY Growth in Unsecured Personal Loans; Strong Pickup Since 2015 - Now Makes Up ~10% of Group Loans

0%

15%

30%

45%

60%

75%

Jun-06

Dec-06

Jun-07

Dec-07

Jun-08

Dec-08

Jun-09

Dec-09

Jun-10

Dec-10

Jun-11

Dec-11

Jun-12

Dec-12

Jun-13

Dec-13

Jun-14

Dec-14

Jun-15

Dec-15

Jun-16

Dec-16

Jun-17

Source: Company data, Morgan Stanley Research

The third advantage relates to cost of credit delivery. Both consumer and MSME loans require a significant number of people selling the products, collecting data and so on. However, as on-tap data availa-bility increases, lenders can start offering these loans electronically. This will bring down sourcing costs very sharply.

An example of a product piggybacking on this increased data availa-bility in consumer segment has been HDFC Bank's unsecured loans in ten seconds.

This essentially allows existing customers of HDFC Bank to be able to borrow unsecured personal loans in less than ten seconds. This enables the bank to increase volumes and reduce costs.

In our view, this will be the template for more loan products (con-sumer and MSME) over the next few years, across banks.

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32

Exhibit 36:Timeline of Steps Taken in Setting Up Digital Infrastructure and Policies That Will Help Drive MSME Loan Growth


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Surge in Data Lies Ahead - Consumer and MSME To Be the Big Growth Drivers

With a large part of the loan book, i.e. large corporate loans, unlikely to grow, lenders will likely search for new lending avenues. We believe that consumer and MSME loans will be the big growth drivers. We expect digitization to cause a significant increase in the number of data sources that banks can tap into to lend across the retail and MSME sectors.

For instance, the use of digital payments leaves a data trail for banks to assess cash flows of smaller enterprises / traders and so on. This will allow the banks to lend to them at lower rates given the better data history. This will enable banks to make quick lending decisions.

GSTN is likely to be a big source of data for the MSME sector - As mentioned earlier, GST is the common indirect tax code for the entire country. The implementation of GST requires significant investment in the creation of IT infrastructure. This is the responsi-bility of GST Network (GSTN). It is the technology backbone for GST and will administer registration, invoice uploading, tax return filing and the tax payment system. The businesses will have to upload invoices for individual transactions on the GSTN network. It will map these invoices and then the taxpayer can claim a tax credit. The GSTN expects to handle ~3 billion invoices every month.

As the new tax system picks up there will be a significant impact on tax collections for the government as compliance will improve. The other benefit for lenders would be access to good quality data on tax payers' cash flows. The data uploaded on GSTN could only be accessed by the tax payer and the respective tax officials.

However, if somebody wants to access a loan, they can allow lenders to have access to their tax filings in the GSTN. This will provide banks with significant cash flow information of the borrowers, thereby ena-bling them to price loans in a much better way with much more cer-tainty on likely credit performance.

We look at both consumer and retail loan markets and assess how big they can be in 10 years.

MSME will be a big driver of loan growth over the next decade for lenders

MSME as a sector has to do well for the economy to pickup. This seg-ment consisted of ~45 million enterprises as of March 2012 (source: Ministry of MSME) and provides employment to about 100 mn people (~10% of the country’s population). Also, as per the Fourth Census of the MSME sector (2006-07), the sector accounts for about 45% of the manufacturing output and around 40% of the total exports of the country. An RBI Working Group report estimates that the economic output growth in this segment has consistently out-paced overall GDP growth.

However, despite the fact that it is a fairly critical part of the economy, credit availability to the sector has been weak - Banks have tradition-ally shied away from this segment due to factors like a lack of proper accounting records and necessary documents, erratic cash flows, the higher cost of operations, the need for customization during disbur-sals/repayments and past experience of higher delinquencies and, hence, credit costs.

In fact, if we look at bank lending to micro and small industry compa-nies (where investment in plant and machinery is less than Rs 50 mn) it has been a fairly weak story for almost two decades. As a per-centage of bank lending, loans to these businesses contracted from 14% in F2000 to about ~7% in F2010 and then ~5% in F2017. If we look at loans given to medium-sized industry companies (investment <Rs 100 mn) as well, the loan proportion has slowed sharply from ~5% in F2008 to 1.5% in F2017.

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Exhibit 38:Bank Credit to Medium Industry Companies as Percentage of Total Non Food Credit and GDP

0%

1%

2%

3%

4%

5%

6%

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Bank Credit to Medium Industry as % of Total Non Food Credit Bank Credit to Medium Industry as % of GDP

* This does not include loans to MSME in the services sector. Source: RBI, Morgan Stanley Research

Exhibit 39:NBFC Credit to MSME as Percentage of Total Credit (Banks and NBFCs) to MSME Industry

11% 12%

13%

17%

20%

23% 23% 24%

26%

29%

0%

5%

10%

15%

20%

25%

30%

35%

F2008 F2009 F2010 F2011 F2012 F2013 F2014 F2015 F2016 F2017

Source: Company Data, RBI, Morgan Stanley Research Estimates

Exhibit 40:SCUF's Lending Yields Minus AAA 1 Year Bond Funding Costs

22.0%

15.9%

13.6%

14.4%

15.7%

17.7%

12.8%

11.1%

13.6% 12.9%

14.4%

13.3% 13.5%

8.0%

12.0%

16.0%

20.0%

24.0%

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Source: Company Data, Bloomberg, Morgan Stanley Research. We have used enterprise loan yields of SCUF which is largely MSME but also includes two-wheeler and gold loans

Exhibit 37:Bank Credit to Micro and Small Industry Companies* as Percentage of Total Non Food Credit

0%

3%

6%

9%

12%

15%

F2000

F2001

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Bank Credit to Micro & Small Industry as % of Total Non Food Credit

Bank Credit to Micro & Small Industry as % of GDP

* This does not include loans to MSME in the services sector. Source: RBI, Morgan Stanley Research

Banks have been fairly averse to lending to this sector. Losses in a down-cycle in the economy have been fairly elevated. Also, given the lack of data, most of these loans have been collateral backed lending and not cash flow based lending. And with foreclosure of collateral not very easy, banks have shied away from this lending.

Most of the lending to this space in recent years has been in the form of Loan Against Property (LAP), which requires the borrower to pledge their own property (for instance their residence) to borrow.

This field had been left open for NBFCs to tap into. While it is difficult to get proper NBFC data in terms of lending to this sector, we added up the 20 large HFCs' and NBFCs' exposure in these segments. This shows fairly sharp growth in lending towards these sectors, espe-cially over the last five years. Their loans have increased over 10x in the last ten years and have increased to ~29% of total credit exposure (banks and NBFCs) to this segment, from ~11% a decade back.

Why should it matter whether loans are coming from NBFCs or banks?

One reason is that NBFCs are wholesale funded with limited leverage capacity - implying that they can never be able to meet the full demand. Also, with banks absent, the interest rates charged by NBFCs can be very high. They are lower than in the informal sector - moneylenders - but still materially higher than those charged by banks. For instance, if we look at the average yield earned by Shriram City Union (SCUF) on its entire book - its spread over 1 year AAA paper is almost 14%. Also, since F2012 (when banks were affected by NPL issues) this spread has expanded by >200 bps.

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In our view this will change over the next 10 years as data availa-bility of these companies' cash flow becomes much broader and faster. This is a space where a number of fintech companies in India are operating - for instance, Capital Float & Lending Kart. Capital Float has various products, for instance supply chain finance loans for SMEs. The borrowers who qualify can apply online within ten min-utes and get credit within three days at reasonably low rates (consid-ering their financing cost).

Exhibit 41:Capital Float's Key Value Proposition to an SME Borrower (Per the Company)

Capital Float PSU Banks Private Banks Traditional NBFCs Money Lenders

FAST

Time to get funds <1 Week 4-6 Weeks 1-2 Weeks 1-2 Weeks <5 Days

Apply anywhere, any time! Yes No No No No

Hassle-free documentation & processing10 minute online

application3 months 1 week Doc intensive Unregulated

FRIENDLY

Zero Collateral Yes No Maybe Maybe Yes

Minimum years in business 1 year 3-5 years 3-5 years 3-5 years Varies

More inclusive for 'New-Age' business Yes No No No Maybe

AFFORDABLE

Loan Tenure 1-12 Months Not less than 1 year Not less than 1 year Not less than 1 year <1 year

Preclosure Penalties None 5% of loan 5% of loan 0-5% of loan Varies

Repayment options Flexible EMI only EMI only EMI only Weekly, Monthly

Advertised interest rate 18% - 24% 14% - 16% 14% - 22% 16% - 24% 24% - 120%

Processing fees up to 2% 2% 2% - 3% 2% - 3% 2%

Hidden charges None Varies 2% Insurance 2% Insurance None

Source: Company Data, Morgan Stanley Research

Over time, we expect banks to start using these models to lend in the space. This in turn will likely cause a significant pickup in lending to the MSME sector by banks. This will not be easy and its unlikely that we see a big growth pickup for two or three years as formal lenders have to do the following:

1. Build lending models based on the incoming data - Although data sources will increase significantly, banks will take time to build models to lend on the basis of these new data points.

2. Refine models - When CIBIL was launched, it took three to four years for banks to be sure of data points they needed before they could lend on the basis of these models. Similarly, the models here will need to be refined, especially after one credit cycle. For instance, the data from GSTN will enable banks to capture data on sales on a monthly basis. They will be able to identify any potential issues on an almost real-time basis.

Sharply lower lending rates in the MSME sector over the next five years - The real time flow of data is likely to reduce riskiness of these loans meaningfully. Also, the cost of underwriting will reduce fairly sharply given the dependence on technology. All this will feed into lower pricing. It is tough to take a call on how much spreads can come down in this product - but we could easily see average lending rates declining by 300-400bp over the next five years.

Right now lenders are not sure of how bad credit costs can be as busi-nesses slow down. Given the lack of data, lenders cannot identify problematic loans until they have almost become NPLs. This makes them price loans at a fairly elevated level - resulting in high ROEs even in a normalised credit cost scenario. However, as data availa-bility improves, lenders will be able to have more clarity on busi-nesses on a much more frequent basis. Also, the cost of delivery will come down. In this scenario, we would expect lenders to cut pricing significantly and still earn ~20% ROE.

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Exhibit 42:Indian Lenders Can Cut Spreads on MSME Loans by ~300bp as Data Quality Becomes Better and More Reliable

Bank NBFC Bank NBFC

Interest Income 16.5 20.0 13.8 17.0

Interest Expense 5.0 7.3 5.0 7.3

NII 11.5 12.7 8.8 9.7

Fee Income 0.0 0.0 0.0 0.0

Total Income 11.5 12.7 8.8 9.7

Operating Costs 5.6 4.8 4.9 3.8

Operating Profit 5.9 7.9 4.0 5.9

Loan Loss Provisions 1.9 2.5 1.1 1.5

Standard Provisions 0.06 0.07 0.06 0.07

Profit before Tax 3.9 5.3 2.8 4.3

Tax 1.3 1.8 1.0 1.5

Profit after Tax 2.5 3.5 1.8 2.8

ROA 2.5% 3.5% 1.8% 2.8%

Leverage 11.0x 7.1x 11.0x 7.1x

ROE 28.0% 24.8% 19.8% 20.2%

Loans 76 100 76 100

CRR 4 4

SLR 20 20

Interest Earning Assets 100 100 100 100

Equity 9.1 14.0 9.1 14.0

Applicable Risk Weights 100% 100% 100% 100%

RWAs 76 100 76 100

Tier I Ratio 12.0% 14.0% 12.0% 14.0%

Borrowings 90.9 86.0 90.9 86.0

Yield on Loans 20.0% 20.0% 16.5% 17.0%

Cost of Funds 5.5% 8.5% 5.5% 8.5%

Spread 14.5% 11.5% 11.0% 8.5%

Yield on SLR 6.5% 6.5%

NIM 11.5% 12.7% 8.8% 9.7%

Fees / Avg Loans (Assumption) 0.0% 0.0% 0.0% 0.0%

Operating Costs / Avg Assets (Assumption) 5.6% 4.8% 4.9% 3.8%

Standard Provisions / Loans (Assuming 20% loan

growth)0.1% 0.1% 0.1% 0.1%

Loan Loss Provisions / Avg Loans (Assumption) 2.5% 2.5% 1.5% 1.5%

Effective Tax Rate 34.6% 34.6% 34.6% 34.6%

Present With gains from higher customer dataMSME Dupont

Source: Morgan Stanley Research. Note: The above calculations are made on an asset book of 100 units of a given currency. For MSME loans by banks, risks weights can be lower at 75% subject to certain conditions, making these loans more profitable. However, for this exercise we have assumed a 100% risk weight.

A stronger economy and better access (quicker and at lower rates) to credit should help the MSME sector to do very well, in our view. We expect these loans (from banks and NBFCs) to grow at a CAGR of 17% over the next ten years and increase to ~22% of total loans. Some of this growth will also be taken up by the fintech based len-ders (we consider them to be a part of the NBFC book).

As we discuss in the economics section, better credit availability is a big driver to MSME profitability and investment. China saw this transformation, and if our thesis plays out, we will likely see this sector as a big driver of India's economic growth.

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Case Study: Role of SMEs in China's developmentSMEs have played a crucial role in driving economic development in China, primarily in two areas: first, job creation, in particular, during periods of significant structural transitions, and second, the promotion of industrial upgrading (see Cunningham [2011], SMEs as motor of growth: A review of China’s SMEs development in thirty years, 1978–2008).

As a major driver of employment growth, SMEs allowed for the swift absorption of agricultural labor during the country's initial industrialization process in the 1980s, with the blossoming of township and village enterprises. The OECD estimates that Chinese SMEs accounted for 60% of GDP in 2013, and 68% of China’s total exports in 2011. SMEs' operational flexibility and small-scale have meant that they can better cater to the diverse outsourcing demands from foreign firms.

Access to credit has been vital to the development of China’s SME sector. SME loans account for 57% of GDP (broadly similar to their economic size), and 39% of total loans in China as of 2Q17. According to the World Bank enterprise survey database, only 2.9% of firms in China report having difficulty in accessing credit, as compared with 26.2% globally and 15.1% in India. Moreover, the loan rejection rate in China is also materially lower, with only 6.6% of SME loan applications turned down, versus 11.5% globally and 12.9% in India in 2014.

Consumer Loans - Likely to grow at a CAGR of ~17% over the next 10 years

While loan growth has slowed across segments, consumer loans have performed very well. Since 2000, these loans have increased from ~4% of GDP to around 16% of GDP in F2017 - a CAGR of 23% over 17 years. There was a pause during the GFC when consumer credit to GDP declined as unsecured loans saw meaningful NPLs - but even then in absolute terms consumer loans grew at a CAGR of ~13% over that three-year period. If we look at the credit multiplier in India, consumer has been reasonably strong at around 1.5x for the last few years.

Exhibit 43:Consumer Loans to GDP

3.8%

13.5%

15.9%

0%

3%

6%

9%

12%

15%

18%

F2000

F2001

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Source: RBI, NHB (National Housing Board), Company Data, Morgan Stanley Research Estimates

Exhibit 44:Consumer Credit Multiplier and Total Credit Multiplier

4.4

1.9

2.3

0.8

0.0

1.0

2.0

3.0

4.0

5.0

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Consumer Credit Multiplier , 3YMA Total Credit Multiplier

Source: RBI, NHB, Company Data, Morgan Stanley Research Estimates

We expect consumer lending to grow at a CAGR of ~17% over this period and to increase to around 25% of GDP. This would imply retail loans will increase by around 5x to US$ 1.5trillion.

Various factors are driving this move.

1. Economic growth and likely sharp increase in per capita GDP - We expect India's GDP in F2027 to be ~US$6.0 trillion and per capita GDP to be ~US$4,094 (~ INR 330,000) in nominal terms. This would imply an INR CAGR at ~11%, compared to ~12% over the last 10 years. On a PPP adjusted basis, we expect per capita GDP to increase to ~US$16,800 from the current ~US$7,150. If India matches other countries' consumer loan penetration versus PPP GDP, we should see consumer lending to GDP reach around 30% by F2027.

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Exhibit 45:India Per Capita GDP Should Rise 3x in the Next Ten Years

0

50000

100000

150000

200000

250000

300000

350000

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F2018E

F2019E

F2020E

F2021E

F2022E

F2023E

F2024E

F2025E

F2026E

F2027E

Nominal GDP Per Capita (Rs)

Source: RBI, World Bank, Morgan Stanley Research (e) estimates

Exhibit 46:Consumer Credit to GDP Versus per Capita Income

India

China

Indonesia

Korea

Malaysia

Philippines

Thailand

0%

20%

40%

60%

80%

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000

C2

01

6/F

2017

Co

nsu

mer

Cre

dit

/ G

DP

C2016/F2017 Per Capita Income (PPP, USD)

India by C2026e/F2027e

Source: IMF, Central Bank Data, RBI, NHB, Company Data, Morgan Stanley Research (e) estimates

2. Government push for mortgages - The government is focussed on increasing the stock of affordable housing in India as this can have a significant trickle-down effect on the economy. In 2017, the govern-ment has announced significant incentives to boost both supply and demand in housing. This coupled with the increase in income levels will likely drive mortgage growth.

We are building in a 16% CAGR for banks and HFCs over the next ten years and are forecasting outstanding home loans to grow from ~US$220bn as of FY17 to ~US$905bn as of FY27. This should result in mortgages to GDP moving from ~10% to ~15% during the period.

Exhibit 47:Multipronged Push by the Government to Improve Housing

RERA to bring greater transparency in real estate transactions and

empower buyers

Restrictions on end use of homebuyer funds, penalties for material deviation from the

building plan and penal interest / imprisonment for delays in construction, should all result

in better buyer sentiment and protection.

Better profit margins on affordable housing projects

100% Profit-linked income tax exemption for promoters/developers of affordable housing

scheme on projects getting approved from June, 2016 to March, 2019 and completed in 3

years from the date of approval. In addition, real estate developers will also get tax relief

on unsold stock as tax liability will arise on capital gains when the project is completed.

Infrastructure status to affordable housing will provide cheaper sources of finance to

developers and also open up additional avenues for developers to raise funds. The carpet

area cap for affordable housing has also been increased to 60 sq. mt. instead of 30 sq. mt.

earlier.

Priority lending status for affordable housing

The government has announced various schemes to boost supply and demand in affordable

housing. Prominent scheme on the demand side is the credit linked subsidy scheme which

involves an upfront subsidy for first time home buyers up to Rs0.26mn across Economically

weaker sections (EWS), Low income groups (LIG), and Miiddle income groups (MIG1 &

MIG2).

Rs290.4bn budgeted overall for FY2017-18; Rs60.4bn for urban housing

and Rs230bn for rural housing Budgetary support

to Pradhan Mantri

Awas Yojana -

Housing for All by

2022

Infrastructure Status

to Affordable

Housing

RERA

Tax Sops for

Developers for

Affordable Housing

Projects


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Exhibit 48:Mortgage Penetration in India is Quite Low Compared with that in Many Developed / Developing Countries

90%

68% 64%

47% 47% 42% 41%

32% 27% 26%

13% 10%

0%

20%

40%

60%

80%

100%

Denm

ark

UK

US

A

Sin

ga

pore

Hong K

on

g

Germ

any

Jap

an

Mala

ysia

So

uth

Kore

a

Chin

a

Thaila

nd

India

Source: Countries' central banks, RBI, NHB, CEIC, IMF, Morgan Stanley Research

Exhibit 49:Mortgage Penetration (i.e. Mortgages / GDP) Relative to Per Capita GDP

India

China

Indonesia

Korea

Malaysia

Philippines

Thailand

0%

10%

20%

30%

40%

50%

0 10000 20000 30000 40000

Mo

rtg

ag

e P

en

etr

ati

on

, 2016

Per Capita GDP (PPP, USD), 2016

Source: Countries' central banks, RBI, NHB, CEIC, IMF, Morgan Stanley Research

3. The other big driver of consumer loans will be loans that are higher up in the risk spectrum - The area where banks have been more aggressive on using data mining to lend has been the unsecured consumer loan space. Given the data banks have (CIBIL, transaction history and so on), they have started offering the following:

a) Quicker processing: Now lenders can offer these loans with a much quicker turnaround. For instance, HDFC Bank's loan in ten seconds essentially allows it to credit a customer's account with the loan amount within ten seconds of application.

b) Significant operating leverage: Since most of the processes - appli-cation, underwriting and actual credit delivery - happen online, the cost of originating these loans is fairly low.

This has caused banks to cut unsecured retail lending rates quite sig-nificantly over the last few years. For instance, for a good borrower unsecured personal loans are being offered at ~11-12%, compared with 16-17% which was the norm three to four years ago.

We are also seeing households using more leverage to buy discre-tionary items. For instance, the proportion of buyers using leverage to buy cars has increased from 72% in F13 to 80% in F17, and we expect this to continue to increase. Other segments like two-wheelers will also see a reasonably large pick-up in financing, in our view. This again is driven by banks' willingness to lend at a price that borrowers can afford.

Exhibit 50:Proportion of Maruti Customers Using Finance to Purchase a Vehicle

Source: Maruti Suzuki

Exhibit 51:Proportion of Buyers Using Finance to Buy Two-Wheelers; Likely To Increase Sharply

37%

23% 23%

24%

25%

26% 26% 26% 27%

22%

24%

26%

28%

30%

32%

34%

36%

38%

F2

00

9

F2

01

0

F2

01

1

F2

01

2

F2

01

3

F2

01

4

F2

01

5

F2

01

6

F2

01

7

2W Finance Penetration (%)

Source: Crisil, Morgan Stanley Research

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Exhibit 52:Consumer Loan Mix Across Key Loan Products and Forecasts

F2012 F2017 CAGR F2027e CAGR F2012 F2017 F2027e

Housing Loans 6,193 14,754 19% 65,343 16% 56.8% 60.8% 58.8%

Banks 3,971 8,601 17% 29,320 13% 36.4% 35.4% 26.4%

HFCs 2,222 6,153 23% 36,023 19% 20.4% 25.4% 32.4%

Non Housing Loans 4,701 9,519 15% 45,694 17% 43.2% 39.2% 41.2%

Banks 3,858 7,599 15% 32,142 16% 35.4% 31.3% 28.9%

NBFCs 843 1,920 18% 13,552 22% 7.7% 7.9% 12.2%

Non Housing Loans (Product wise)

Auto Loans (Banks only) 891 1,705 14% 7,212 16% 8.2% 7.0% 6.5%

Credit Cards (Banks only) 204 521 21% 2,205 16% 1.9% 2.1% 2.0%

Other Retail Loans 3,606 7,292 15% 36,277 17% 33.1% 30.0% 32.7%

Banks 2,763 5,373 14% 22,725 16% 25.4% 22.1% 20.5%

NBFCs 843 1,920 18% 13,552 22% 7.7% 7.9% 12.2%

Total 10,893 24,273 17% 111,037 16% 100.0% 100.0% 100.0%

As % of GDP 12.5% 15.9% NA 25.1% NA

Rs Billion Mix

Source: Company Data, RBI, NHB, CSO, CEIC, Morgan Stanley Research (e) estimates. Note: Numbers for NBFCs and HFCs are based on our assumptions

Exhibit 53:Annual New Loan Originations in Consumer Sector Likely To Be ~9% of GDP by F2027 and Grow 4.5x to Rs 40 trillion by F2027

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

2012 2017 2027e

Retail Disbursements (Rs Bn)

18% CAGR

16% CAGR

Source: RBI, NHB, Company Data, Morgan Stanley Research (e) estimates

Are these very aggressive assumptions? In our view, these are not aggressive as even after building in this growth, we are likely to end up with consumer credit to GDP at ~25% by F2027 compared with ~16% now. As mentioned above, given that lenders are likely to focus on consumer / MSME loans for growth and also continued improve-ment in technology / data collection, this should be achievable.

Another way to look at this would be what would this imply in terms of new loan originations every year. Given that housing will still be around 60% of total retail loans and it runs off at ~14% every year, the annual originations needed by F2027 will be around Rs40 trillion compared to around Rs9 trillion in F2017 (16% CAGR). Given nominal GDP growth at ~11% and the focus on consumer loans, this should be achievable in our view.

We can also compare the experience of the US when its GDP rose from US$2.1 trillion in 1977 to US$6.8 trillion in 1993. India will likely be on a faster path than the US was in that period given the significant difference in GDP per capita. During this period, retail credit penetra-tion in US went from 42% of GDP to 59%. Again, given the difference in GDP per capita between the US then and India now, this is not strictly comparable. But it does show that penetration can increase meaningfully as populations get richer.

Exhibit 54:In the US, Consumer Credit Penetration Surged When Nominal GDP Went From US$2.1 Trillion to US$6.8 Trillion (1977-1993)

0%

20%

40%

60%

80%

100%

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

US Nominal GDP went from ~USD 2.1 trillion in 1977 to USD 6.8 trillion in 1993. During this time

retail credit increased from 42% to 59% of

GDP

Source: Central Bank data, World Bank, Morgan Stanley Research

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Key Takeaways1. Digitization should provide an additional boost to an already compelling structural growth story. We estimate that digitization will provide a boost of 50-75bps to GDP growth and forecast that GDP growth will average 7.1% between F2018 and F2027, with India growing to a US$6.0 trillion economy and achieving upper-middle income status by F2027.

2. As digitization takes hold, SMEs and consumers will have better access to credit, which should help boost domestic demand. Specifically, SMEs will be able to lift their capital spending, thereby raising sustainable growth, while households will be able to increase their discretionary spending.

3. Digitization will help improve public finances via stronger tax compliance and enhanced efficiency in welfare spending. All else equal, digitization should help improve the country's fiscal deficit, and public debt to GDP should decrease over the next ten years.

Implication 2: Digitization = Economic Growth Booster

Exhibit 55:Key Forecasts

Bull Base Bear

Real GDP, YoY (avg) 7.1% 8.4% 7.1% 5.9%

Nominal GDP, US$ bn (eop) 2,279 7,026 6,040 5,180

Nominal GDP, YoY (avg) 11.3% 13.0% 11.2% 9.5%

GNI Per Capita, US$ (eop) 1,702 4,809 4,135 3,546

Investment as % of GDP, (avg) 29.8% 34.3%

FDI, US$ bn (eop) 60 120

F2018-F2027EF2017

Source: Morgan Stanley Research, Note: GDP growth rate in INR terms.

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42

India’s Structural Growth Story Remains Very Compelling

We have, on a number of occasions (e.g., see The Next India - From a Cyclical Downturn to a Structural Upturn), presented our view that India is likely to continue to enjoy structurally strong rates of growth. Indeed, since the mid-1980s, trend-line growth rates in India have been rising steadily. GDP growth has averaged 7.1% in 2000-17, 5.8% in the 1990s, and 5.7% in the 1980s. Over the coming decade, India is likely to remain one of the fastest-growing large-sized economies in the world.

The structural growth story is based on a combination of three key drivers: demographics, globalization, and reforms. First, favorable demographic trends provide surplus labour that can be mobilized. Second, globalisation provides exports as an additional source of aggregate demand and financing that can be used to boost growth. Third, economic reforms spur the corporate sector to invest, which in turn leads to utilization of surplus labour and unleashes faster pro-ductivity growth.

In fact, it is this combination – favorable demographics, riding the wave of globalization, and implementing policy reforms that boost investment – that has been a key factor in sustaining growth across countries in Asia. Throughout the region, a virtuous cycle of falling age dependencies (i.e., the ratio of non-working age population to working age population), along with an improving saving (and invest-ment) to GDP ratio, has led to long phases of strong GDP growth. Japan was the first to experience a positive demographic wave in the early 1950s, followed by the collective experience of Hong Kong, Korea, Singapore, Taiwan from the 1960s and China from 1974 onwards. According to UN estimates, India will continue to undergo this positive demographic trend of an improving age dependency until 2040, and, thus, we believe it is well positioned to experience a phase of rapid growth.

Exhibit 56:India's Demographic Profile Remains Favorable

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014E

2016E

2018E

2020E

2022E

2024E

2026E

2028E

2030E

2032E

2034E

2036E

2038E

2040E

2042E

2044E

India World ex India

US China

Age Dependency Ratio (%)

Demographics Deteriorating

Source: United Nations Population Database, Haver, Morgan Stanley Research. E=UN estimates

Exhibit 57:India Likely to Contribute 27% of the Addition to the World's Working Age Population in the Next Ten Years

-27 (-6%)

-24 (-5%)

-5 (-1%)

7 (2%)

3 (1%)

19 (4%)

43 (9%)

110 (24%)

122 (27%)

-80 -30 20 70 120 170

Europe

China

Japan

US

Rest of AXJ^

Indonesia

LATAM

ROW

India

Africa*

World

Additions to Working Age Population, People mn (2017-2026E)

Working Age Population as of

2016

4872

676

874

428

199

214

76

175

735

457 (100%)

208 (46%)

Figures in () indicate share in world working age population addition 490

(100%)

1005

Source: United Nations Population Database, World Bank, Haver, Morgan Stanley Research. E=UN esti-mates

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Exhibit 59:… and Investment Rates Remain Weak Relative to Those of Other Asian Economies

10%

15%

20%

25%

30%

35%

40%

45%

50%

19

80

19

81

19

82

19

83

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84

19

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87

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89

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09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

India

Asian tigers

China

Japan

Investment as % of GDP

Note: Asian tigers are Hong Kong, Korea, Singapore and Taiwan. Source: IMF, CEIC, Morgan Stanley Research.

Investment - The Key to Unlocking the Structural Story

We note that favorable demographics is a necessary but not suffi-cient condition for a phase of rapid growth. While a cycle of falling age dependencies typically leads to a virtuous cycle of improving saving to GDP rates, the key to unlocking a phase of strong GDP growth lies in investment. A rise in investment-to-GDP ratio is needed to drive a virtuous cycle of higher investment – job growth – higher income – and higher saving.

Structurally, though, India’s investment-to-GDP ratio remains below that which other Asian economies experienced during their rapid development phases ( Exhibit 59 ). Indeed, despite India's favourable demographic trends, the only instance in which there had been a strong investment cycle was during the 2003-07 period, when investment-to-GDP picked up to a peak of 38.1% in 2007, as com-pared with an average rate of 22.6% between 1980 to 2002. Unsur-prisingly, this was also the period during which India's GDP growth rate had been the strongest in the country's history, as the contribu-tion of investment growth accelerated significantly. However, out-side of this period, India’s investment-to-GDP ratios have remained lackluster, averaging just 27.9% of GDP, as compared to an average of between 30-35% for most other Asian economies, when they were experiencing their favourable demographic waves.

One of the key drivers affecting India's investment trend is the lack of saving within the economy. India’s savings trend has been consist-ently below that of the other Asian economies, despite the country's more favourable demographic profile. Indeed, India’s 2017 savings ratio of 27.2% is almost identical to that of Japan, despite the fact that India’s median age is 27, as compared with 47 in Japan, and that the age dependency ratio in India is at 51.0%, as compared with 66.5% in Japan.

While India's private capex cycle has been weak in recent years, con-strained by a challenging macro environment, we expect it to pick up in 2018, driven by recovery in end-demand, improvement in corpo-rate balance sheets, and the positive momentum provided by strong public capex and FDI flows. Over the medium term, we expect the share of investment to GDP to rise, supported, as noted, by a cycle of favourable demographics and rising income and savings rates. Ulti-mately, in our view, it is the strength of the capex cycle that will deter-mine how strong and sustained the growth cycle will be. Over the next decade, we expect investment to GDP ratios to average 34.3%, contributing 3% points to real GDP growth.

Exhibit 58:India's Saving …

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IndiaAsian tigersChinaJapanIndonesia

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Note: Asian tigers are Hong Kong, Korea, Singapore and Taiwan. Source: IMF, CEIC, Morgan Stanley Research.

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Digitization - Three Channels of Impact

It is against this backdrop of structural forces that the recent devel-opments in digitization should be evaluated. We see three key chan-nels of impact as digitization takes hold: improved access to credit for SMEs (boosting investment), stronger lending to households (boosting discretionary consumption), and strengthening tax com-pliance and better efficiency in welfare spending (fostering improve-ment in public finances). The key impact will come via increasing the availability of financial saving – and thereby boost the investment cycle. Digitization could provide greater economic benefits than the 50-75bps boost to growth that we have accounted for. For instance, intangible benefits (e.g., reduced costs and improved efficiency in doing business) would yield a key productivity boost. Digitization could also have the potential to disrupt and create new growth chan-nels, and could thereby provide additional growth engines.

Exhibit 60:Real GDP Growth to Average 7.1% YoY; We estimate a US$6 Trillion Economy by 2027

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1. Corporate sector: Improved access to credit, especially for MSMEs

On the corporate side, the key impact will be via increased access to credit, particularly for the underserved MSME sector. This will princi-pally help boost investment, leading to stronger and sustained growth.

Traditionally, the lack of formalisation and access to credit has been the key impediment to growth in the MSME sector. The lack of for-malisation (i.e. lack of legal status) limits access to new markets such as the public sector and MNCs and deters the formation of business linkages with registered companies. Informal MSMEs are less likely to invest in human or physical capital, given the limited size of their end-markets. At the macro level, this implies sluggish productivity growth and lower aggregate growth rates.

The other key constraint is the lack of available credit. With better access to credit, the MSME sector can create more jobs as they can start new businesses more easily, make larger investments, and indi-rectly create employment via supply and distribution chains as firms expand operations after gaining access to finance.

Exhibit 61:India Fares Relatively Poorly with Respect to Other EMs on Credit Access to MSMEs

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Thailand Indonesia Philippines India Mexico Malaysia Russia Argentina Brazil Poland

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Note: Latest available data as of 2016 Source: IFC, Morgan Stanley Research

Exhibit 62:Lack of Credit Access to MSMEs Remains a Barrier

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Note: Latest available data as of 2016 Source: IFC, Morgan Stanley Research

Exhibit 63:Credit Access for MSMEs Remains Weak for India

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Source: IFC, Morgan Stanley Research

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Exhibit 64:India Only Fares Better than a Few EMs with Respect to MSME Credit Value Gap

3.0% 3.0% 3.8% 3.9%

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Indonesia China Philippines Russia South Africa Mexico India Malaysia Poland Turkey Republic ofKorea

Argentina Colombia

Total MSME credit value gap, % of GDP

Note: Credit value gap: Degree of access to credit and use of deposit accounts. Source: IFC, Morgan Stanley Research

What has changed and will change for the MSME sector?

In the case of India, the implementation of the GST is addressing both the issues of formalization of SME sector and access of credit, which will significantly improve SMEs’ growth prospects. The GST has already led to the registration of 5.9 million taxpaying entities in the GST network, with an additional 1.4 million yet to complete their pro-cedural formalities (in total, approximately 1.9 million more entities than before GST), as of 29 August 2017. While the push for registra-tion in the MSME segment might have been predominantly driven by the need to facilitate the claiming of input tax credits, it has the posi-tive spillover benefits of providing a kickstart to the formalisation process.

We expect digitization to improve flow-based lending, with the SME sector being the key beneficiary in the corporate space. We expect overall credit growth (from banks and NBFCs) to the MSME sector to grow at a CAGR of 17% over the next ten years. SMEs will then be better able to achieve scale economies and lift their investment. We expect this to provide a boost to capital deepening, and to provide a boost to growth of about 30-40bps over the next decade.

2) Households: Better consumption smoothing, stronger con-sumer durable spending

Households, too, will benefit from improved credit access. Credit penetration in the household segment in India remains low relative to the country's per capita incomes, limiting the ability of households to smooth consumption over their lifecycle.

In recent years, shifts have begun to occur in the consumer credit space. India's household debt to GDP ratio has risen from 11.8% in 2010 to 16.2% in 2016. This has also led to an increase in the private consumption to GDP ratio, from 56.0% in F2012 to 58.8% in F2017.

The major boost to consumer activity will likely occur in the discre-tionary consumption space. Based on the CPI basket weights, food accounts for 46.8% of annual household expenditure, which is amongst the highest such levels globally ( Exhibit 65 ). While this is likely a reflection of India's current level of economic development, as per capita incomes rise, the share of expenditure will likely shift towards non-food consumption. A cross-country analysis of a number of DM and EM economies as of 2016-17 ( Exhibit 66 ) sug-gests that food tends to account for an average of 21.6% of the CPI basket, with the shares ranging from a low of 9.7% in the UK to a high of 35.5% in Russia.

Exhibit 65:Households in India Spend Almost 50% of Their Expenditure on Food

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Source: CEIC, Haver, IMF, Morgan Stanley Research. GDP per capita and CPI weights as of 2016 for Korea, 2017 for all other countries

Exhibit 66:Rising per Capita Incomes Indicate Shifting Consumption Patterns away from Food

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Japan: 1970-2017, Korea: 1994-2016, Germany: 1995-2017

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Thus, as the experience of other countries suggests, the share of expenditure towards non-food items tends to rise as per capita incomes rise. Indeed, India's own experience has begun to reflect this transition, too. As per Euromonitor data, the share of consumer expenditure on food and non-alcoholic beverages has been system-atically declining since the late 1990s, and we expect this transition to gather pace as per capita incomes rise.

b) Improved efficiency in public spending

On the expenditure side, digitization efforts also enable the govern-ment to introduce a more targeted approach towards disbursing wel-fare spending to the country's citizens. A more targeted approach would help in preserving financial resources – in contrast to the pre-vious approach of engaging in transfers to households, which was prone to leakages.

The government has already implemented a direct benefit transfer (DBT) scheme – a social welfare scheme under which the subsidy benefits are directly transferred to the beneficiary’s account – rather than issuing checks / cash payments / rebates. Presently, 290 schemes in 50 ministries are under DBT, and the government plans to scale that up to 533 central payout schemes in 64 industries by March 31, 2018 (see Livemint, September 7, 2017). Cumulatively, the total direct benefit transfer so far has been approximately INR2025bn, and savings have amounted to INR496.5bn over the pre-vious method.

3) Government: Increased tax compliance and revenues, more effi-cient public spending

The third channel in which digitization helps from a macro perspec-tive is via its impact on government finances. Two positive effects should emerge: 1) boost to tax revenues and 2) improved efficiency in spending.

a) Improved tax compliance helps control fiscal deficit and reduce public debt

India’s tax revenue to GDP ratio is on the low side as compared with levels in other EMs, and this has been a key obstacle in achieving a fiscal deficit more in line with that of EMs. The recent implementa-tion of the GST (while not necessarily a direct beneficiary of digitiza-tion – though aided by it, and it should drive further digitization), will help increase tax compliance amongst corporates, leading to a boost in tax revenues, even while the tax rates are, in and of themselves, revenue neutral.

Over time, improvement in tax revenues should drive improvement in fiscal deficits and public debt to GDP trends. Indeed, we estimate that if the primary fiscal deficit stays at 1.2% of GDP (as compared with an average of 2.1% over the past five years, and at 1.6% in F2017RE), public debt to GDP should decline to below 60% by F2027.

Exhibit 67:India's Tax Revenues to GDP Levels Appear Low in an EM Context

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Tax revenue as % of GDP, 2016

Source: CEIC, Haver, Morgan Stanley Research

Exhibit 68:Public Debt to GDP to Decline: Debt to GDP Ratios in F2027 Based on Various Primary Deficit and Nominal GDP Assumptions

Primary Deficit (% of GDP) 11 12 13 14 15

1.0 57 53 48 44 41

1.2 59 54 50 46 42

1.4 61 56 52 47 44

1.6 63 58 53 49 45

1.8 65 60 55 51 47

2.0 67 62 57 52 49

Nominal GDP Growth (YoY %)

Note: Current primary deficit as of F2017 is 0.3% and public debt to GDP is at 67.6% in F2017. Source: Morgan Stanley Research estimates

http://www.livemint.com/Politics/YhHFO3gKV2KzRMODioDEwL/Govt-starts-direct-transfer-of-subsidy-to-check-diversion-s.html

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Global Implications

It took nearly 60 years from independence for India’s GDP to reach US$1 trillion (in F2007). However, the confluence of positive factors (demographics, reforms and globalization) helped the country reach the next trillion milestone within nine years (by F2015). With sus-tained strong rates of growth in the coming decade and the added boost from digitization, India's economy, we believe, could reach US$6 trillion by F2027. By our estimates, this would make India the third-largest economy by then, up from seventh currently.

On a per capita income basis, the changes would be even more pro-found. We estimate that per capita annual incomes will likely reach US$4,135 by F2027, lifting India into an upper-middle income status. To put this in perspective, per capita incomes in India by 2027 would be similar to those of China in 2010. Such a rise of a large-sized, upper-middle income society is likely to have profound implications on how India interacts with the rest of the global economy and becomes an even larger market for many of the world’s companies.

From a macro perspective, India’s markets have been more open at this stage of development. As it is, India is attracting FDI inflows amounting to 2.7% of its GDP on a 12-month trailing basis in July 2017. India accounts for 2.5% of total global FDI flows (as of 2016) and is the 11th largest recipient of global FDI inflows. This is up from 0.8% of global FDI flows in 2005 when India was the 32nd largest recipient of global FDI inflows. FDI flows have been concentrated thus far in the telecom, insurance, wholesale and retail trade & IT sectors.

In particular, foreign investment for the financial and technology sec-tors (which traditionally are more protected) are more liberal as com-pared with China at a comparable development stage (per capita incomes), and financial liberalization efforts have also gathered apace relative to India’s stage in economic development. This open-ness has meant that companies will be in a better relative position to capitalize on the growth opportunities that India is offering.

Against this backdrop, we project that India will receive gross FDI inflows amounting to US$120bn by F2027, almost double the cur-rent 12-month trailing run rate of US$64bn. As a marketplace, India, in our view, offers significant new opportunities in the discretionary consumption and infrastructure spaces. As highlighted previously, with the rise in per capita incomes, discretionary spending growth in India is on track to accelerate and take a larger wallet share in con-sumer expenditures. Similarly, in investment, the needs for infra-structure buildup will also have to be met. Aside from the funding requirements, capital goods companies can also be a significant sup-plier to meet India’s infrastructure needs.

As a case in point, the recently announced Mumbai-Ahmedabad bullet train project (costing Rs108bn [US$1.7bn], and slated for com-pletion by 2022), which is being 80% financed by a loan from the Japan International Cooperation Agency, will likely be beneficial for Japanese companies that can leverage India as an export market and transfer of Japan's technology. In the high-speed rail space, six other projects are in the pipeline, highlighting the infrastructure develop-ment opportunities in India.

Exhibit 69:India to Achieve Upper Middle Income Status within the Next Ten Years

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Implication 3: A Massive eCommerce Opportunity

Key Takeaways1. The eCommerce market should receive a major boost, with rising internet penetration, improving data speeds and a fast developing handset ecosystem, an ever-growing assortment of goods and services online and a palpable need for convenience. The government’s drive to digitize payments and the introduction of GSTN are significant enablers for the growth of the online economy. These coupled with the regular flow of growth capital from both financial institutions and strategic players will be key to the rapid growth of the eCommerce industry.

2. We expect eCommerce sales to grow at a 30% CAGR through F2027 (C2026) and to touch ~US$200bn of GMV, translating into a 12% online penetration within retail sales, versus ~2% in F2017 (C2016).

3. Between 2014 and August 2017, the eCommerce sector received funding of US$10.3bn. The importance of funding was demonstrated in 2016 when it fell 66% yoy and led to a slowdown in growth in Gross Merchandise Value (GMV). The level of funding has improved in 2017 YTD (reaching US$4.3 bn by the end of August), but a regular inflow of large amounts of money will be critical for growth of the segment, in our view.

Exhibit 70:Scenario Analysis for India's eCommerce Sales Suggests that the Market Can Compound Significantly from Current Levels

BASE BULL BEAR

Total Internet users (million) 432 915 1,010 841

Internet Penetration (%) 33% 62% 68% 57%

Total Online shoppers (million) 60 475 630 378

Online shoppers as % of total internet users 14% 52% 62% 45%

Total online retail market size including food delivery (US$ bn) 15 200 251 105

Total online retail as % of total retail (%) 2.2% 12.1% 14.0% 7.7%

Scenarios for India online retail market F2027e

F2017

Source: IAMAI, Morgan Stanley Research (e) Estimates. Please note that F2027 represents calendar year C2026 ending December 2026 and so on for the previous years; For F2017 online retail market size is based on Morgan Stanley Research estimates and is an approximate figure .

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We believe the eCommerce industry in India will grow extremely fast in the next ten years for the following reasons:

1. Rising internet penetration - India is adding over two new internet users every second, driven by falling prices of smartphones, the higher adoption of mobile devices, and the availability of telecom infrastructure that supports 3G/4G speeds. 81% of all smartphones shipped to India in 2016 were 4G LTE enabled, and the price of the cheapest 4G handset touched Rs3,000 (a 36% decline in 15 months). Internet penetration was 33% in F2017 (C2016), with 432mn internet users, and we expect penetration to go over 60% by F2027 (C2026), with about 915mn internet users. India has a large population of mil-lennials who will be exposed to technology and the internet at an early age and could drive rapid online adoption.

2. Availability of higher assortment as more merchants/prod-ucts come online - We believe a healthy marketplace is one where there are several sellers on one side and several buyers on the other. Currently, the number of merchants selling on online platforms such as Flipkart is around 150,000, however, this number could signifi-cantly increase. Amazon India has 160mn products listed on its plat-form, versus 400mn+ for Amazon in the US. We can see two key developments taking place that can increase the number of sellers/products online: a) Availability of credit to merchants - large eCom-merce companies such as Flipkart and Amazon have implemented seller lending programs for providing working capital loans to sellers on their platform. With these loans, not only will the sellers be in a position to bring more inventory online but also this development will help bring new sellers on the platforms. In addition to these pro-grams, various P2P marketplace lending platforms such as Capital-float, Indifi and Lendingkart are providing loans to merchants that were historically unable to take loans from banks; and b) GST - increased availability of credit due to GST will be a key enabler of eCommerce.

3. Faster growth of online shoppers and per capita spends - India had only ~60mn online shoppers in F2017 (C2016), which was ~14% of the total internet population, versus 64% in China. Our analysis of some global eCommerce companies highlights that two-thirds of the growth in their eCommerce sales happened due to new users coming online and shopping, while the balance was driven by existing online shoppers buying more frequently and/or driving up order values. As per an AlphaWise survey conducted in 2014, we saw that internet

Exhibit 71:AlphaWise Survey (2015) Showed that Individuals with Over Five Years of Use on the Internet Were More Likely to Transact Online

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users with less than two years of activity on the internet were less susceptible to transacting and primarily indulged in emails, mes-saging and search. However, users with over five years of experience on the internet were more likely to transact online. A large chunk of the internet base in India has emerged only in the last few years and hence has possibly not matured yet to the stage of transacting online. However, in 2019 and beyond, more than half of the internet population will have matured over five years and that could possibly be when online shopping sees a massive inflection. Further, India's millennial population (including past millennials of 2016) by 2020 will be 36% of the total population but will be a much larger force to reckon with in terms of the internet and online shopper population; this could be a key driver of online activity. As an example, as per our survey of millennials in India in 2016 (The Next India: Technology: The Millennials Series: The Disruptive Wave in the World's Seventh Largest Economy (Feb 19, 2017)), the online shopper penetration is already high at close to 40% (versus 14% for the overall population in India in 2016) across some key segments; we expect online shopper penetration in India to cross 50% by F2027 (C2026). With close to 475mn online shoppers in F2027 and an online spend of ~10% of the per capita income, we believe the eCommerce market can grow rap-idly from the current base. Furthermore, with the help of data, we expect banks, NBFCs and fintech companies to provide short-term financing online, which could significantly boost consumerism in the country.

https://ny.matrix.ms.com/eqr/article/webapp/0f6bc734-e6a1-11e6-b3fe-837ed4512f41?ch=rpint&sch=sr



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Exhibit 72:India's Online Shopper Penetration in F2021 Will Be Similar to What Brazil and Russia Have Today, and by F2027 it Will Be 50%+

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Exhibit 73:Convenience Outstrips Price Attraction Once Users Have Over Five Years of History on the Internet; by C2019-20, About 50% of the Indian Internet Population Will Have Been on the Internet for Over Five Years

Source: AlphaWise, IAMAI, Morgan Stanley Research; E = Morgan Stanley Research estimates

Exhibit 74:Cash on Delivery Is a Prominent Payment Method for eCommerce Sales; However, New and Easy Payment Methods Along with Growing Customer Confidence in Online Retailers Could Cause Payments to Become More Digital

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4. Evolving payment methods thus reducing dependence on cash - Cash on delivery is the main payment method, accounting for about 55-60% of total eCommerce sales. One of the key reasons for the high dependence on cash is the trust deficit that exists between cus-tomers and online merchants. However, with the passage of time, we believe cash could lose market share to credit/debit cards and pay-ment wallets. We have already seen a significant surge in the usage of digital wallets from about two or three years back when their usage was small. This should improve the online shopping experience by making payments more seamless and therefore easier.

5. GST could boost logistics and warehousing capabilities - We see GST enabling the free flow of goods across the country as hur-dles at state borders (in the form of tax payments and other adminis-trative measures) are done away with. Not only will surface transportation become a possibility, but the change may also cause eCommerce and logistic companies to relook at their warehousing strategies and possibly invest closer to demand centres, thus improving delivery timelines and customer experiences.

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eCommerce Opportunity Could Be US$200bn in F2027

eCommerce sales in F2017 (C2016) touched ~US$15bn; however, this marked a significant slowdown from what had occurred in the pre-vious years. One key reason for the slowdown was soft VC/PE (ven-ture capital and private equity) activity leading to companies scaling back on growth plans and instead focusing on profitability. Further-more, with funding drying up and becoming restricted to only a few big players in each segment, several start-ups folded up. The demon-etization drive in November 2016 also impacted growth given the massive reliance on cash-on-delivery. However, funding has resumed in 2017 and with that we see companies are focusing on growth again. The digitization push from the government however, reinforces our view that a lot more transactional activities are likely to be done

online as big data, the availability of funding to both merchants and customers, and the rapid adoption of digital payments will make it a more convenient and fulfilling experience.

eCommerce was about 2% of the total retail market in 2016 and we see this climbing to 12% of the retail market by F2027 (C2026), reaching a size of US$200bn (including food delivery). While smart-phones, electronics and apparel are some of the prominent catego-ries today, we expect grocery, personal and beauty products, furniture and food delivery to become important as well. The key drivers of this growth will essentially be a growing population of online shoppers aided by a large assortment of merchandise avail-able online.

Exhibit 75:Top eCommerce Apps in India (in Terms of Downloads)

Rank App Category

1 Paytm General merchandise/Digital Wallets

2 Amazon India General merchandise

3 Flipkart General merchandise

4 Snapdeal General merchandise

5 Myntra Fashion/Apparel

6 Limeroad Fashion/Apparel

7 Voonik Fashion/Apparel

8 Shopclues General merchandise

9 Jabong Fashion/Apparel

10 AJIO Fashion/Apparel

Source: Sensor Tower, Morgan Stanley Research; the above rankings are based on downloads for the 12 months ending August 2017

Exhibit 76:Engagement Levels on eCommerce Platforms Looking Robust in India; Average Time Spent on Various Online Platforms in India in July 2017, Along With a US Comparable (in Minutes)

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Source: ComScore, Morgan Stanley Research; Data for July 2017; Average time spent calculated as total time spent in minutes divided by total unique visitors/viewers

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Exhibit 79:India's Online Spending Per Capita as a Percentage of GDP Per Capita in 2026 Could Be Similar to That of China in 2010 in Our Base Case Sce-nario, Based on Parity in GDP Per Capita (US$, %)

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China GDP per capita (US$) India GDP per capita (US$)

India - Online spend as % of GDP per capita (RHS) China - Online spend as % of GDP per capita (RHS)

India - Bear case

scenario

India - Bull case

scenario

Source: CEIC, International Monetary Fund, World Economic Outlook Database, Morgan Stanley Research (e) Estimates. Please note that F2027 represents calendar year C2026 ending December 2026 and so on for the previous years.

Exhibit 80:VC/PE Funding: General Merchandise Dominates Within eCommerce (January 2014 to YTD 2017)

General merchandise

Fashion, shoes and accessories

Furniture and home décor

Baby care

Groceries

Jewelry

Source: Economic Times, VC Circle, Inc42.com, Crunchbase, company data, Morgan Stanley Research

Exhibit 81:Key Investors in Indian eCommerce Sector

Flipkart

Paytm

•SoftBank

•Tiger Global

•Naspers

•Microsoft

•eBay

•Tencent

•Steadview

•Accel India

•SoftBank

•Alibaba Group

•SAIF Partners

•Silicon Vallley Bank

•Nexus India Capital

•GIC

•Abraaj Group

•Bessemer Venture

Partners

•Helion Venture

Partners

•SoftBank

•Nexus Venture Partners

•Kalaari Capital

•Tiger Global

•SoftBank

•Nexus Venture

Partners

•Kalaari Capital

•Bessemer Venture

Partners

•eBay

Source: Economic Times, VC Circle, Inc42.com, Crunchbase, company data, Morgan Stanley Research

Exhibit 78:eCommerce as a Percentage of GDP: The Effect on the Indian Economy Is Likely To Be High

0.0%

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China

US

India

Source: IMF, IDC, Euromonitor, Morgan Stanley Research. eCommerce estimates are Morgan Stanley Research estimates. Please note that F2027 represents calendar year C2026 ending December 2026 and so on for the previous years.

Exhibit 77:eCommerce Sales in India to Cross US$200bn by 2026 and Constitute ~12% of Total Retail Sales in India in our Base Case Scenario (US$bn, %)

0.0%

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eCommerce Sales (US$ bn) ( L.H.S.) eCommerce sales as % of total Retail sales - Base Case (R.H.S.)

Bull Case

Bear Case

Bull Case

Bear Case

Base Case

Base Case

Source: Euromonitor, Morgan Stanley Research Estimates. Please note that F2027 represents calendar year C2026 ending December 2026 and so on for the previous years.

BLUEPAPERM


Key Takeaways1. We expect India to continue to be among the world's best-performing markets, with a potential 24% CAGR in US dollar returns over the coming five years.

2. We expect such a return to be driven by acceleration in earnings growth (12% CAGR, 2017-27, in US dollar terms), as well as by multiple expansion.

3. The starting point of under-penetration combined with digitization almost guarantees growth in financial assets and liabilities on the household balance sheet, driving up the size of the domestic mutual fund industry and household ownership of equities.

4. We would focus on investing in the financials, consumer, and emerging large caps categories, while avoiding global sectors, such as technology and pharmaceuticals, to play this story.

5. We expect considerable expansion in market activity, with trading likely to rise from US$21 trillion to US$41 trillion in 2027, we estimate.

Implication 4: Digital to Drive Equity Bull Market

Exhibit 82:India Equities at a Glance

Key Forecasts Current F2027e Bull Bear

BSE Sensex 31,627 1,00,000 1,30,000 65,000

10-year CAGR 7% 12% 15% 7%

Market Cap (US$ billion) 2,100 6,100 8,500 3,700

10-year CAGR 6% 11% 15% 6%

Aggregate Trading Turnover (US$ bn) 21,289 40,951 57,375 23,618

Cash Volumes (US$ bn) 1,131 4,575 6,375 2,220

Derivatives Volumes (US$ bn) 20,152 36,376 51,000 21,398

10-year Equity Issuances (US$ bn) 166 500 850 259

10-year Domestic Equity Flows (US$ bn) 60 420 706 211

Domestic Equity Mutual Funds AUM (US$ bn) 111 1,000 1,530 481

ETF AUM (US$ bn) 9 200 300 100

Source: Morgan Stanley Research (e) estimates

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54

India Could Continue to Be a Strong Equity Market over the Next Ten Years

Exhibit 83:India - The World's Top-performing Market Over Two DecadesTop markets Market Cap (US$

bn)

Market Cap

to GDP

20 year

returns

UNITED STATES 7,691 40% 164%

CHINA 7,691 65% -5%

JAPAN 5,754 119% 23%

UNITED KINGDOM 3,593 144% 18%

FRANCE 2,493 103% 114%

GERMANY 2,350 69% 109%

CANADA 2,255 141% 188%

INDIA 2,105 86% 396%

SWITZERLAND 1,750 265% 159%

KOREA 1,544 103% 387%

AUSTRALIA 1,327 98% 140%

TAIWAN 1,180 208% -4%

BRAZIL 944 44% 88%

SPAIN 830 67% 88%

SWEDEN 829 163% 177%

Source: Bloomberg, IMF, WEF, MSCI, RIMES.

India’s digitization program, as discussed, has the potential to lift GDP growth. The concomitant impact is that corporate earnings growth would also likely accelerate. India's history shows a good cor-relation between nominal GDP growth and earnings, albeit earnings also depend on other factors such as the investment and saving rate. We expect this relationship to be sustained going forward. Ulti-mately, earnings growth is what drives share prices, but we also sense that Indian multiples could expand in the years ahead. Thus, Indian stock markets could be among best-performing in the world in the coming decade.

Indian equities have been strong performers over the past 20 years. In US dollar terms, the MSCI India index ranks as the top-performing market among the world's largest economies. This is consistent with India’s GDP growth, which also ranks among the best over this period. Indeed, in local currency terms, the market has done even better.

With such trailing performance, the temptation may be to be more cautious about the coming decade. However, in our view, factors seem ripe for India's outperformance to continue in the coming decade.

Why do we hold such a positive view?

First, we expect US dollar earnings to compound at 12% over the next ten years

Exhibit 84:Earnings Growth Versus GDP Growth - Strong Relationship

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

8% 10% 12% 14% 16% 18%

Broad Market Earnings growth 2- year MA

Nominal GDP growth 2-year MA

Source: Morgan Stanley Research, Morgan Stanley Research estimates

We think earnings can easily match or better our forecasts for nom-inal GDP with a 10.1% CAGR in US dollars over the next 10 years. The next five years could witness significantly more growth than the latter part of the ten-year period, given the low starting point of trailing earnings. India’s digital story could also lift India’s credit-to-GDP ratio. Rising credit to GDP is good for earnings growth. Rising nominal growth is also good for earnings. There is also another metric that should support the coming earnings cycle: the starting point of profit share in GDP is itself attractive – sitting well below trend, and we expect mean reversion as explained below. That the 10-year trailing CAGR in earnings is well below historical levels is only an added advantage to the earnings outlook for the coming period.

BLUEPAPERM


Our framework to understand earnings comes from the Kalecki Equation, which itself is derived from the identity for the current account:

l Current Account = Investment - Saving (as % of GDP)l Current Account = Investment - (Government Saving +

Household Saving + Corporate Saving) (all as % of GDP)l But Corporate Saving = Corporate Profits - Corporate Divi-

dends, so, rewriting, we getl Corporate Profits (as % of GDP) = Investment - Current

Account - Government Saving - Household Saving + Divi-dends (as % of GDP)

This gives us the share of profit in GDP, and, multiplying it by nominal GDP growth, yields the nominal earnings growth rate. This analysis helps explain the source of earnings. Thus, profit share in GDP is a function of the investment cycle, the current account, and the sav-ings rate of the government and households. We expect the invest-ment cycle to turn in the coming months, as explained earlier. While a declining fiscal deficit is a drag on earnings, the changing mix of household saving, from physical to financial, should provide signifi-cant support for profits. Digitization is helping accelerate the shift in household saving to financial assets. The current account appears range bound, at around 1.0-1.5% over the next 10 years, which is neu-tral for profits.

Exhibit 85:We Expect Profits to GDP to Rise over the Next Decade

3%

4%

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1991

1993

1995

1997

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2009

2011

2013

2015

2017e

2019e

2021e

2023e

2025e

Profits / GDP %

Source: CEIC, Capitaline, Morgan Stanley Research (e) estimates

Exhibit 86:Rising Bank Credit Will Support Earnings Growth

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Bank Credit

Broad market (Ex oil) earnings growth YoY -RS

Source: RBI, Capitaline, Morgan Stanley Research

Factors that favor earnings growth include a rising investment rate and household balance sheet leveraging.

l We forecast that the nation's investment rate will rise, led by public investment, especially in infrastructure. We also expect the private capex cycle to turn next year. The gov-ernment spending mix has changed favorably towards investments, but aggregate government spending is still muted, and, to some extent, offsets the positive impact of a rising investment rate.

l Positive real rates have helped reduce the current account and are positively affecting the mix of household savings towards financial saving. We expect the current account deficit to stay in a narrow range, unlike circumstances in the recent past, when India ran a very high deficit. When the current account is in deficit, it means local demand is being serviced by global production, reducing domestic production and earnings.

Households are leveraging-up their balance sheets, a prom-ising development for consumption, and a counter to a rel-atively strong savings rate. The shift in the household balance sheet is being supported by India's digitization pro-gram, which will increase penetration of the financial system as well as improve transparency thereby reducing the attractiveness of gold and property as asset classes. The starting point of under-penetration almost guarantees growth in financial assets and liabilities on the household balance sheet. For example, mutual fund assets are just 9% of GDP compared with 100% in the US and consumer loans are only 16% of GDP - albeit partly explained by low per capita income.

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56

Exhibit 87:Our Macro Model Points to Recovery in Earnings

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F2023e

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Corporate Profit Growth Based on the Macro model

Actual Broad Market Profit Growth

Source: Morgan Stanley Research, Morgan Stanley Research estimates

Exhibit 88:India's EPS Growth Appears to Have Troughed

-10%

-5%

0%

5%

10%

15%

20%

25%

30% MSCI India 5-year CAGR trailing EPS growth MSCI India 5-year CAGR trailing EPS growth

Source: RIMES, MSCI, Morgan Stanley Research

Second, we expect Indian multiples to remain above historical averages - and a move towards 100,000 Sensex, or US$6 trillion market cap

Two factors are likely to drive the multiple:

1) Rising demand for shares from domestic investors: We think India is in the midst of a domestic liquidity supercycle. We project equity saving of between US$420bn and US$525bn over the next 10 years, versus the respective US$60bn and US$120bn that household and foreign portfolio investments had invested over the previous 10 years. The three main sources of these flows are mutual funds, pen-sion and provident funds, and insurance companies. The drivers of this change (see: Asia Insight: India's Domestic Liquidity Supercycle, May 2, 2017) are falling age dependency and low risk averseness (typ-ical of a young population) on the demand side, combined with macro stability and initiatives to educate investors, as well as progressive regulations and digitization, on the supply side. Consensus is still largely overlooking such drivers, and continues to be concerned about sustainability of a domestic equity savings trend. We expect five factors ("DREAM") to play an important role in driving an equity savings boom in India:

D – Demographics: A young population tends to be less risk averse, and, combined with accelerating income growth, is likely to save more, especially into equities.

R – Regulations: Multiple changes have made the equity markets more palatable to retail investors. Rule changes for institutions such as the National Pension System (NPS) and the Employees Provident Fund Organisation (EPFO) are also driving flows into stocks.

E - Education, or investor literacy: This has helped create better sav-ings and investing behaviour among retail investors, who, for the past 20 years, were almost absent from equities, leading to a big drop in accumulated savings' exposure to equities.

A - Appetite for risk: Trailing returns establish equities as a favored asset class over other categories, such as gold, bonds and property.

M – Macro: Positive real rates make financial assets more attractive, while improving growth underpins equity performance.

The demand for equities should be seen in light of the expanding financialization of India's economy, as driven by digitization, rising per capita incomes, and increasing financial literacy, among other factors. We estimate that financial savings could swell by US$5 trillion over the next 10 years, premised on the assumption that the financial sav-ings share in GDP rises 25bps in each of the next 10 years. We view this as a reasonable assumption because, despite the annual rise, the share of financial savings to GDP would still be lower than the pre-vious peak of 17.7% in F2007. By F2027, the financial-savings-to-GDP ratio would rise to 13.5%, we estimate, higher than the long-term average of 11%.

https://ny.matrix.ms.com/eqr/article/webapp/976d47b2-2589-11e7-b132-327dac2266b1?t=1493762532%3A1852%3A5712%3Avmias1106666&m=1&ch=autob#

https://ny.matrix.ms.com/eqr/article/webapp/976d47b2-2589-11e7-b132-327dac2266b1?t=1493762532%3A1852%3A5712%3Avmias1106666&m=1&ch=autob#

BLUEPAPERM


2) Stock multiples: The effect of declining public debt to GDP: As we argue, robustness in government revenues arising from suc-cessful execution of GST is likely to lead to a lower public debt to GDP ratio. It clearly follows that this would lead to a crowding in of private investments, with a positive impact on interest rates and inflation. This will also lead to higher multiples, given the historically inverted relationship between the change in public debt and P/E mul-tiples.

The sum total of higher earnings growth (which we estimate at 20% for the coming five years) and higher multiples implies that the leading indices could compound at around 24%, in US dollar terms (25% in INR terms), in the coming five years. This type of front-ended returns could lead to moderation of returns in the subsequent five years. Thus, the coming ten-year period could witness an 11% CAGR in US dollar stock returns, just a shade behind our forecast for earnings growth, at 12%, for the same period.

Exhibit 89:Declining Debt-to-GDP Ratio Helps Valuation Multiples

0

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4

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6

9.0% 10.0% 11.0% 12.0% 13.0% 14.0% 15.0% 16.0% 17.0%

P/B

Annual Change in Debt to GDP

Source: CEIC, MSCI, RIMES, Morgan Stanley Research. .Data as of August 31, 2017

Exhibit 90:Rising Profit Share in GDP Drives Market-Cap-to-GDP Ratio

y = 0.1207e20.779x

R² = 0.8384

0%

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120%

140%

160%

4% 6% 8% 10% 12%

Market cap to GDP

Net Profit to GDP

Source: BSE, NSE, Capitaline, CEIC, Morgan Stanley Research . Data as of September 20, 2017

Exhibit 91:Market Multiple in the Middle of Historical Range

R² = 0.766

y = -0.0358x + 0.246

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MSCI India Trailing P/B

Annual 10-year fwd MSCI India returns Current P/B of 3.1 implies a

10-year annual return of 13.8%

Source: RIMES, MSCI, Morgan Stanley Research. Data as of September 20, 2017

Exhibit 92:India Market Forecasts

10Y Avg. Trailing Peak Current F2027E

Nominal GDP growth in US$ 14.9% 20.2% 8.7% 10.2%

Nominal GDP - US$ bn 2503 6040

Net Profit to GDP 8.9% 10.7% 7.0% 8.5%

Net Profit growth (in US$) 12.8% 56.0% 1.8% 12.4%

Mkt Cap to GDP 80% 149% 84% 101%

India's Market Cap - US$ bn 1239 2105 2105 6100

Source: BSE, NSE, Morgan Stanley Research estimates

BLUEPAPERM

58

Portfolio Implications

a) Buy Emerging Mega Caps

In our view, as India gains performance versus emerging markets and the world at large, its MSCI EM index weight will rise. Already, India is under-represented in the index relative to its GDP rank in the EM world. As India's index weight rises, foreign flows will become larger, and the equity market will also attract "tourist" money – larger quan-tities of opportunistic flows. This will result in the search for large liquid names. Simultaneously, domestic institutions are likely to grow in size. Hitherto, domestic institutions derived a lot of their per-formance from buying stocks down the cap curve. This was a viable strategy when domestic funds were small relative to the market. But, going forward, larger size will increase the need to make the right calls on large liquid names. Counterintuitively, getting these large-cap calls right may become key to beating the market. The third reason to favor large caps is likely growth in exchange-traded index funds. We forecast that ETFs will grow 30x in the coming decade, to US$200bn in assets by 2026. From a relatively small size of US$100mn in 2009, ETF assets have grown to US$8.4bn in size in a span of seven years. We expect ETFs in India to gain further traction as provident funds pursue a policy of channelling their investments in equities via ETFs. In our view, all these trends point to the growing importance of mega and large caps in India.

Exhibit 93:India's Index Weight Set to Rise in the Coming Years

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India GDP weight in EM

msci ff market cap weight in MSCI EM

Source: MSCI, IMF estimates, Morgan Stanley Research

Exhibit 94:Domestic Mutual Fund Assets: Likely to Rise Tenfold, to US$1 Trillion in 10 Years

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Source: AMFI, Morgan Stanley Research. e=Morgan Stanley Research estimates

Exhibit 95:ETF AUM Has Risen 8x in the Past Few Years

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Provident fund flows into ETFs

Source: AMFI, EPFO annual report, Morgan Stanley Research

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b) Buy Financials and Discretionary Consumption; Avoid Global Sectors

Exhibit 96:Consumption and Financial Sectors to Gain Share in Total Market Cap

22% 30%

25% 33%

36% 20%

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share in India's market cap

Source: Capitaline, Morgan Stanley Research estimates.

Exhibit 97:Currently, India Has a High Food Share in Its Overall Consumption

CPI Basket Urban India USA

Food and beverages 36% 15%

Housing 26% 37%

Clothing and footwear 6% 3%

Fuel and light 6% 5%

Transport and communication 10% 19%

Healthcare 5% 9%

Recreation 2% 6%

Education 6% 3%

Others 5% 4%

Source: BLS, CEIC, Morgan Stanley Research

Rising GDP growth, a rising loan-to-GDP ratio, and market share gains for the private sector financials at the expense of the public sector are likely to drive strong top-line and earnings growth for Indian private sector financials, in our view, boosting the sector's performance rela-tive to other sectors in the coming years. We expect the share of financials in India's total market to rise from 22% in 2017 to 30% by 2027, with their absolute market cap likely rising from US$460 billion to US$1.8 trillion in the coming ten years.

We expect discretionary consumption to surprise on the upside because of rising GDP growth and increasing consumer credit pene-tration, aided by digitization. We expect consumer credit to com-pound at around 17% annually over the next ten years. Given the high share of food in India's consumption basket, we expect the food share to decline as per capita incomes rise. Not only is nominal income set to grow faster in the coming decade, but future consumption is being advanced through leveraging, and non-food consumption itself is likely to grow faster than overall consumption. Further, digitization will likely lead to an increase in the share of the organized sector in the consumption space. Versus an overall annual GDP growth of 11%, it is quite possible that organized non-food consumption registers mid-teen growth in the coming decade. Thus, the share of consump-tion-related sectors (discretionary plus staples) in the market capi-talization could rise from just over 25% to 33%, at the expense of global sectors. This means that these sectors could add up to US$2 trillion in market cap by 2027, up from US$500 billion cur-rently.

BLUEPAPERM

60

Exhibit 98:Tech and Pharma Underperform, But Could Keep Experiencing Trading Pops

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Performance of Technology and

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Source: Capitaline, Morgan Stanley Research

Exhibit 99:The Coming Financial Savings Boom

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Source: RBI, Morgan Stanley Estimates

Global sectors, such as software services and healthcare, have already lost market appeal over the past few years. The valuations for some large-cap stocks in these sectors have turned attractive, and they find a place in our Focus List, with a 12- to 18-month time horizon, with a portfolio perspective in mind. However, widening our perspec-tive to a longer, multiyear view, these sectors could continue to lose share in the overall market as their earnings lag those of the domestic sectors. So, to fund overweight positions in Financials and Consumer Discretionary, portfolio managers could aim to be underweight any of these sectors: Materials, Energy, Software Services, Pharmaceuti-cals.

c) Big growth in capital markets

We note two additional arenas that could grow along with India's market capitalization: stock market trading and equity issuances. At a cash trading to market cap level of 56%, India is well below the 88% average for the world's top 20 markets (by market cap). We expect trading to rise as financial savings penetration improves. Assuming that, over the next ten years, India's cash volumes trade at 75% to market cap (still below the world average) and derivatives volumes trade at 8x cash volumes (the trailing average), this would imply that India could be trading about US$4.5 trillion in cash and another US$36 trillion in derivatives, up from current levels of US$1.1 trillion and US$20 trillion, respectively. As market cap grows, we expect new listings, as well as existing listed companies, to raise fresh cap-ital. India's 20-year trailing equity issuances are 1.7% of market cap. However, during the previous bull market (2004-08), equity issu-ances amounted to 2.3% of market cap. We think issuances could head back toward that level in the coming years. Using the historical average of 1.7%, equity issuances could add up to US$500 billion in the coming decade, as compared with US$166 billion in the trailing 10-year period.

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Implication 5: Financials – US$1.8 Trillion Market Cap in 10 Years

Key Takeaways1. Strong asset growth should help Indian lenders to grow earnings at a good pace. Technology will impact various sources of revenue. However, Indian lenders lack economies of scale – as more business moves online, we expect operating leverage to be very large. The gap between digital leaders and laggards will cause continued shifts in market share.

2. We expect the market cap of financial services stocks to reach US$1.8trn over the coming decade, from US$370bn in F2017. This will be driven by the growth of existing businesses and new listings.

3. We believe the combined market cap of non-banks will grow faster than banks as they continue to gain share and as there are new listings for insurers, AMCs and other capital-markets businesses. We expect SOE banks to decline to less than 10% of the sector's market cap.

Exhibit 100:Indian Financials: Key Indicators Over Next 10 Years and Likely Move in Market Shares

F2007 F2017 F2027EF07-17

CAGR

F17-27E

CAGRF2007 F2017 F2027E

% %

Digital Payments 11 107 1,208 25.1% 27.4% 1.2% 4.7% 20.0%

Total Loans 512 1,530 4,704 11.6% 11.9% 51.9% 67.1% 77.9%

MF AUM 74 273 1,935 13.9% 21.6% 7.5% 12.0% 32.0%

Life Insurance Premiums 36 62 185 5.7% 11.5% 3.6% 2.7% 3.1%

General Insurance Premiums 6 18 59 10.9% 13.0% 0.6% 0.8% 1.0%

E-Commerce 0 15 200 41.5% 29.7% 0.0% 0.7% 3.3%

Market Turnover (Cash) 667 1,131 4,575 5.4% 15.0% 67.6% 39.6% 75.7%

Market Cap (Overall) 805 2,105 6,100 10.1% 11.2% 82.5% 79.6% 101.0%

Market Cap (Financials) 95 371 1,844 14.5% 17.4% 9.7% 16.3% 30.5%

USD Bn % of GDP

Source: RBI, IRDA, Bloomberg, Morgan Stanley Research (E) estimates. USD/INR for FY17 we have used is 67. MF AUM for FY17 is 4Q Average AUM. F2017 Market Turnover (Cash) and Market Cap (Overall) are current data

Exhibit 101:India Financials Market Cap as Percentage of GDP - Comparing with US and China as it Stands Now

Market Cap US$ Bn

As % of

GDP US$ Bn

As % of

GDP US$ Bn

As % of

GDP US$ Bn

As % of

GDP

Financials 4,795 25.7% 2,431 21.7% 371 16.3% 1,845 30.5%

Banks 2,044 11.0% 1,529 13.6% 226 9.9% 966 16.0%

Insurance 1,062 5.7% 410 3.7% 10 0.5% 216 3.6%

Asset Management 452 2.4% 135 1.2% 0 0.0% 77 1.3%

Others 1,237 6.6% 357 3.2% 134 5.9% 586 9.7%

USA (Current) INDIA (F2027E)CHINA (Current) INDIA (F2017)

Source: Bloomberg, Morgan Stanley Research (E) estimates. USD/INR for F2017 we have used is 67

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Exhibit 102:India Financials Market Cap - Comparison with Large Economies as They Stand Now

In US$ Bn ITALY GERMANY FRANCE CANADA JAPAN UK USA

Financials Market Cap 222 273 374 645 688 788 4,795 2,431 1,845

% of GDP 12% 8% 15% 42% 14% 30% 26% 22% 31%

G-7 Nations (Current) CHINA

(Current)

INDIA

(F2027E)

Source: Bloomberg, Morgan Stanley Research (E) estimates

Exhibit 103:Indian Financials: Market Cap to GDP

0.0%

3.0%

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18.0%

21.0%

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Mkt Cap (Rs Trillion) As % of GDP, RS

Source: Bloomberg, Morgan Stanley Research

Indian financial stocks have been strong performers over the past two decades. Their market cap increased by >80x over this period as the underpenetration of the financial services industry was reduced. Even over the last 10 years (from elevated levels before the global financial crisis as the average P/E of the sector in February 2008 was 31x), the market cap of Indian banks has increased almost 5x (private banks have seen a 7x increase).

Exhibit 104:Market Cap Progression: Private Banks Will Dominate Market Share Formation in Nominal Terms

0

500

1000

1500

2000

F2017 F2027E

SOE Banks Private BanksNBFCs + HFCs AMCsLife Insurance (ex. LIC) General InsuranceOthers

Source: Bloomberg, Morgan Stanley Research estimates. Note: Data in US$ Bn

We expect continued strength for the financial services sector over the decade to come. In this section, we look at the lending, insurance and capital markets-related businesses separately and conclude that they can achieve a combined market cap of US$1.8trn in 10 years – a fivefold increase from the F2017 level. This will come primarily from growth and new listings across the financials space.

We continue to expect a shift in market share towards private players (banks, NBFCs and other financial businesses), with SOE banks likely to be pushed further out to the fringes.

Exhibit 105:Indian Financials: Change in Market Cap, Rolling 12 Months YoY

-80%

-40%

0%

40%

80%

120%

160%

Dec-99

Jun-00

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Jun-17

Source: Bloomberg, Morgan Stanley Research

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A point to note here is that while the structural story for Indian finan-cials is very strong, there will be cyclical downturns that may be fairly aggressive. Since 2000 Indian financials have delivered very strong returns, but there have also been periods of big corrections. The next 10 years will likely be similar, with strong returns but significant vola-tility. Given the structural thematic we would advise investors to buy any dip in the non-SOE part of the financial system.

Banks, NBFCs and HFCs – Upside Ahead, Driven by Growth and Share Gains for Better Lenders

An interesting thing has happened over the past five years. System's return on assets fell to 0.4% from 1% – and yet the banks' combined market cap rose from US$135bn in 2012 to US$265bn as of August 2017. This has essentially been driven by the big shift in market share towards the private players, which trade at much higher multiples. As a result system P/E multiples for the sector have increased.

Exhibit 106:Indian Banking System's ROA Has Compressed Sharply Since F2012 Due to NPLs

0.0%

0.3%

0.6%

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F2017E

Source: RBI, company data, Morgan Stanley Research (E) estimates

Exhibit 107:Profit Share of Bank Groups

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SOE Private Foreign


Over the next 10 years, we expect banks' loan growth to increase by 12% annually – implying an average credit multiplier (nominal credit growth as a percentage of nominal GDP growth) of ~1x. As men-tioned in an earlier section, this will primarily be driven by loan growth in the consumer and MSME sectors. Corporate loan growth is likely to be fairly muted in comparison.

We expect the SOE banks' loan market share to fall to around 35% by F2027 from 65% in F2017 (this is market share within the banking sector). This is driven by our view that the balance sheets of most SOE banks will remain fairly challenged, with capital being infused in a trickle-down fashion. We expect the credit growth of SOE banks to be 5% annually over the next 10 years, with the larger banks growing at 7-9% but some smaller ones contracting their loan books. Private banks, on the other hand, are likely to see annual loan growth of 21%. Overall, we forecast that credit growth in the banking system will average 12% annually in the next 10 years.

This is fairly conservative given Morgan Stanley's estimate of nom-inal GDP growth at a CAGR of more than 11%. But with SOE banks being unable to grow, the system overall will struggle to reach loan growth of much more than 13% annually. Some of this additional demand will likely be met through strong NBFC and HFC growth (including fintech lenders in this space) and some will move towards the bond markets.

Exhibit 108:Indian Financials: Our Expectation of Loan Growth Over the Next 10 Years...

% CAGR

F17-27E

SOE Banks 14,401 56,243 89,657 5%

Private Banks 4,148 22,370 144,879 21%

Foreign Banks 1,263 4,181 13,650 13%

NBFCs 1,366 11,556 48,648 15%

HFCs 1,096 8,173 47,847 19%

TOTAL 22,275 102,524 344,681 13%

GDP 42,947 152,781 442,821 11%

Loans / GDP 51.9% 67.1% 77.8%

F07 F17 F27ERs Bn

Source: RBI, NHB, company data, Morgan Stanley Research (E) estimates

Exhibit 109:…As Well As Market Share of Lending

% of Total F07 F17 F27E

SOE Banks 65% 55% 26%

Private Banks 19% 22% 42%

Foreign Banks 6% 4% 4%

NBFCs 6% 11% 14%

HFCs 5% 8% 14%

Source: RBI, NHB, company data, Morgan Stanley Research (E) estimates

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So essentially a larger part of the banking system will be dominated by the better-run – and therefore higher-multiple – businesses such as private banks, NBFCs and HFCs. We look at these segments sepa-rately from an earnings and market cap perspective.

Banks – Asset growth, stable ROA and private-sector share gain will drive market-cap creation

From a profitability perspective, technology will impact banks in the form of lower revenue yield and lower costs. There are clearly a number of revenue streams where banks will earn less. As of now,

most of the disruption due to technology has been limited to the pay-ments space as mobile wallets take share from established payment gateways. However, moving ahead we see pressure on various sources of revenue – MDR charges, distribution income, low-cost deposits, high-yield loans – which in turn will impact both net interest income and non-interest income. The exhibit below shows the level of disruption for key revenue items now and for the next few years.

Exhibit 110:Areas of Disruption Versus Revenue Impact as Technology Usage Gets More Widespread

Payments

CASA

Unsecured Loans

Mortgages

Distribution - Simple products (MF, protection)

Distribution - Complicated products (Traditional

Insurance)

Remittances

Lev

el o

f D

isru

pti

on

---

>

Impact on Revenues --->

Now In Next Few Years


Exhibit 111:Indian Banks: Commissions From MF Sales Will Be Under Pressure

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AX

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I

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YE

S

Rs Mn As % of Fees, RS

Source: Company data, AMFI, Morgan Stanley Research

Exhibit 112:Indian Banks: Revenue From MDR Charges Is Another Source of Pres-sure

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Source: Company data, Morgan Stanley Research estimates

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Revenue yields will come off for the system. But, the positive side will be lower costs – both opex and credit costs. Against this backdrop, how should we think of ROA for the system as a whole over the next decade? We look at each of the key lines of ROA:

Net interest income: We expect yields on the overall loan book to be relatively stable over the next decade. Loan yields will come down across products as underwriting becomes easier and better. How-ever, as the loan mix shifts towards MSME/consumer loans from the current domination by corporate loans, there will be some net interest margin (NIM) support.

The other risk to net interest income (NII) will come from competi-tion for deposits. Since the RBI deregulated saving account rates, most banks have stayed away from competing aggressively for these deposits. Some of the smaller banks have offered higher rates (and gained significant share) but larger players have generally stayed away from competing. As it becomes easier to move money between banks, larger banks may have to start thinking more about competi-tion.

We are assuming a contraction in NII/assets from 2.9% in F2012 to 2.7% by F2027.

Fees: This is the part of revenues that will likely come under pressure from the increased use of technology. Clear pressures will be felt in fees from the distribution of financial products – mutual funds, insur-ance, and so on. We expect a larger share of these products to be sold through direct channels over the next decade. Cyclically, this busi-ness is booming for banks given the sharp pick-up in equity markets. But structurally this will likely decline.

Various other parts of fees like MDR should also reduce over time – however, a pickup in volumes (which will be much faster than asset growth) should help this part of fees to be stable as a percentage of assets.

Costs: Indian banks run fairly subscale businesses. This is driven by the country's relatively scattered branch network given the vast geography and smaller banking system pie per capita. Over the next 10 years, banks will be in a position to control this meaningfully.

1) As GDP expands, banking system assets should expand at a CAGR of 12%. This will increase economies of scale. This increase in the size of the system balance sheet itself will also help improve costs to assets. But this will be accentuated by the rapid increase in the digiti-zation of banking services.

Exhibit 113:Indian Banking System Lacks Economies of Scale

0

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a

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Thaila

nd

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Ph

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Loan per Capita (in USD)

Deposit per Capita (in USD)

Source: Central banks, CEIC, Morgan Stanley Research

Exhibit 114:HDFC Bank: Sharp Increase in Balance Sheet Per Employee and Per Branch

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Employees (Number) Assets / Employee (Rs Mn), RS


2) The implementation of technology in almost all facets of financial services will reduce the requirement of branch expansion. We have already started seeing signs of this, with branch sizes getting smaller, not necessarily occupying premier retail space, and cuts in manpower requirements.

Costs as a percentage of assets for Indian banks are among the highest in Asia, and we expect banks to easily take out 40-50 bps of assets over the next decade. This would imply that underlying ROA should be fairly stable for banks. There will be pressure on revenues for sure - but cost control will help drive profitability growth.

This is evident in the case of HDFC Bank, which is at the forefront of offering digital solutions. Over the last three years, its balance sheet has grown at a CAGR of 21% while its branch network has grown at an 11% CAGR and its employee base at a 7% CAGR. In fact, since Sep-tember 2016, its employee base has declined by ~10,000 people despite the balance sheet expanding by 8%.

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This is likely to cause costs as a percentage of assets to come off fairly meaningfully. Hence, while there are pressures on revenues, the pri-vate banking sector as a whole should be able to reduce costs to meet these pressures and keep ROAs broadly stable. This, coupled with strong asset growth, will help drive earnings progression.

Exhibit 115:HDFC Bank's Versus SOE Banks' Cost Income Ratio: Sharp Divergence Between Winners and Laggards Ahead

35%

40%

45%

50%

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65%

F2005

F2006

F2007

F2008

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F2017E

F2018E

F2019E

HDBK SoE Banks

Source: Company Data, Morgan Stanley Research. Note: We have taken core income as NII+CEB

We expect banks with strong digital adoption to gain share in reve-nues and control costs very effectively. Carrying on the HDFC Bank example from above, if we compare HDFC Bank's cost income ratio evolution over the last five years with SOE banks' (where costs are sticky given state ownership), the differential will likely widen to 15-20% points over the next two to three years. This exemplifies how the gap between winners and "data laggards" will likely expand.

Exhibit 116:Indian Banks: Credit Costs (as Percentage of Loans); We Are Building in Normalization at ~85 bps of Loans

0

50

100

150

200

250F2008

F2009

F2010

F2011

F2012

F2013

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F2016

F2017

Source: Company Data, Morgan Stanley Research

We also build in normalized credit costs at around 50 bps of assets. Currently , credit costs are running at elevated levels given the corpo-rate credit cycle - which has been going for the past few years. This has impacted corporate lenders - IFRS implementation should make banks provide for bad loans quickly. The retail lenders have main-tained credit costs at 50-60 bps and stronger data can keep costs lower for longer. For F2027, we assume credit costs at 85 bps of loans (50 bps of assets).

Exhibit 117:Indian Banks: We Expect the Industry to Earn an ROA of 1.2% Over the Next Decade, With Fees and NII Pressure Negated by Cost Efficiencies

% of average assets F2012 F2017 F2027E

Net Interest Income 2.9% 2.6% 2.7%

Non-Interest Income 1.1% 1.2% 1.1%

Fee Income 0.7% 0.6% 0.6%

Others 0.4% 0.6% 0.5%

Total Revenues 4.0% 3.8% 3.7%

Total costs 1.8% 1.8% 1.5%

Pre-Provision Operating Profits 2.2% 2.0% 2.3%

Bad Debts 0.5% 1.3% 0.5%

Other Provisions incl Tax 0.7% 0.3% 0.6%

ROA 1.1% 0.4% 1.2%

Leverage 14x 13x 11x

ROE 14.6% 5.3% 12.5%


Banking sector's market cap will likely rise to US$965bn: The above estimates for asset growth, ROA and mix shift imply that profits for the Indian banking system will be around Rs4.7trn by F2027. This compares with Rs550bn in F2017 – a year that was hit by huge loan losses and a lack of profitability at SOE banks. In F2012, profits for Indian banks were Rs817bn, implying a CAGR of 12% over 15 years.

More importantly we expect the profit share gains of private banks to grow even faster than their likely gains in asset share. This will be driven by stronger profitability as costs are controlled even though revenue yield comes under some pressure. Five years back the SOE banks' share of system profits was around 60% – we expect this to fall to around 20% over the next 10 years. Private banks, on the other hand, should be about 70%, with foreign banks making up around 10% of system profits.

We assign P/E multiples to various types of banks – 8x for large SOE banks; 6x for smaller banks; 15x for private banks – and arrive at a potential market cap of Rs71trn for the banking sector over the next 10 years compared to the current Rs15trn. Within the subset, we expect the SOE banks' market cap to be up by about 1.6x – larger banks will likely do better but some of the smaller banks will find it tough to hold on to current market caps. Private banks is where the market cap pickup will be fairly material – we expect it to compound at around 19% in rupee terms.

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Exhibit 118:Indian Profits* of Foreign Banks: Citi Has Been Most Consistent

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PAT (Rs Bn)

Citibank StanC HSBC

* This is per local regulatory filings. Source: Company Data, Morgan Stanley Research

Foreign bank profits should also increase reasonably strongly over the 10-year period to Rs390bn (US$5.3bn). Within foreign banks, the profits above are based on regulatory filings and to that extent do not capture the India linked earnings, which are booked abroad (for instance, lending to an Indian corporate in US dollars from a foreign branch). The bulk of these profits are concentrated in three banks - Citi, HSBC and Standard Chartered - with Citi delivering consistent trend. This will likely continue, with DBS potentially becoming a bigger player as Digibank gets rolled out.

We are assigning no market cap as the Indian entities may not be listed (unless they decide to go for a wholly-owned structure and list – DBS has recently got approval in principle to open a WOS (wholly-owned subsidiary) in India). But for these banks, implied market cap will be reflected in their parent businesses.

In our bull case, we have assumed 2.3ppt stronger loan growth com-pared to the base case, driven by stronger GDP growth, greater market share gains in retail/MSME lending relative to NBFCs, and lower-than-expected competition (in fees and deposits) from fin-techs. We have also assumed higher RoA by 10bps, driven by higher cost efficiencies and lower competition in margins. Consequently, this in our view will also help improve valuations to 16x versus 14x in our base case. We estimate a US$1.5trn market cap in our bull case, 55% higher than our base case.

Exhibit 119:Indian Banks – Total Market Cap of Private and SOE Banks Could Reach Rs71trn Over the Next 10 Years, With Private Banks Gaining More Share

F2012 F2017 F2027E F2017 F2027E

10 Year

Average F2017 F2027E

SOE 495 5 881 959.6x 8.8x 10.0x 4,546 8,120

Private 227 434 3,424 24.7x 15.5x 15.0x 10,706 62,674

Foreign 94 118 386 NA NA NA NA NA

Total 817 557 4,691 18.7x 14.3x NA 15,252 70,794

PAT PE Market Cap

Rs. Bn

Source: RBI, company data, Morgan Stanley Research (E) estimates. To arrive at market cap, we have first computed the valuations of the standalone entities (PAT * core P/E as we see in the above table) and then added valuation of stakes in other entities.

In our bear case, we have assumed 3.5ppt slower loan growth com-pared to the base case, driven by weaker GDP growth and greater competition from NBFCs and fintechs. More importantly, we have assumed lower ROA by ~25bps versus our base case, driven by signif-icant compression in fee income and also margins (lower float and hence moderation in CASA ratios). Consequently, this in our view would also reduce valuations to 12x versus 14x in our base case. We estimate a US$475bn market cap in our bear case, 50% lower than our base case.

Exhibit 120:Market Cap of Indian Banks by F2027 – Scenario Analysis

Banks Base Bull Bear

Assets CAGR (FY17-27E) 12% 14% 8%

Assets (FY27E)

INR Bn 427,327 524,640 309,376

USD Bn 6,375 7,827 4,615

ROA (FY27E) 1.2% 1.3% 0.9%

PAT (FY28E) 5,344 7,350 3,089

Forward P/E 13.8x 15.5x 11.8x

MCAP (FY27E), Listed

INR Bn 70,794 109,326 34,642

USD Bn 966 1,491 473

Source: RBI, company data, Morgan Stanley Research (E) estimates. To arrive at market cap, we have first computed the valuations of the standalone entities (PAT * core P/E as we see in the above table) and then added valuation of stakes in other entities.

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NBFCs and HFCs – Strong outlook driven by market growth and share gains

Exhibit 121:NBFC and HFC Loan Book Grew at a 23% CAGR in FY07-17, to Rs19.5trn

0

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NBFC+HFC Loan Book (Rs Bn)


This is one space that has continued to do well over the last few years. A number of market participants are usually concerned about the sustainability of this space given the fact that these are wholesale-funded.

Because of these concerns, these stocks tend to be fairly volatile. Whenever the market slows, these stocks tend to have big draw-downs as concerns around asset quality and NIMs increase.

However, despite these concerns and the slowdown seen in India over the last five years by the broader financial system, this space has seen loans increase from Rs2.5trn in F2007 to Rs19.5trn in F2017 – a CAGR of 23%.

Given the likely increase in loan demand over the next 10 years and the fact that SOE banks will be unable to grow by much more than 5% given capital issues, NBFCs and HFCs will likely grow at a CAGR of 17% – taking their share in the system to 28% from 19% in F2017. Within this segment, the corporate NBFCs – dominated by infra-structure lenders – will likely lag, in our view, with consumer/SME NBFCs, diversified NBFCs and HFCs growing much faster.

With respect to profitability, below are our views on various seg-ments:

HFCs: In our view competition in home loans will continue to inten-sify, weighing on yields and NIMs. We are also seeing pricing competi-tion in developer loans intensify. Further, as data availability improves and as more avenues open up for MSMEs to borrow, their dependence on Loans against Property will go down, which could potentially impact the HFCs, which generally do only secured lending. Hence, we have assumed compression in ROAs from FY17 levels. Credit costs and operating costs are low and hence there is limited scope for meaningful change.

Consumer/SME NBFCs: These NBFCs will also face pressure on rev-enue yields, but we expect lower costs led by technology rollouts and a reduction in credit costs from all-time highs for some of the more cyclical NBFCs to result in slightly better ROAs than FY17 levels.

Diversified NBFCs: These NBFCs, being more diversified with respect to both lending (mix of corporate and retail loans) and rev-enue streams (non-lending businesses like asset manage-ment,wealth management, broking, investment banking, insurance, and so on), are better positioned to counter both the competition and cyclicality in businesses. We are building in some NIM compression and assuming some credit cost normalization from low levels, although we expect this to be offset by operating leverage in both the lending and capital markets businesses. This should result in some marginal ROA expansion from FY17 levels.

Corporate NBFCs: We expect some improvement in ROA as better quality credit is written, resulting in lower credit costs offset to a large extent by lower yields.

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Exhibit 122:We Expect Profitability at HFCs to Decline on Lower Margins due to Competition. We Expect Overall Profitability at NBFCs to Improve, Driven by Operating Leverage at the Consumer/SME/Diversified NBFCs and a Reduction in the Share of Large Infrastructure Loans in the Overall NBFC Loan Book

F2012 F2017 F2027e F2012 F2017 F2027e F2012 F2017 F2027e F2012 F2017 F2027e F2012 F2017 F2027e

Net Interest Income 3.1% 3.0% 2.7% 5.2% 5.6% 5.4% 7.7% 8.0% 7.1% 3.9% 4.8% 4.3% 4.0% 4.1% 3.1%

Non-Interest Income 0.5% 0.3% 0.3% 1.3% 1.8% 2.6% 0.5% 0.9% 0.9% 6.3% 6.4% 6.4% 0.1% 0.2% 0.2%

Total Revenues 3.6% 3.3% 3.0% 6.5% 7.4% 8.0% 8.2% 8.8% 8.0% 10.2% 11.2% 10.7% 4.1% 4.3% 3.3%

Total costs 0.5% 0.5% 0.5% 2.5% 3.0% 3.7% 3.2% 3.6% 3.0% 7.0% 7.2% 6.6% 0.4% 0.3% 0.3%

PPOP 3.1% 2.8% 2.6% 4.0% 4.4% 4.3% 4.9% 5.2% 5.0% 3.2% 3.9% 4.1% 3.7% 4.0% 3.0%

Provisions 0.2% 0.3% 0.3% 0.6% 1.5% 1.1% 1.4% 1.9% 1.6% 0.6% 0.6% 0.8% 0.1% 1.6% 0.5%

PBT 2.9% 2.6% 2.3% 3.4% 2.9% 3.3% 3.5% 3.3% 3.4% 2.6% 3.3% 3.4% 3.6% 2.5% 2.6%

Taxes 0.8% 0.8% 0.8% 1.1% 1.0% 1.1% 1.4% 1.1% 1.2% 0.9% 1.1% 1.2% 1.0% 0.9% 0.9%

ROA 2.1% 1.8% 1.5% 2.3% 1.9% 2.1% 2.1% 2.1% 2.3% 1.7% 2.2% 2.2% 2.6% 1.6% 1.7%

A) HFCs C) Consumer / SME NBFCs D) Diversified NBFCs E) Corporate NBFCsB) NBFCs (Aggregate of C,D,E)As % of Average Assets

Source: Company data, Morgan Stanley Research; e = Morgan Stanley Research estimates. The above computations are for underlying businesses and excluding numbers of holding companies

Exhibit 123: HFCs: One-year Forward P/E

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b-1

6

Aug-1

6

Fe

b-1

7

Aug-1

71Y Fwd P/E

Source: Thomson Reuters, company Data, Morgan Stanley Research

Exhibit 124:NBFCs (ex HFCs): One-year Forward P/E

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Aug-0

7

Fe

b-0

8

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-09

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b-1

7

Aug-1

7

1Y Fwd P/E

Source: Thomson Reuters, company Data, Morgan Stanley Research

These players usually trade at a discount to private banks given the lack of a retail funding franchise. We assume the same trend will con-tinue despite fairly strong growth.

In our base case, we assume that NBFCs will sustain a valuation mul-tiple of 14x forward earnings (compared with a 10-year average of 11x), driven by diversification of business and an increasing share of more profitable businesses, and HFCs trade at 14x forward earnings (10-year average of 15x) – implying a potential market cap of Rs39trn.

Exhibit 125:With Diversification in Revenue and Profit Streams and an Increase in the Share of Better-run Businesses, We Expect an Overall Forward P/E Multiple of 14x for NBFCs and HFCs Versus a 10-Year Average of 12x

F2012 F2017 F2027e F2017 F2027e

10 Year

Average F2017 F2027e

NBFCs 117 235 1,116 14.2x 15.7x 11.0x 4,717 20,142

Consumer / SME NBFCs 39 90 538 17.9x 15.0x 12.9x 2,010 9,277

Diversified NBFCs 10 60 402 14.6x 14.9x 22.5x 1,753 8,756

Corporate NBFCs 68 86 175 9.4x 10.0x 7.2x 954 2,108

HFCs 64 139 761 15.0x 14.1x 14.9x 3,697 18,363

Total NBFCs / HFCs 182 375 1,877 14.5x 17.6x 12.2x 8,414 38,505

Rs. Bn

Profits Forward P/E Market Cap

Source: Company data, Morgan Stanley Research; e = Morgan Stanley Research estimates. To arrive at market cap, we have first computed the valuations of the standalone entities (PAT * core P/E as we see in the above table) and then added valuation of stakes in other entities.

In our bear and bull cases, we assume a 2.5ppt lower/higher CAGR compared to the base case, key drivers being economic growth, the credit cycle and competitive intensity from banks. We have assumed an ROA differential of 20-25bp (mainly driven by pricing power and NIM) across the scenarios and a P/E multiple differential of 2x. In our base case, the combined market cap of NBFCs and HFCs works out to US$525bn versus US$795bn in the bull case and US$260bn in the bear case.

Exhibit 126:NBFCs and HFCs: Valuation Scenarios

NBFCs + HFCs Base Bull Bear

Assets CAGR (FY17-27E) 17% 20% 12%

Assets (FY27E)

INR Bn 109,438 135,058 70,877

USD Bn 1,493 1,842 967

ROA (FY27E) 1.8% 1.6% 2.0%

PAT (FY28E) 2,183 2,986 1,179


MCAP (FY27E)

INR Bn 38,505 58,129 19,060

USD Bn 525 793 260

Source: Morgan Stanley Research (E) estimates

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Thus, in our base case, the lending businesses – banks and NBFCs – will likely go from a market cap of Rs24trn now to Rs109trn in F2027. Almost the entire increase in market cap is being driven by earnings progression and a gain in share by better-run businesses.

Insurance (Life & General) to See Strong Growth and a Spate of New Listings

Until 2016 there was only one pure play on the insurance sector in India (Max Financial Services). Subsequently, ICICI Prudential Life Insurance got listed and now there are multiple life and general insurers which have filed DRHPs with the intent of going public. The market cap in this space is fairly small right now given that there are only two listed entities – but we expect a sharp pickup driven by growth and new listings.

We have kept LIC, India's biggest insurer, out of this analysis because there is not enough data on its operations.

Life insurance – We expect a market cap of US$126bn in 10 years (excluding LIC)

Insurance penetration has stabilized over the past two years after declining in F2009-14. From a top-down perspective, this has been driven by the stabilizing regulatory environment and the improving share of financial savings.

Incrementally, our view is that significant regulatory changes are likely done, and the shift towards financial savings is not only cyclical but also structural - given formalization of savings. This, coupled with relatively low penetration, should help the insurance sector to grow at ~13% CAGR over the next decade compared to nominal GDP growth of 11%.

Exhibit 127:Expect Insurance Penetration to Stabilize

0.5% 0.7%

1.9%

1.1% 1.1% 1.3%

1.2%

1.6%

2.2%

1.7% 1.6%

1.7%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

F2001

F2003

F2008

F2014

F2017

F2027E

Total Insurance Premiums (% of GDP) First Year Premium

Renewal Premium

CAGR

32%

1.7%

2.3% 2.8%

4.2%

2.7% 3.1%

CAGR

24%

CAGR

41%

CAGR

23%

CAGR

4%

CAGR

10%

CAGR

14%

CAGR

8%

CAGR

13%

CAGR

12%

Phase I - Entry of Private Players

Phase II - Expansion of Private Players

Phase III - Downturn in ULIPs

Phase IV - Growth Revival

Source: IRDA, company data, Morgan Stanley Research; E = Morgan Stanley Research estimates

Exhibit 128:Large Bank-backed Insurers to Grow Faster Given Better Operational Metrics

ICICI Pru

Max Life

Birla Sunlife

SBI Life

Bajaj Life

Kotak Life

Reliance Life

LIC

60%

70%

80%

90%

5% 10% 15% 20% 25% 30%

13th

Mo

nth

Pers

iste

ncy,

F2017

Adjusted Cost Ratio, F2017


However, large bank-backed insurers will grow faster (15-18% CAGR) than nominal GDP, driven by market share gains. They have access to banks and good operational metrics – both of these are critical in the new normal environment. While the regulator has allowed open architecture, we expect gradual moves by the large banks. On profit-ability, the current differential between large bank-backed insurers and other private insurers is quite high and we see it being sustained at elevated levels as the large bank-backed insurers increase their protection mix and leverage technology to improve efficiency and cross-selling.

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Exhibit 129:Focus on Protection, Which Is Under-penetrated, Will Drive Profitability

US Japan

Singapore

Korea

Malaysia Germany

Thailand

India

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 500 1000 1500 2000 2500 3000 3500

Su

m A

ssu

red

/ G

DP

(201

3)

Life Insurance Density (Premiums per capita in USD), 2014

Source: Swiss Re and ICICI Prudential Life Presentation, Morgan Stanley Research

Exhibit 130:Market Share Comparison - Sum Assured Versus APE

0%

15%

30%

45%

60%

75%F

2013

F2014

F2015

F2016

F2017

F2013

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F2013

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F2017

F2013

F2014

F2015

F2016

F2017

LIC IPru Life SBI Life Max Life Kotak Life Reliance Life Birla Sunlife Bajaj Life

Market Share (%) Sum Assured APE

Source: Company data, Life Insurance Council, Morgan Stanley Research. Note: Data is for F2017. Sum assured system data does not include Sahara Life and India First Life.

Technology will create the next leg of differentiation between private players

We expect a big change in the way insurance is distributed over the next 10 years, led by technology. The current generation of insurance buyers (35-40 years old) has a significant portion of customers who are less tech savvy and still visit branches for banking services, where a lot of insurance sales pitches actually take place.

However, over the next 10 years, the prospective insurance buyer could be quite different and much more digital. Indeed, branch foot-falls will come down significantly. This is a key challenge for private insurers as 50-60% of their insurance sales happen via bancassur-ance. In this context, building a relationship with prospective cus-tomers via strong digital infrastructure becomes very important.

Private insurance companies are creating infrastructure for this shift

Online sales for simpler products have been picking up – term insur-ance has picked up well and we expect low cost ULIP products to follow: For relatively simple/pull insurance products like protection, online insurance penetration has picked up quite significantly. This could be sales via a company's own online portal, partner or aggre-gator websites and even call centers (assisted online sales). How-ever, online sales are significantly under penetrated for most other savings products given that these are relatively complex products.

For relatively less simple or push products, digitization could empower distributors with better lead generation and sales – Key initi-atives that insurers are working on include a) upselling insurance pol-icies to existing customers at the time of inbound calls, policy maturity and also based on analytics; b) innovative digital marketing tools via social media, viral marketing and online display banners; c) integrating digital platforms with those of distributors – eg, straight through processing integration; d) emerging financial marketplaces and moving away from just placing products in partner ecosystems with differentiated pricing and promotion schemes for customers using analytics.

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As distribution evolves, we expect private players which are more nimble to continue to gain significant share from state-owned entity.

We expect the market cap of the private life insurance sector to rise to US$126bn by F2027 and for the top five private bank-based insurers to contribute 89% of that. A sector valuation exer-cise is not easy given the lack of detail around EV for all players. In our exercise, we have estimated EV for all private players based on a) reported net worth, and b) our estimates of VIF/policyholders' AUM for players where EV is not reported. We estimate the private sector EV to be US$14bn as of F2017, with the top five bank-based private life players contributing 57% of that.

Our view is that the top five bank-based private players (combined) could compound EV (pre dividends) at 15-20% over the next 10 years, driven by a) strong premium growth and b) improving profitability helped by an increasing share of protection and greater economies of scale.

For other private life insurers, we have assumed an RoEV (pre divi-dends) CAGR of 10%, much higher than the low single digits we cur-rently estimate. The improvement is driven by a) a cyclical uplift to growth, even as they lose market share, and b) an improvement in profitability given lower cost overruns. However, we expect RoEV to remain below CoE for multiple years, driving our low valuation for this group.

The bull case for the sector is a surprise recovery in the agency channel and potential regulatory changes that relax some of the stricter product regulations. Another driver would be higher-than-expected financial savings growth and a stronger-than-expected pickup in protection. We assume stronger EV growth (pre dividends) by 3ppts and also expect valuations to be sustained at higher levels.

The bear case for the sector is a) significant margin compression in the protection business, b) a significant growth slowdown in bancas-surance sales, driven mainly by lower footfall, and c) a potential increase in corporate income tax rates. Consequently, we assume weaker EV growth (pre dividends) by 3ppts compared to our base case. Against this backdrop, valuations moderate to 2.0x EV vs. 2.6x in our base case.

Exhibit 131:Private Life Insurance ValuationsLife Insurance Base Bull Bear

EV CAGR (FY17-27E) 13% 16% 10%

EV (FY28E) 3,533 4,715 2,627

Forward P/EV 2.6x 3.0x 2.0x

MCAP (FY27E)

INR Bn 9,247 14,226 5,299

USD Bn 126 194 72

Source: Company data, Morgan Stanley Research (E) estimates

General insurance – We expect a US$90bn industry in 10 years

We believe the general insurance industry can grow at a 15% CAGR (following a 13% CAGR over the past five years), even after which penetration will remain low at 1.0% of GDP (F2027)

As with most financial services, general insurance penetration in India is low at 0.8% (the world average was 2.8% in 2016) and is sup-ported by favorable demographics and stable to improving economic growth. Since 2000, the sector has grown through three broad phases: a) Phase 1 (2000-07): High growth for private players helped by the liberalization of the sector; b) Phase 2 (2007-11): Industry con-solidation with detariffing of key products and high losses in Indian Motor Third Party Insurance Pools (IMTPIP); and c) Phase 3 (2011 onward): Improving profitability helped by tariff revisions in third party motor insurance and new growth segments like crop insurance. Incrementally, we believe there are two key catalysts: 1) the Motor Vehicles (Amendment) Bill 2016, which can be a significant catalyst to growth and profitability as it intends to a) fix a maximum time limit for claim requests of six months (no limitation now), b) fix maximum insurer liability on claims, and c) encourage renewal registrations of motor vehicles; and 2) Digitization aided reduction in combined ratios. Another potential catalyst of profitability that needs to be watched is a potential for increased focus on profitability at PSU insurers given the government's drive.

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Exhibit 132:General Insurance Penetration

4.7

4.3

3.5 3.3 3.3

3.2

2.8 2.7 2.6

2.4 2.0

1.8 1.8 1.4 1.3

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A

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uth

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ica

UK

Jap

an

Italy

Chin

a

Bra

zil

Hong K

on

g

Irela

nd

India

Non Life Insurance Penetration, 2016 (%)

Source: Swiss Re

Exhibit 133:General Insurance Penetration to Improve to 1.0% of GDP

0.8%

1.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F2027E

Non Life Insurance Penetration, India (%)

Source: General Insurance Council, Morgan Stanley Research (E) estimates

Exhibit 134:Combined Ratios

-30%

0%

30%

60%

90%

120%

150%

Ba

jaj A

llianz

HD

FC

Erg

o

IFF

CO

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ICIC

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om

bard

Relia

nce

New

In

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Assura

nce

United Insura

nce

National In

sura

nce

Combined Ratio (F2017) Claims Commission Expense

Source: Company data

Leading private players are better placed on distribution, under-writing/product mix and also technology

To start with, the leading private players (ICICI Lombard, Bajaj Gen-eral, HDFC Ergo and so on) have a better product mix (more retail), distribution mix, underwriting capabilities, and more conservative reserving practices. Consequently, their combined ratio is much lower than peers'. This should continue to help them gain market share and improve profitability.

Moreover, we believe the general insurance industry could see a meaningful impact from technology adoption. In our view, tech-nology will play an even greater role in a) the underwriting process and policy selection and b) reducing costs. Unless competed away, the successful players could reduce combined ratios by at least 2-3% over the next 10 years. The key benefits of technology could be as follows:

a) Lower operating costs: Insurance is a cost-intensive business (with F2017 cost ratios of 20-40%), and digital platforms could be used to reduce cost of acquisitions, improve turnaround times, survey claims digitally (via video streams for motor claims or drones for wind turbines, and so on), and automate sales and customer ser-vice (chatbots, other apps).

b) Distribution: Not only can a greater amount of insurance policies be sourced digitally, but insurers can partner with various manufac-turers/dealers and provide end-to-end digital platforms for product innovation/solutions (mobile-based cashless claims, virtual surveys) – and this can help build sticky relationships. This also applies to banking and other distribution tie-ups.

c) Better risk management systems and underwriting: Insurers can utilize artificial intelligence and machine learning techniques to improve underwriting practices amid increasing data availability.

In our base case, we assume that industry RoEs average 10% over the next 10 years, and we also assume a P/E of ~15x. For the private players, we assume higher P/E multiples given better growth and profitability outlook. Our base case assumptions yield a valuation for the industry of US$90bn in F2027.

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The bull case for the industry would be a) significant changes in com-petitive practices by large public insurers, b) higher-than-expected benefits from technology changes, and c) the motor insurance bill getting cleared by IRDA, reducing the claim intimation period. This would imply stronger RoEs (11% versus 10% in our base case) and higher P/E multiples (17x versus 15x). Consequently, the valuation of general insurance in our bull case would be as high as US$131bn, 46% above our base case.

The bear case for the industry would be high and increasing competi-tive intensity, not only by the public sector, but also within the large players as they all eye profitable sub-segments and compete aggres-sively. This would imply weaker RoEs (8.5% versus 10%) and lower P/E multiples (12x versus 15x). Consequently, the valuation of gen-eral insurance in our bear case is US$57bn, 37% lower than our base case.

Mutual Funds – Strong AUM Growth and Listings Over the Next 10 Years

The fund industry in India has seen significant AUM growth over the past decade (with a F2007-17 CAGR of 22%) and the past five years (F2012-17 CAGR of 24%). The past three years have seen an accelera-tion (F2014-17 CAGR of 29%). Moreover, the composition of AUM has moved towards equity (F2014-17 CAGR of 43%). Equity has increased to 33% of AUM from 21% three years ago.

Despite this strong growth, the asset management industry remains very underpenetrated relative to other countries. Overall domestic AUM/GDP was at 9% as of 2016 and equity AUM/GDP was at 3% – one of the lowest levels among large countries.

Exhibit 135:General Insurance Market Cap ComputationsGeneral Insurance Base Bull Bear

PAT CAGR (FY17-27E) 27% 29% 24%

PAT (FY28E) 446 557 340


MCAP (FY27E)

INR Bn 6,572 9,602 4,153

USD Bn 90 131 57

Source: Company data, Morgan Stanley Research (E) estimates

Exhibit 136:Overall Domestic AUM/GDP (2016)

133%

101%

78% 76%

59% 57% 56% 50%

29%

12% 11% 10% 9%

0%

30%

60%

90%

120%

150%

AU

ST

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US

A

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KO

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TA

IWA

N

CH

INA

ME

XIC

O

IND

IA

DMs EMs

Overall AUM / GDP (2016)

Source: IMF, IIFA, Morgan Stanley Research

Exhibit 137:Domestic Equity AUM/GDP (2016)

56%

50%

26% 24%

13%

8% 12%

4% 3% 3% 3% 1% 1%

0%

15%

30%

45%

60%

US

A

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IND

IA

ME

XIC

O

CH

INA

DMs EMs

Equity AUM / GDP (2016)

Source: IMF, IIFA, Morgan Stanley Research

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Exhibit 138:Systematic Flows Gaining Share

52 92 118 143 145

205

317

439

18

-125

3

-145 -103

744

839 887

-200

0

200

400

600

800

1,000

F2010 F2011 F2012 F2013 F2014 F2015 F2016 F2017

SIP Flows Flows in Equity MFs

Source: AMFI, Morgan Stanley Research

We expect the growth in AUM to be sustained at a very strong pace. This is being driven by higher financialisation of savings – a trend that will accelerate, as discussed earlier in the report. Apart from a pickup in the economy and stronger financial savings growth, which we have discussed in other places, two trends will help AUM growth.

a) Rising share of systematic flows – Flows into systematic invest-ment plans have logged a CAGR of 30% in the last five years. The share of SIP flows in overall equity flows has been 28%, 38% and 49% in the last three years. Given that these are regular monthly invest-ment plans, these are fairly predictable and are good for long-term growth.

b) Rising contribution from smaller cities – In the past, mutual fund flows and AUM have been largely concentrated in the top cities. Even today, the top five cities account for over 70% of mutual fund AUM. However, in recent years the share of cities beyond the top 15 cities has been growing.

This is happening amid extremely strong growth in the top 15 cities. In our view, the share of the smaller cities in equities could have picked up even more sharply, given that debt flows are more likely to be from institutions and HNIs in urban areas. Technology will con-tinue to drive investors in these smaller cities towards mutual funds as it becomes easier to offer them products in a cost-effective way.

Exhibit 139:Contribution of B-15 Cities Has Risen Despite Strong Growth in the Top 15 Cities

AUM by Geography - Consolidated

data for MF IndustryF2013 F2014 F2015 F2016 F2017

Total AUM - Industry (Rs bn) 7,014 8,252 10,828 12,326 17,529

Top 5 Cities (Metros) 5,193 6,018 7,786 8,897 12,694

Next 10 Cities 900 1,108 1,477 1,675 2,254

Beyond Top 15 Cities 921 1,126 1,565 1,754 2,580

As % of Total Industry AUM

Top 5 Cities (Metros) 74.0 72.9 71.9 72.2 72.4

Next 10 - (Tier 1 Cities) 12.8 13.4 13.6 13.6 12.9

Beyond Top 15 Cities 13.1 13.7 14.5 14.2 14.7

YoY Growth (%)

Top 5 Cities (Metros) 24% 16% 29% 14% 43%

Next 10 Cities 9% 23% 33% 13% 35%

Beyond Top 15 Cities 6% 22% 39% 12% 47%

Source: AMFI, SEBI, Morgan Stanley Research. Note: B-15: Beyond top 15 cities.

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Our strategy team (Ridham Desai and Sheela Rathi) forecasts a 27% CAGR in equity AUM during F2017-27 – or a tenfold increase in con-stant currency terms, from US$100bn to US$1trn (discussed earlier in the report). We build in a 20% CAGR in debt AUM during the same period, compared with a 25% CAGR in the last decade. This translates into a 23% CAGR for overall AUM in INR terms. Adjusted for currency depreciation, we forecast overall AUM at US$1.85trn by F2027 (a 22% CAGR). AUM/GDP should increase from 11% to 28% over the coming decade.

Industry valuation: As of now there are no listed asset management companies. Some companies have already expressed an intent to list and have moved in that direction.

1. 'Reliance Nippon Life AMC files IPO papers'2. 'UTI Asset Management Company fairly ready for IPO, says

MD Leo Puri'

It is possible that more leading AMCs in India may list over the next decade. Most of the bigger ones are owned by financial conglomer-ates, and there may be continued moves towards price discovery through IPOs.

What could be the valuation for AMCs? Given that there are no listed entities in this space, there is no peer group in India to compare valua-tions with. However, there have been quite a few secondary market deals over the years (the last being the sale of a stake in Reliance Mutual Fund to Nippon Life in October 2015). Some of these deals have been done at valuations of around 5-6% of AUM. These are higher than global averages. But given the stronger growth prospects in India, it is possible that these levels may be sustained for several years.

We use a base case valuation of 4.0% of AAUM to arrive at an industry valuation of US$77bn by F2027. Our bull and bear case sce-narios assume AAUM CAGRs of 30% and 13% respectively, resulting in valuations of US$188bn (@5.5% of AUM) and US$26bn (@3.0% of AUM).

Exhibit 140:We Expect the Mutual Fund Industry's Domestic AUM to Post a 23% CAGR in F2017-27; AUM/GDP Should Increase from 11% to 28%

2,319 5,872 17,529

59,735

135,920

5% 7%

11%

22%

28%

0%

4%

8%

12%

16%

20%

24%

28%

32%

-

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

FY07 FY12 FY17 FY22e FY27e

AUM - MF Industry, Rs bn (LHS) as % of GDP (RHS)

Source: AMFI, Morgan Stanley Research; e = Morgan Stanley Research estimates

Exhibit 141:Assuming CAGRs of 27% and 20% for Domestic Equity AUM and Debt AUM Over the Next Decade, the Share of Equity in Overall AUM Would Rise to 47% Versus 33% in F2017

55% 68% 67%

60% 53%

45% 32% 33%

40% 47%

0%

20%

40%

60%

80%

100%

FY07 FY12 FY17 FY22e FY27e

Debt Funds Equity Funds

Source: AMFI, Morgan Stanley Research; e = Morgan Stanley Research estimates

Exhibit 142:AMC Industry: Valuation ScenariosAMCs Base Bull Bear

AAUM CAGR (FY17-27E) 23% 30% 13%

AAUM (FY27E)

INR Bn 141,869 250,364 64,419

USD Bn 1,935 3,415 879

Valuation Multiple (% of AAUM) (FY27E) 4.0% 5.5% 3.0%

MCAP (FY27E)

INR Bn 5,675 13,770 1,933

USD Bn 77 188 26

Source: e = Morgan Stanley Research estimates. AAUM = Average Assets Under Management.

http://www.livemint.com/Money/OmykKu9FTP5Y31wcU4vLSL/Reliance-Nippon-Life-AMC-files-IPO-papers-eyes-Rs18000-cro.html

http://www.business-standard.com/article/markets/uti-asset-management-company-fairly-ready-for-ipo-says-md-leo-puri-117071301103_1.html

http://www.business-standard.com/article/markets/uti-asset-management-company-fairly-ready-for-ipo-says-md-leo-puri-117071301103_1.html

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How Big Can Fintech Companies Get in Terms of Market Cap?

We are valuing other financial companies – comprising exchanges, rating agencies and fintechs – at US$60bn by F2027. The key piece within this is fintech, and we discuss our valuation methodology below.

We look at the potential size of digital payment transactions and assume that they will have a 20% share of the system by F2027, up from 8% now. That would imply annual transactions worth around US$240bn through these platforms.

Some of the other global payment platforms trade at 13-15% of total payment volumes. Applying that to the potential payment throughput in India would imply a potential market cap of US$20-60bn for these payment platforms. It is likely that the bulk of this will be dominated by very few players, with more consolidation in this space. The key here will be monetization – will these compa-nies start charging for payments or will they keep them free to attract customers and use the data to offer other products like wealth management, lending services, etcetera.

Exhibit 143:Fintech: Valuation Scenarios

Payments / Fintechs Base Bull Bear

Digital Transactions 1,208

% Share in Digital Transactions 20% 25% 15%

MCAP / Transactions 0.15X 0.20X 0.10X

MCAP (FY27E)

INR Bn 2,657 4,428 1,328

USD Bn 36 60 18

Source: Morgan Stanley Research (E) estimates

If we look at the spectrum of fintech companies in India, they straddle multiple parts of the financial services industry. There are multiple players in payments, lending, wealth management, loan origination, and insurance. How could they be valued given the nascent nature of these businesses?

Most of these fintechs are operating in areas where banks and non-bank lenders are already operating, and in that sense they will be a part of the market sizing analysis we have conducted above. Hence, we are not trying to ascribe a potential value to them separately.

The one area which is not being captured in the earlier areas is market share gained by independent digital payment platforms like Paytm. Hence, we have ascribed a potential value to these businesses.

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Repeated trust and f Aadhaar und Aad-ands and sed.

for strong s in recent ion along ealthcare, ect could ple to its se people t.

n or crisis ents and

ned initia-

th of this ons in the ce and/or

a's e-com-ent inter-

MRisks to our StoryWe have high confidence in India's digitization theme evolving over the next ten years with significant benefits for investors. Nonetheless, this investment theme does carry risks. These include:

Political outcome of 2019 elections - A change in government could pose the risk of change in agenda and unwinding of current pol-icies, developments that could hamper growth and buck our assump-tions about rising equity savings. The current government is a major proponent of India's digital economy and is giving regulatory and administrative impetus to the Aadhaar platform. There is no guar-antee that such an impetus may continue if there is a change in gov-ernment.

Risk of Aadhaar being subsumed by the ongoing debate around privacy - A key driver of the success of digitization is the seamless use of Aadhaar in both financial and nonfinancial transactions. Hence, any legal hurdles that might severely limit usage of Aadhaar could hinder the digitization process. India's Supreme Court recently judged that privacy is a fundamental right for Indian citizens. Whether Aadhaar infringes privacy or not is an ongoing debate.

Smooth transition to GST - The general expectation is that, over a period of time, tax compliance will rise significantly, thereby resulting in a stronger fiscal position. If GST implementation were not to be as expected, then the resultant expected benefits of improved credit access for MSMEs and for economic growth might not unfold as we envision. We should also not lose sight of the near-

Threats to cybersecurity as more data goes online - cyberattacks and newsflow of data theft could rattle userslow growth in digital transactions. While the architects oevince great confidence in the security arrangements arohaar, the security of associated platforms is in diverse hcould pose a problem to the system at large if compromi

India’s macro climate - Although India is positioned well economic growth (given demographics and policy initiativeyears), such growth is contingent upon successful executseveral fronts, including infrastructure, job generation, hand education, for example. Any impediments in this respadversely affect our outlook. India will add significant peowork force in the coming decade and generating jobs to theis crucial to the economic, social and political environmen

Deep global recession or crisis - A deep global recessiocould negatively impact capital flows, currency, investmthereby hurt the progress of many of the above-mentiotives.

E-commerce growth risks: Funding is key to the growsector, which in turn depends on technology stock valuatiUS. So adverse developments in either the global VC/PE spaa sharp correction in technology stocks could affect Indimerce growth story. Also as the sector gains size, governmvention may increase in the form of regulations or taxes.

78

term risks that GST brings to the fore, which is that MSME profita-bility suffers, leading to job losses and an overall slowdown in economic activity.

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MIndividual Stock SectionTheme 1: Indian Financials
l Bajaj Finance l Edelweiss Financial Services Ltd.l HDFC Bank l ICICI Prudential Life Insurancel Kotak Mahindra Bankl LIC Housing Financel Mahindra & Mahindra Financial Services

Theme 2: Indian Consumption

l Asian Paintsl Eicher Motorsl ITCl MakeMyTrip

Theme 3: Global Stocks With Indian Optionality

l Alibabal Amazonl DBSl Naspers l Softbank l TransUnion l Visa / Mastercard


l Maruti Suzukil Ultratech Cement

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80

This is a pure play on consumer and SME financing growth given it has the highest exposure to these seg-ments as a share of the loan book. It should benefit more from higher consumer / SME data given high existing use of analytics.

Bajaj is the most geared, among our financials coverage, to the strong growth potential driven by digitization in consumer and SME lending.

Consumer and SME loans, which we forecast will be the major driver of loan growth over the next ten years, constitute >90% of the loan book of Bajaj Finance (BAF). BAF offers a diverse range of products across both these segments. Continued focus on these segments has helped it deliver a strong 33% EPS CAGR, with an average ROE of 21%, FY2014-17.

We expect the following factors to drive sustained strong perform-ance at BAF, FY2017-27:

1. BAF's expertise and strong positioning in discretionary con-sumption finance, which we expect to accelerate meaningfully over the next ten years. BAF has been at the forefront of tapping the financing opportunity in discretionary consumption. It finances >20% of all consumer durables (white goods) sales in India. It has also been consistently and aggressively increasing its footprint across channels (both physical and digital). In addition, it has been adding products. This has driven strong growth in customer acquisi-tion as well as repeat business with existing customers.

2. Ability to deliver product innovation and retain customers through cross sell and customer satisfaction. Rising share and incomes of millennials should result in demand for newer products and services. In addition to consumer durables, BAF has been innova-tive in identifying opportunities and adding verticals, such as digital financing (mobile phones and so on); lifestyle financing (furniture and so on); and life-care financing (dental care, hair restoration, laser eye treatment, stem cell preservation and so on). Product innova-tions include pre-approving customers, loyalty cards (called Existing Member Identification i.e. EMI cards), and credit lines for both SMEs and consumers. BAF has also expanded its product suite by adding payments via its tie-up with MobiKwik.

Bajaj Finance 3. BAF's strong technology, digital orientation, and risk manage-ment. In our view, BAF has demonstrated great operational rigour in delivering a high volume of small-ticket loans, as well as credit risk management (working with a large inflow of new-to-credit cus-tomers). We believe that, given BAF's early adoption, relative to peers, and hence greater familiarity with, for example, a scorecard-based approach to credit underwriting, and credit bureau data-based analytics, it should benefit significantly from the coming data democ-ratization being fostered by policies such as GST and RERA.

India's multiyear discretionary consumption growth story, driven by millennials, is one of the core drivers of our expecta-tion for BAF to excel amid digitization. We believe that the com-pany can sustain high growth (around 30%) and ROE (around 20%) for the next three to five years. India's retail credit penetration is much lower than that of other Asian emerging countries and the developed world. We believe this can increase significantly over the next ten years, given the growing Millennial population, alone (i.e., the sheer proportion of the population entering the work force). In our view, this augurs very well for consumer financiers such as BAF that have made significant investments in this business, possesses a pan-India network, experience, and which have spent significant effort in developing risk management systems and service delivery channels.

Where we could be wrong: An underlying assumption is that BAF will be able to maintain asset quality and profitability. If this were not to happen and if BAF were to see meaningful compression in profita-bility with or without an increase in NPLs, valuation multiples could come under significant pressure from current premium levels.

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Exhibit 144:BAF Screens Higher on ROE Profile Than Retail Private Banks...

21.7

%

17.9

%

13.8

% 20.9

%

18.4

%

14.1

% 21.6

%

19.4

%

14.7

%

25.0

%

20.2

%

16.2

%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

BAF HDBK Kotak

FY17 FY18e FY19e FY20eROE (%)

Source: Company data, Morgan Stanley Research (e) estimates

Exhibit 145:… and its Share of Consumer Loans + SME in Loan Book (>90%) Is Much Higher Than That of Retail Private Banks, Which Helps Explain its Pre-mium Relative Valuations

BAF

Kotak

HDBK

15

17

19

21

23

25

27

29

31

33

35

40% 60% 80% 100%

1Y

Fw

d P

E

Share of retail loans (F1Q18)

Size of bubble indicates Consumer+SME book (F1Q18)

Source: Company data, Morgan Stanley Research. Morgan Stanley Research (e) estimates

PAPER

d.

tured scale. rela-pared credit ation-ereby come,

ecast t ten atory ment th of

next nities s are e for-apital struc-

BLUEM

This is a diversified financial with exposure to many of the fastest-growing and highly profitable financial ser-vices businesses - affordable housing and SME lending, wealth and asset management, niche spaces like dis-tressed credit.

Edelweiss Financial Services LtExhibit 146:We Believe that Exposure to Diverse and Fast-growing Profit Pools (With Less Competition, and Hence High ROE) Position Edelweiss for Significant Profit Growth Over the Next Decade

Structured Collateralised

Credit 15%

Wholesale Mortgage

22%

Retail Mortgage

6%

LAS, SME & Agri 9%

Distressed Credit 12%

Wealth & Asset

Management 10%

Capital Markets

15%

BMU, Corporate and Others

10%

PAT Mix ex-insurance - FY17 (Pre MI)

Credit Business

Franchise Business


As a diversified financial services competitor, with a good combina-tion of credit and capital-light businesses, Edelweiss is positioned well to benefit from the strong growth we expect in financial ser-vices, FY2017-27. In FY17, its credit and other businesses contributed 75% of group profits, and non-credit businesses (capital market linked) contributed 25%.

Its distinctive advantage is that its key businesses are in segments that are among the fastest-growing parts of the financial services industry, but which face relatively less competition from banks, implying good pricing power (i.e., profitability potential):

1. Affordable housing finance: Edelweiss's focus is on small- to medium-ticket self-employed housing loans, which is not a signifi-cant focus of banks. Hence, unlike traditional "prime" mortgages, this product has pricing power and hence greater profitability potential. Over the next ten years, government initiatives for affordable housing should drive a strong profit CAGR for Edelweiss, in our view.

2. MSME credit: Edelweiss provides small-ticket loans to MSMEs, a significant proportion of which are disbursed on the basis of surro-gate means of underwriting (e.g., observing footfalls, talking to the borrowers' vendors and suppliers), owing to a lack of documentary evidence of income. GST implementation should result in higher con-sumer credit data availability, and hence significantly higher vol-umes. While yields will likely move lower, credit costs should also move lower, and we expect leverage to improve over time.

3. Distressed credit: Edelweiss ARC is India's largest asset recon-struction company by managed assets, and it has ~50% market share in managed assets as of FY17. Capital deployment / ability to mobilize capital via partners and strategic investors will, we believe, be a key differentiating factor among ARCs as the industry's focus has moved towards resolution and potential complete takeover of stressed assets from bank balance sheets. In our view, Edelweiss is positioned

4. Structured credit solutions: Like distressed credit, struccollateralized credit is also a niche business with few players ofEdelweiss's key strength in this area is its investment bankingtionships, which enable it to better assess and take risk, as comwith peers who do not focus on this arena. As in its distressed business, Edelweiss has indicated that it can use its various relships to scale this business via the off-balance-sheet route, thlimiting balance sheet risk and deriving management fee inrather than growing these assets on the balance sheet.

5. Capital markets: As discussed earlier in the report, we forvery strong equity flows and trading turnover over the nexyears. Bond markets should benefit from positive regulchanges. We expect Edelweiss's traditional broking and investbanking businesses to derive significant benefit from the growthis segment.

6. Wealth management: Strong economic growth over thedecade should result in significant wealth creation and opportufor wealth managers. Domestic players such as Edelweisramping up significantly, especially in the wake of exits by someign competitors. Synergies are high with other businesses (cmarkets, asset management, insurance, distressed assets and tured credit).

82

well, supported by partners such as CDPQ (a Canadian Pension Fund) and by its high net worth individual relationships in its wealth man-agement, alternatives and capital markets businesses.

Where we could be wrong: Our thesis won't play out if Edelweiss sees a sharp rise in NPLs with or without a major prolonged decline in equity markets and sentiment.

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HDFC Bank Exhibit 147:HDFC Bank: Balance Sheet Per Employee Is Rising Meaningfully

0

25

50

75

100

125

0

20,000

40,000

60,000

80,000

100,000

F2001

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Employees (Number) Assets / Employee (Rs Mn), RS


Play on acceleration in retail and MSME loan growth

HDFC Bank is clearly one of the biggest beneficiaries of the con-sumer and MSME lending boom. HDFC Bank has a number of advan-tages over the rest of the banking system:

1. Cleaner balance sheet relative to many other lenders. This has allowed management to focus on growth areas and benefit from the market share shift away from corporate lenders. Even in the corpo-rate lending space, the bank is seeing solid growth as it develops stronger relationships with large corporates.

2. HDFC's low funding cost allows it to price aggressively and still make strong returns. The bank has sought to maintain a strong liability base, with a high proportion of funding coming from current accounts and savings accounts. This has kept its funding cost amongst the lowest in India, allowing it to achieve reasonably high spreads, even on the high-quality assets.

On top of this, the bank has been aggressively rolling out its digital strategy, helping it to reduce its cost of operations fairly significantly. For instance, since September 2016, the bank has grown its balance sheet by >20%, while its employee base has contracted from ~95,000 to ~85,000 during this period.

As we mentioned in the market cap section, we would expect some pressure on revenue yields for banks, as technology is likely to stoke competition. But the compensating factor would be lower operating costs as a percentage of assets. And HDFC Bank is seeing early signs of such improvement. We expect its cost efficiencies to improve fur-ther, which should help keep ROA fairly stable.

Exhibit 148:HDFC Bank: We Expect Market Share in Bank Loans to More Than Double Over the Next Decade

0.8

%

0.9

%

1.1

%

1.7

%

2.2

%

2.3

%

2.4

%

2.5

%

2.8

%

3.6

%

3.8

%

3.9

%

4.1

%

4.4

%

4.7

%

5.2

%

6.2

%

7.3

%

16.4

%

0.0%

3.0%

6.0%

9.0%

12.0%

15.0%

18.0%

F2000

F2001

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F2027E

CAGR of

20%


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Exhibit 149:HDFC Bank: P/E Multiple Is High Versus History

10.0

15.0

20.0

25.0

30.0

35.0

Se

p-0

7

Mar-

08

Se

p-0

8

Mar-

09

Se

p-0

9

Mar-

10

Se

p-1

0

Mar-

11

Se

p-1

1

Mar-

12

Se

p-1

2

Mar-

13

Se

p-1

3

Mar-

14

Se

p-1

4

Mar-

15

Se

p-1

5

Mar-

16

Se

p-1

6

Mar-

17

Se

p-1

7

HDBK HDBK Core

Mean + 1SD

Mean

Mean - 1SD

HDFC Bank core adjusts for its stake in HDB Financial. Source: Company data, Morgan Stanley Research

The bank is also using data very effectively in growing its loan book. For instance, almost 30% of its unsecured loan book is being offered through its "loan in 10 seconds" product. The bank has set up a back end that can rapidly process loan applications, access its customer data, retrieve and assess credit bureau data, and then quickly make the loan. This is one of the factors that is helping it grow its loan vol-umes at a fast pace.

We believe that as MSME lending picks up, supported by data mining, HDFC Bank will be amongst the major beneficiaries. It should be able to process this data more quickly than many other banks and make faster lending decisions, given its digital infrastructure. This, along with funding cost advantage, should help significantly boost its growth. We expect HDFC Bank's loan growth to average about 20% over the next decade (as compared with ~27% over the past 10 years).

Strong growth coupled with stable ROA is likely to drive strong earn-ings. Moreover, HDFC Bank's nonbanking subsidiary - HDB Financial - is also performing well. It should also derive a substantial benefit from a pickup in consumer and MSME loans - the key focus areas for HDB Financial.

HDFC Bank's valuations as compared with its history are elevated and will likely contract over the next ten years. But, given the likely strength of compounding, we expect the stock to perform well.

Where we could be wrong: a) greater than expected competition in retail on pricing; b) slower than expected CASA growth; c) higher than expected competition in processing and other fees.

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ICICI Prudential Life InsuranceExhibit 150:We Expect ICICI Pru Life's APE Market Share to Improve ~6ppts Over the Next Decade

8.8

%

10.1

%

9.9

% 1

2.7

%

10.9

%

9.3

%

7.3

%

5.9

%

7.0

%

7.2

%

11.3

%

11.3

%

12.0

%

18.0

%

0.0%

4.0%

8.0%

12.0%

16.0%

20.0%

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F2027E

ICICI Pru Life: APE Market Share (%)

Source: IRDA, Morgan Stanley Research estimates

Play on strong growth in equity savings and under insurance

India's life insurance segment, in our view, is likely to be a key beneficiary of: a) accelerating GDP growth, b) formalization of sav-ings and increasing share of financial savings within that, and c) accel-erating protection growth. Large bank-backed insurers are well placed to capitalize on such developments. They have better distri-bution, strong operating metrics (persistency, costs), and are focused on various technology initiatives. ICICI Prudential Life is one such play.

We forecast a 17% CAGR for premium growth and a 6ppt APE market share rise, to 18% in ten years: ICICI Prudential is a leading unit-linked insurance product (ULIP) competitor, sup-ported by a portfolio of relatively competitive products. While the regulator has significantly capped expenses under ULIPs, we note that ULIP products at ICICI Prudential have expense charges that are even lower than the requirement, and this has helped its ULIPs stand out relative to the competition, and even versus mutual funds over a longer-term investment horizon. In our view, this will help ICICI capi-talize on the coming growth in equity savings that we expect.

We forecast a 25% VNB CAGR, 2017-27, much higher than growth in premiums, given significant improvement in profitability. We highlight two key reasons:

a) increasing protection mix: Selling protection in India has been tough historically. Lack of awareness and also limited focus by insur-ance (10 years back) are the key reasons, and this has meant that life protection penetration in India is generally quite poor versus levels in more developed markets. However, awareness levels are now changing (as seen in a pickup in protection premiums). Moreover, insurers are working on a number of technology initiatives to under-write and cross-sell better. This should help drive protection mix higher.

Exhibit 151:Cost and Persistency Ratios - Strong Improvement Over Past five Years

50%

60%

70%

80%

90%

10%

12%

14%

16%

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

Adjusted Opex Ratio %) 13M Persistency Ratio (%), RS

Source: Company data, Morgan Stanley Research.

Exhibit 152:IPru Life: P/EV Versus ROEV Forecast

15.0%

15.5%

16.0%

16.5%

17.0%

17.5%

18.0%

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Sep

-16

Mar-

17

Sep

-17

Mar-

18

Sep

-18

Mar-

19

Sep

-19

Mar-

20

Sep

-20

Mar-

21

Sep

-21

Mar-

22

1Y Forward P/EV (Headline) ROEV (%), RS

Source: Thomson Reuters, company data, Morgan Stanley Research estimates

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86

b) better operating leverage. One of the key enablers here would be technology. To start with, ICICI prudential has used technology well to reduce cost and improve persistency ratios. Over the next ten years, we believe technology usage to cross-sell will play a greater role in insurance sales, particularly for ICICI Prudential, as it is very focused on protection and low-cost ULIPs. Traditional products, on the other hand, are relatively complex, and hence technology will play a relatively lower role in such arenas, in our view. We believe that ICICI Pru is prudently focused on smart initiatives, such as a) cross-selling/upselling customers at various touch points using analytics, b) developing innovative digital marketing tools, and c) integrating digital platforms with distributors, among other efforts.

Although ICICI Pru valuations are not cheap, we nonetheless believe that the combination of the above two factors can drive sustainable RoEV of ~17-18% over next ten years. This implies strong returns, even as valuations move lower.

Where we could be wrong: a) significant margin compression in the protection business; b) an aggressive move to open architecture by ICICI Bank; and c) potential increase in tax rates.

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Big beneficiary of acceleration in consumer/MSME loan growth and capital market activities

In our view, among our coverage universe, Kotak Bank will be one of the biggest gainers in the financial services boom that we expect. Kotak kept itself away from lending to riskier segments and has one of the industry's strongest balance sheets (with strong capital and low impaired loans) in the current cycle. More-over, the merger integration process with erstwhile ING Vysya bank is now complete, and the bank can now focus on growth. This, coupled with a strong management team, should help improve loan/revenue growth sharply, as well as boost RoE.

Kotak Mahindra Bank1. Sound industry play, given presence across financials value chain: Kotak has presence across the entire value chain, with 100% ownership across most business segments. As discussed earlier herein, we expect capital market businesses to do well, given higher formalization of savings and increasing financial savings within that.

Exhibit 153:Kotak: Present Across the Entire Value Chain

Source: Company presentation

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Exhibit 154:Kotak: We Expect Market Share in Bank Loans to More Than Triple in the Next Three Years

0.2

%

0.2

%

0.3

%

0.4

%

0.4

%

0.6

%

0.7

%

0.6

%

0.6

%

0.7

%

0.9

%

0.9

%

0.9

%

1.0

%

1.7

%

1.8

%

5.7

%

0.0%

1.5%

3.0%

4.5%

6.0%

7.5%

F2002

F2003

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F2027E

25%

CAGR


We expect bank RoA to improve to 2.0% from 1.7% currently, driven by higher operating leverage. In our view, the CAGR of costs at Kotak Bank over the next 10 years is unlikely to be higher than 16-18%, much lower than the revenue CAGR of ~23% (we expect fee income growth to be lower than NII growth). Slower cost growth should be driven by a declining pace/size of branch expansion, as cus-tomer acquisition and maintenance turns digital. For instance, Kotak has launched 811, a paperless and digital way to open bank accounts within five minutes. More importantly, the acquisition cost via this approach is ~90% less than the previous manual method.

Banking Businesses: We expect strong 28% growth in earnings over the next 10 years, driven by:

Strong ~25% loan growth CAGR, 2017-27, leading to market share of 5.7% (versus 1.8% currently). Kotak's loan book has one of the highest contributions from the SME and consumer segments. As discussed earlier in this report, we expect system growth in con-sumer and MSME loans to be around 17% each, respectively, over the next ten years. For Kotak, we believe growth should be higher, given its continued strong focus and relative expertise in this segment (also helped by its ING Vysya acquisition).

Exhibit 155:Market Share in Various Capital Market Segments

2.3%

5.0% 4.5%

6.2%

0.0%

1.5%

3.0%

4.5%

6.0%

7.5%

Life Insurance AMC

F2017 F2027E

20% CAGR

23% CAGR

Source: Company data, IRDA, SEBI, Morgan Stanley Research estimates

Capital market earnings will be strong as well; we expect a ~20-23% earnings CAGR over the next 10 years. As discussed ear-lier, our macro team expects equity savings of US$420bn–US$525bn over the next ten years in India, versus the respective US$60bn and US$120bn that households and foreign portfolios invested over the previous ten years. This, coupled with Kotak's relatively low starting point in these segments and strong management, will help it grow faster. We expect bottom-line growth to be higher than top-line growth given the high operating leverage nature of these businesses.

Although Kotak's valuations are not cheap, we believe that strong earnings compounding implies strong returns potential, even as valu-ations move lower.

Where we could be wrong: The key risk to our thesis on Kotak Bank is higher than expected competition on pricing driving down margins and/or weaker than expected loan growth.

Exhibit 156:Kotak (Consol): 1Y Forward P/B

1.0

2.0

3.0

4.0

5.0

Mar-

04

Mar-

05

Mar-

06

Mar-

07

Mar-

08

Mar-

09

Mar-

10

Mar-

11

Mar-

12

Mar-

13

Mar-

14

Mar-

15

Mar-

16

Mar-

17

Mean+1SD

Mean

Mean-1SD

Source: Thomson Reuters, company data, Morgan Stanley Research estimates

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Big beneficiary of strong growth in affordable housing as it is the lowest-cost producer of housing loans; RERA and GST should drive bigger foray into self-employed and developer segments

LICHF is India's second-largest housing finance company (HFC), with a ~9% market share, with among the strongest core mort-gage franchises. Given strong parentage and an AAA rating, LICHF's cost of funds is one of the lowest among HFCs. Further, its cost of operations is lowest among the HFCs. This thus makes LICHF the lowest-cost producer of individual housing loans. Consequently, on prime individual home loans, LICHF's ROE is among the highest.

LIC Housing FinanceExhibit157:Low Starting Point of Non Housing Loans, i.e., Flexibility to Drive Loan Growth and Margins

Individual Home Loans,

83.3%

LAP, LRD & Other Non

Core, 12.9%

Developer Loans, 3.8%

Source: Company data, Morgan Stanley Research. Loan mix as of June 2017.

LICHF has a strong pan-India presence and has traditionally had lower risk preference with among the largest exposures in the salaried housing loan space. LICHF has a geographically diversified loan book covering about 450 key centres across the country. It has among the lowest exposures to non-home-loan products, like loans against property (12.9% of the F1Q18 loan book) and developer loans (3.8%). The salaried segment (having predictable cash flows and greater overall tax compliance) forms 84% of the individual segment (LAP + home loans). Even within the individual segment, the share of loans to government employees is quite high.

Growth in recent years has been sluggish. However, we see a strong case for higher loan growth and taking on more risk, i.e., potentially a better profitability mix, driven by the confluence of GST and RERA:

Historically, LICHF's share in the self-employed segment has been low relative to some of the other fast-growing large HFCs. But this could change as underwriting self-employed borrowers becomes easier with data democratization as fostered by GST implementation. This could open new segments / markets for LICHF, driving higher loan growth. Further, loans to self-employed customers also earn a slightly higher loan spread, although this should progressively move lower with better data availability.

Exhibit 158:LICHF Has the Highest Share of Lower-ticket Home Loans Among Large HFCs, i.e., It Is Positioned Well To Be a Big Beneficiary of a Pickup in Affordable Housing

32.1%

12.7% 8.5% 7.1%

67.9%

87.3% 91.5% 92.9%

0.0%

25.0%

50.0%

75.0%

100.0%

LICHF HDFC PNBHF IHFL

Individual Housing loan more than Rs. 1.5 mn

Individual Housing loan upto Rs. 1.5 mn

Source: Company data, Morgan Stanley Research. Data for FY17.

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90

Among the large HFCs, LICHF should be one of the biggest beneficia-ries of strong growth in the affordable housing segment. With ~32% of individual loans having a ticket size of <Rs1.5mn, LICHF has a stronger franchise in this segment than most other large HFCs, for which the share of such loans is much lower (under 15%).

Historically, LICHF, among the large HFCs, has had the lowest expo-sure to the developer segment, given the information asymmetry and specialized skills required for underwriting, monitoring and recovery. RERA implementation could catalyze higher exposure, which could drive both higher loan growth and NIM. RERA is expected to bring in more transparency and accountability in transactions and end-use of funds by developers. This should make it easier to underwrite devel-oper loans. Further, developers' borrowing needs are also likely to increase under RERA. While loan yields should move much lower, the addressable market should expand significantly. This should be an ideal opportunity for LICHF to increase the share of developer loans and drive both higher loan growth and NIM.

Exhibit 159:Starting Point of Valuation Is Attractive Relative to Most HFCs

4.0 3.8

3.7

2.6

2.2 2.2 1.9

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

CanFinHomes

PNBHF IHFL Repco Home GIC Housing LICHF DHFL

Price to Book Value (x) - FY19e

Source: Thomson Reuters, company data, Morgan Stanley Research (e) estimates. Note: Bloomberg consensus estimates are used for Canfin Homes, GIC Housing, DHFL, Repco.

Driven by the above reasons, we expect a strong housing loan CAGR (around 16%) over the next ten years, with potentially even a stronger non-housing loan CAGR, which could help improve / sustain NIM in the wake of NIM competition in the core housing loan business.

Where we could be wrong: LICHF fails to accelerate growth in home loans and loses market share in housing loans. It also does not increase the share of non-housing loans thereby seeing a decline in net interest margins.

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This is a pure play on growth in rural financing opportu-nities given its rural focus and large network. Digitiza-tion should enable it to serve its customers better and reduce its cost of operations.

Mahindra & Mahindra Financial Services

Exhibit 160:Given its Rural Focus, Expertise, and Strong and Growing Network, MMFS Is a Pure Play on Rural Lending Opportunities and Should Grow Assets at 17-20% CAGR Over the Next Decade, We Expect

133,907

182,264

241,366 286,007

319,409

~600,000

0

80,000

160,000

240,000

320,000

400,000

480,000

560,000

640,000

FY2013 FY2014 FY2015 FY2016 FY2017 PotentialOpportunity

MMFS Presence in Villages

Source: Company data, Morgan Stanley Research.

As penetration and acceptance of digital modes of payments rises in rural India, it should boost financial inclusion and lead to better and more economical servicing of the 'mass' rural cus-tomer. High preference for, and prevalence of, cash in transactions; low proximity to customers, i.e., population spread over large areas; and consequently high costs of customer engagement, have histori-cally been the key impediments in servicing rural customers in both credit and liabilities.

MMFS is the pure play in this space. While most banks do have a rural presence, MMFS' businesses (vehicle finance, housing finance and insurance broking) are focused solely on rural and semi-urban customers. Further, MMFS' key customer segment is 'new-to-credit' borrowers, which is essentially high-risk / high-yielding collateralized loans to 'mass' rural customers, not the preferred segment of banks. Of the ~600,000 villages in India, MMFS has a presence in ~320,000.

Over the longer term, some of the potential benefits for MMFS from increasing digitization that are not priced in today, in our view are:

Exhibit 161:Given High Operating Costs in the Business, Sensitivity of Profitability to Reduction in Operating Costs Is HighAvg F08-17 Cost to Assets 3.4%

Avg F08-17 ROA 2.8%

% Reduction in underlying

cost of operations ROA (bp) Profits (%) ROE (%pt)

5% 11 4% 0.9%

10% 22 8% 1.8%

15% 34 12% 2.7%

20% 45 16% 3.6%

25% 56 20% 4.5%

Impact on

Source: Company data, Morgan Stanley Research (e) estimatesa) Digital payments, which should help drive a lower cost of operations and better cash management for MMFS. >50% of MMFS' loan installment collections are in cash, and many times these are multiple small value collections requiring repeat visits to the cus-tomers, creating a high cost of operations, cash handling charges and treasury costs. As the share of digital payments increase in the rural ecosystem, the possibilities for MMFS to reduce costs are substantial – i.e., collect multiple installments digitally, use the "ask money" fea-ture in UPI to both remind customers and pull funds, manage trea-sury efficiently, and so on. Digital records of earnings of customers over time, could also help underwrite and monitor them better.

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b) Faster, better and customised credit delivery to existing cus-tomers, enabling better customer retention. To existing, pre-ap-proved and digitally savvy customers, MMFS could consider disbursing small-ticket instant loans digitally.

c) GST should help open opportunities in the rural MSME financing space. MMFS has been foraying into vendor financing and MSME financing (including the supply chain of M&M). Better transac-tion data, owing to GST , should help assess borrowers better and deliver higher and faster credit.

d) Cheaper deposit funding. MMFS is one of the few NBFCs with a deposit taking license and probably the only NBFC offering a com-pletely online deposit product. Higher online adoption among users could help MMFS garner cheaper deposits (no brokerage and lower admin costs).

Rural housing finance – A large opportunity. Rural housing finance in India is <10% of overall housing finance, and MMFS' subsidiary is one of the few players in this space. PMAY (Rural) plans to construct 30mn homes in rural areas by 2022. Any meaningful progress in this direction could result in a significant growth opportunity (the subsid-iary is already growing the loan book by 50% annually).

Potential to launch more financial products in rural India. MMFS has been assessing various opportunities - in addition to credit and insurance broking, it has also set up an asset management subsidiary.

Where we could be wrong: A deep cyclical rural slowdown with an associated rise in NPLs is the key risk to MMFS; this could also be a spanner in the works for digital initiatives and so on.

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Asian Paints is a key beneficiary of increasing dispos-able incomes and strong growth in property demand. It has a standout business model and is set to benefit from an improvement in urban consumption growth.

Euromonitor estimates the Indian decorative paint industry market size at Rs262bn in 2015, with 10% revenue CAGR over 2007-16. The strong growth was driven by a combination of factors: new construc-tion housing demand, rising urbanization, an increasing number of single-family homes, and a strong repainting demand cycle. Indeed, over the past two decades, paint industry volume growth has also shown a strong correlation with real GDP growth (1.5-2.0 times GDP growth). Our channel checks with dealers and industry experts sug-gest that consumers in India increasingly perceive paint as expendi-ture for home maintenance rather than décor.

Our analysis of consumption trends for decorative paints across geo-graphies indicates that the per capita consumption in India is US$3 per annum, low compared with the US at US$26 but broadly similar to China's US$3.4. However, in terms of share of wallet spend, we note that India's consumption trend is higher than that of peers. We attribute this to the weather conditions in India and the reduced length of the repainting cycle in India. As per our channel checks, the cycle has reduced to 4-5 years currently from 7-8 years in 2006.

Our India property team expects property industry demand to rise at a 14% CAGR, 2015-20, and an 18% CAGR, 2021-25.

Asian PaintsWe believe that strong new construction growth trends with a shrinking repainting cycle augur well for the decoratindustry in India. With 55% market share (in value terms) innized paints industry in India, we believe Asian Paints is tioned to benefit from this growth. Repainting demand co80% of APNT's decorative paint segment revenues currenview, placing the company on a multi-year trajectory volume offtake and, consequently, high visibility on earning

APNT also has advantages on several fronts, in our view, susumer mindshare, dealer penetration, and supply chainstrength. An acceleration in urban discretionary congrowth given visible green-shoots of an urban consumptionwould benefit the home improvement category and APNTular. APNT is one of our top picks in our consumer discretioerage and has performed well, with double-digit domestgrowth over the past three years. This compares favorably wother discretionary consumer companies that reporteddomestic volume growth over the past 2-3 years and fperiod challenging from a demand perspective.

Where we could be wrong: Given the strong correlatioindustry volume growth to real GDP growth, any slowdownomic activity can impact industry growth trends. In the ecompetitive intensity increases in the decorative paint segsee risks to APNT’s market share and subsequently our volume growth estimates. Operating margins for the busbe at risk in the event of a sharp increase in input costs.


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Eicher is a key beneficiary of higher discretionary spending. With rising disposable incomes in India, we expect a strong upgrade cycle for two wheelers in India and we expect Royal Enfield’s (RE) cruiser bikes seg-ment to be a key beneficiary of this trend.

We believe that strong demand is also likely to lead to greater investor confidence in Eicher's ability to sustain earnings growth and thus support long-term cash flows.

a) RE is the only aspirational yet affordable brand in India's autos segment, and we expect it to be a key beneficiary of premiumisa-tion: Eicher, with its Royal Enfield brand, has a distinctive position in India. The brand's aspirational quality helps Eicher stand out among peers, command a loyal customer base, garner strong pricing power, and keep sales promotion spending low. The brand's affordable quality ensures RE is best placed to capitalize from upgrades during replacement purchasing.

b) VECV should see margins improve as market share rises: VE Commercial Vehicles Ltd. (VECV) is a joint venture between Volvo and Eicher. We believe growing volumes and the consequent oper-ating leverage will lead to margin expansion for VECV.

Eicher Motorsc) Exports to be a growth driver: Aiming to capitalizBritish heritage, designed in the UK, made in India: Eicheexports of its RE brand to be a key focus. The company hateam in the UK to make RE a "disruptive force in global motIt plans to develop and design models in the UK, keepingaudience in mind, and offer customers a heritage brand at able price point. It also seeks to expand the 250-750cc segbally by focusing mainly on 500-750cc motorcycles. WeEicher will export around 1,900 units per month of the REF19, versus Bajaj Auto, which exports a combined 18,000 PAvengers per month. A faster-than-expected pickup coulre-rate the company, in our view, as visibility on export tactivity is currently low.

Where we could be wrong:

"Pull brand" turns into a "push brand": RE is the most profitpany now in two-wheelers, and it has attracted competitocompetitor has yet succeeded as has RE. Stronger-thancompetition could be a key downside risk.

Stronger-than-expected competition: Any strong new entracruiser bike segment in India at price points similar to thatcan take away some market share from Royal Enfield.

Any sustained slowdown in commercial vehicles: Also keyout for any signs of sustained sluggish CV demand in Indi

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GST offers the opportunity of structural market share gains for ITC from illicit cigarettes; valuations and earn-ings expectations are relatively benign due to risks from continuing adverse policy action

We have long believed that the only way to counter the illicit ciga-rette segment in India is a relatively benign tax environment (with price hikes only marginally ahead of consumer inflation). However, the implementation of the GST provides the government an oppor-tunity to improve tax compliance based on analysis of data collected from the GST network.

We estimate >70% of the illicit cigarettes sold in India are domesti-cally manufactured but duty is evaded. In the absence of a digital trail of transactions, hitherto, it was difficult for government agencies to establish or monitor tax evasion in the manufacturing value chain. However, the introduction of the GST may present an opportunity for the government to control tax evasion. To be clear, this opportu-nity is captured only in our bull case scenario.

Our channel checks suggest that certain raw materials used in the manufacture of cigarettes like filters and specialized paper are sourced from industries that are relatively consolidated, organized and likely tax compliant. Data collected from these industries may help ascertain the balance between taxes collected on input mate-rials and manufactured goods for the industry. There may be an opportunity for the government to track any gap between cigarettes manufactured and duty paid cigarettes sold in India.

ITCIn addition, in a rational tax environment, we compute that rette profit pool could increase nearly 5x over the next 10 yfew established categories within Indian consumption offeof growth potential with strong earnings visibility. Also, a the Indian duty paid bidi industry (~365bn sticks p.a. achannel checks), is declining ~2% p.a. As observed from oWise survey, the daily consumption frequency of bidi stwice that of core cigarette consumers. We estimate that eof the bidi volumes translate to cigarette volumes, the indgain an incremental 3-ppt growth p.a. from this transition also interesting to note that the total bidi industry (includganized) is much larger, producing 750bn-1tn sticks p.a. Heroom for growth could be higher.

Historically, a valuation re-rating/de-rating for ITC is linkbility of cigarette volume growth. The latest cigarette polwhich implies a 11-21% increase in tax for cigarettes versF2017, in our view will impact near-term volume growth ations multiples for the stock.

Where we could be wrong: Any incremental adverse gopolicy action (tax, packaging, a loose cigarette ban) will purette volume growth estimates at risk. An increase in awarshift to reduced-risk products (RRP) in tobacco consumsmokers increasingly look for alternatives to combustible cmay impact long-term valuations on the stock. However,out that affordability (relative to other global markets) arestrictive government policies on investments in tobaccmay prove to be insurmountable hurdles for global player


next decade.

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our esti-21. Within further as he hotels, ecifically, inant por-t the OTA 0%+ over

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Dominant OTA platform and direct beneficiary of rising internet penetration and acceleration in consumption expenditure over the next decade

MMYT is the dominant online travel agent (OTA) in India, with a market share of greater than 56% within OTAs in India. We believe MMYT should be a direct beneficiary of rising digitization and an acceleration in consumption expenditure over the next decade. With an increase in online penetration and improved market share, we expect sales and marketing spend to rationalize and the company should achieve profitability by FY20 (2019).

Online penetration within the domestic air ticketing segment has already crossed 50%, and we expect a similar trend to play out within domestic hotels in India. We expect overall online penetration to increase from 20% (in 2015) to 35% by 2021 (largely led by the domestic hotels segment) and dominant OTAs like MMYT should gain further share, taking their total market share to 70%+ by 2021. Secondly, the overall travel trends in India (the total number of domestic trips) is strongly correlated to nominal GDP growth in India. Further we expect consumption expenditure to increase at a faster clip over the next decade (relative to the last decade), which bodes well for discretionary spend items like travel over the coming years.

Addressable market opportunity is huge for the OTAs: We esti-mate the addressable market to increase from US$34bn in 2015 to US$67bn by 2021. This implies a CAGR of over 12% in the overall market.

MakeMyTrip OTAs to gain market share: The online penetration onmates is only 20%, and it can potentially go to 35% by 20the total online market, the share of OTAs could increase they become the dominant online distribution channel for tas in the case of airlines. Within the domestic air segment spMMYT and Ibibo together are well placed to garner a domtion of the total OTA market by 2021, in our view. We expecmarket and MMYT to grow gross bookings at a CAGR of 3the next few years.

Strong bookings/revenue growth and rationalizationand marketing spend to drive profitability: With the buimproving towards the higher-margin Hotels & Packages (ment, we expect net revenue growth to be stronger thabookings over the next few years. With improving blendeenue margins, better economies of scale for the overheadsand lower sales and marketing spend with rising domMMYT platform, we expect the company to turn profitablwith steady state margins improving to 20%+ over the lon

Where we could be wrong: a) Heightened competitivefrom new players for longer could delay the turnaround and drag the company’s cash balance. b) Competition fromdirect channel could increase, such as via airline websitespression in net revenue margins for air and H&P segmeimpact net revenues and profitability adversely. d) The shiftline to online happens more slowly than expected and requicantly larger investments than anticipated. e) Rupee deversus the US dollar impacts the company’s reported net f) There could be a slowdown in the macroeconomic env(leading to slower consumption expenditure on discretionlike travel) or travel shocks due to unforeseen events.

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India is set to be one of the fastest growing car markets in the world and Maruti Suzuki dominates with 80% profit pool share.

The passenger vehicle (PV) industry has been through a long down-cycle and is showing signs of a demand upturn ahead as economic growth and disposable income growth picks up. We also see financing trends being favorable to MSIL - at 80%, on our F2017 esti-mates, the finance penetration was at a ten-year high and banks remain keen to push auto lending further. While Maruti dominates the Indian car market with 80%-plus share of the profit pool, compet-itive intensity in the industry is at a low with several OEMs stressed due to low scale. Consequently we believe Maruti is best placed to capitalize on an upcycle in the Indian PV industry. The stock trades at 25x one year forward P/E on our estimates, which we find reasonable vis-à-vis our estimate of a 20% EPS CAGR for Maruti over F17-20.

Structural reasons to like Suzuki's Indian business: We assume that the Indian market posts a CAGR of 11% in F2017-20 versus 3.3% in F2012-17. We expect Maruti’s growth will be strong not only on an absolute basis but also on a relative basis and hence expect market share wins to be sustained given the strong moats Maruti has built around its business:

Business Moat 1 - Strong product proposition: MSIL offers 15 products, and 7 out of the Top 10 selling models in India are from MSIL (F2017). The product proposition is strengthened by:

Low total cost of ownership: This has been the core of the MSIL brand; it offers low total cost of ownership including best in class resale value.

Maruti SuzukiEconomies of scale: Economies of scale are key to profitaballow a company to extract value at every touch point.

Leading on new technologies: From automated manualsion (AMT), to mild hybrids to compressed natural gas (CNings, the company has been launching technologies consumers

Business Moat 2 – Distribution, more than double thnearest competitor: Distribution is a key strength for MS2,000-plus sales points – more than double the numbnearest competitor. Building this vast distribution is difficuplayers but it is critical for growth as car growth is mainfrom outside the top ten cities. In addition, the company is uits customer reach via new formats like Nexa and now Ar

Where we could be wrong:

The Indian car recovery remains patchy: We assume that market posts an 11% F17-20 CAGR versus a 3.3% CAGR oveslower-than-expected pace of economic recovery coulddown-cycle to last longer than anticipated.

Competition setting up a Tesla-like Giga factory in India: Sckey for success in EVs. Sizable EV investment by an OEM coerate the pace of EV growth in India and Suzuki could remabecause the company, in our view, will launch in EVs m2023/24.

INR depreciates against JPY: ~11% of MSIL’s costs as a percnet sales are in JPY.


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Ultratech is in a sweet spot amid a strong demand out-look given India’s housing shortage and the government focus on infrastructure and affordable housing and slowing capacity additions

With India’s current housing shortage and the government focus on infrastructure and affordable housing, we believe cement demand will remain strong over the next decade. This is also reflected in India’s cumulative per capita cement consumption at 3 tons (cumula-tive since 1950) versus 8-22 tons for developed nations and leading developing nations. In addition, with consumption-led loan growth including housing loans, home upgrades will further support cement demand. With a consumption-led housing boom and the right execu-tion on infrastructure, India could witness high-single-digit demand growth over the next decade, in our view.

Given our view that timelines to add capacity have expanded in India and the cost of adding capacity has risen, we expect industry funda-mentals to remain attractive for incumbent producers in a strong demand growth environment.

Ultratech is in a sweet spot: Being the largest cement company in India and more importantly with a well-diversified pan-India pres-ence, Ultratech is in a sweet spot in a strong demand environment. In addition, its strong balance sheet and capability to add brownfield capacity, better positions it versus peers from a capacity additions perspective, which will be key to delivering industry-leading volume

Ultratech CementBrand power is a sustainable advantage: Unlike in mosthe world, cement is a quasi-branded product in India as thbrands enjoy a pricing premium. Ultratech is among thbrands, which is a sustainable advantage in our view, partthe housing segment of the market that currently accaround two-thirds of cement demand in India and more ththe company volumes.

Cost focus will further boost the profitability profile: few years, management has focused on initiatives like wrecovery, increased usage of petcoke and alternate fuel ation in lead time, with further additions of grinding units cloend markets. We think that continued focus on these areto cost efficiencies, will further boost the earnings profile

Where we could be wrong: Weaker than expected cemenand higher than expected capacity additions.

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growth.

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Exploring for Synergies

India is one of the important markets for Alibaba to tackle during its global expansion. Alibaba is actively exploring business opportunities in this market, starting with the mobile payment infrastructure (Paytm) and expanding to core e-commerce seg-ments (Snapdeal and Paytm Mall), supported by its in-house mobile browser business (UCWeb).

In 2015 Alibaba first invested in Paytm, one of the largest mobile pay-ment platforms in India, and it has about a 9% shareholding as reported in the latest filing. Alibaba's partner in online payment and eFinance, Ant Financial, is also a shareholder of Paytm, which brings the total shareholding to around 40%. Alibaba and Ant Financial have accumulated rich experience in mobile payment and back-end fintech systems, which could help accelerate the transaction growth of Paytm in India.

In March 2017, Paytm completed the spin-off its e-commerce busi-ness, Paytm Mall. Including the newly issued preferred shares, Ali-baba in total acquired a 36% equity interest in Paytm Mall on a fully-diluted basis, for a total cash consideration of US$177mn. Right after the investment, Paytm launched an updated version of a mobile app that introduced a "Tmall-like" market place, which only includes high-

Alibabaquality sellers "passing strict quality guidelines and qualifiteria". This selection-based e-commerce listing likely learnspositioning of Tmall in China and helps Paytm Mall differenfrom other market place e-commerce platforms in India. wise, all products offered on Paytm Mall will also movePaytm Mall's certified warehouse and shippers, similar to htics are handled on Tmall. Alibaba also invested in Snapdeal2015 and took a minority share of less than 5%.

Besides the core e-commerce and payment initiatives,mobile browser App, UCWeb, has provided an additional towith Indian users. UCWeb has captured about 40% markethe mobile browser segment in India as of July 2017, accStatCounter. And UCWeb's mobile news content product,Feeds, has reached 100mn active users in India and IndonMarch 2017, according to Alibaba.

Where we could be wrong: India is a more complicated maChina, and Alibaba has no operational experience in the mresults of Alibaba's initiatives will be affected by product locstrategy execution and various other factors, some of whiout of the company's control.

Morgan Stanley is acting as financial advisor to Cainiao Smart Logistics Network Limited ("Cainiao") in relation to the proposed acof an additional stake in Cainiao by Alibaba Group Holding Limited as announced on September 26, 2017. Cainiao has agreed toto Morgan Stanley for its financial advisory services. Please refer to the notes at the end of the report.


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Making giant strides into the Indian eCommerce market and should be a key beneficiary

Amazon is committed to developing its India business. It has highlighted spend on India numerous times on its quarterly earnings call since 2015, and at a high level, any US$5bn invest-ment, in our view, speaks to commitment and interest.

Focus on customers and selection: It is early, but Amazon is making progress. The company has 160mn products across hundreds of cate-gories currently. On its 4Q15 quarterly earnings call Amazon said that its 4Q India sales were greater than all of 2014, but India is still small relative to Amazon’s total estimated ~US$180bn global GMV (in cal-endar 2016). In 2Q16, Amazon launched Prime in India in over 100 cities, with one- and two-day shipping on hundreds of thousands of products. In 4Q16, Amazon added Prime Video at no additional cost.

AmazonFinally in 1Q17, Amazon announced that it had increased Prime Selec-tion by 75% since it launched and it debuted Inside Edge on Prime Video, the first of 18 Indian Original Series in 2Q17.

Despite Amazon's presence in India still being relatively small, we do believe that India will be a material driver to Amazon’s long-term non-Germany/UK/Japan international retail business, which we model growing at a 38% forward CAGR, driving 17% of forward company-wide retail revenue growth and 56% of international retail revenue growth ( Exhibit 162 ). In all, while we acknowledge Amazon's India business is likely small now, we believe it presents an attractive long-term opportunity for the company to tap into the ~US$200bn (by 2026) Indian e-Commerce market.

Exhibit 162:We Believe Amazon's International Business (ex Germany/UK/Japan) - Which Includes India - Will Be a Material Driver to Companywide Retail Revenue Growth

in $ millions

Amazon

Retail Revenue * 2013 2016 2019 '13-'16 '16-'19 '13-'16 '16-'19

North America 41,410 79,784 146,233 24% 22% 73% 70%

InternationalGermany/UK/Japan 25,465 34,492 46,871 11% 11% 17% 13%

Other Int'l 4,469 9,492 25,109 29% 38% 10% 17%

International 29,934 43,984 71,981 14% 18% 27% 30%

Total Retail Revenue 71,344 123,768 218,213 20% 21% 100% 100%

Other Int'l Contrib. to International retail growth 36% 56%

3-Year CAGR Contrib. to Growth

Source: Company data, Morgan Stanley Research estimates for 2019; Note: "Other Int'l" includes India, France, and China; *ex AWS, ex other

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Investing in fulfillment to drive seller and buyer growth: Amazon is investing in fulfillment in India. We believe this is because the com-pany sees the fact that the existing fulfillment infrastructure is sub-scale. Logistics are likely to be Amazon’s competitive advantage (as in other countries). Amazon's storage capacity and fulfillment infra-structure in India has grown to 41 centres in 13 states with a storage capacity of 13 mn cu ft. It also runs a ‘I Have Space’ program (IHS), wherein it partners with local store owners across different cities to deliver products to customers. Amazon India now has over 17,500 stores under this flagship program in over 225 cities. Like in other countries, we see Amazon investing in fulfillment and Fulfilled by Amazon (FBA) to drive more user growth, prime subscriber growth, and grow its overall share of consumers’ wallets.

Fashion, furniture and grocery: While Myntra and Jabong were considered the early leaders in the fashion category, Amazon India has increased its focus on the fashion category (in particular around mid-2015). It entered the furniture segment in late 2015 wherein it competes with vertical specialists like Pepperfry and Urban Ladder, as well as with Flipkart. The company has also launched its Grocery vertical in Bangalore and reportedly plans to expand across more of India. As detailed in our latest AlphaWise global eCommerce survey note (Here Comes Online Grocery), we have seen Amazon take an early lead in Grocery in other countries (like the US), so it stands to reason the company will invest in this category in India as well.

Where we could be wrong: India is a completely different market than the ones that Amazon has traditionally been active in and hence exposes it to different operational and regulatory risks. Also, the eCommerce industry is still in its early days, thus making it competi-tive and demanding from a funding perspective.

https://ny.matrix.ms.com/eqr/article/webapp/8c6fc28c-9ce5-11e5-b1e8-888b48217db6?ch=rpint

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digibank successful execution could drive strong growth in India and provide lessons for use across the region

DBS has a long and mixed history in India, but we believe that the medium-term investor focus will be on the build-out of its inter-net-based retail offering - digibank by DBS. Not only does digi-bank in India have the potential to become material relative to the rest of the group, but we also expect that the rest of DBS will benefit from what it learns in the build-out phase. DBS is also rolling out the digibank concept elsewhere; an Indonesian ver-sion was launched in late August 2017.

DBS

DBS in India

Exhibit 163:DBS India in Numbers (S$m)

Source: Company Reports, Morgan Stanley Research

DBS Bank India Ltd., is DBS' operating business in India. It operates as a branch and as such faces the usual restrictions around number of branch licenses and so on - it has 12 branches in India.

Given that it cannot offer banking services more than 5km from a branch, this also restricted the expansion of digibank. However, on September 4 DBS announced that it has received an in-principal approval to move to a full operating subsidiary structure, and this will allow it to compete on equal terms with domestic Indian banks - as a result of this we expect DBS will increase its branch network to about 35-40 branches over five years.

Whilst DBS India is a small part of the whole (c.1.5% of loans and deposits, and de minimus profits), it does represent c.2.5% of reve-nues, in part due to the higher margins available to Indian banks. Even in the medium term therefore a strong roll-out of the digibank fran-chise in India (as well as Indonesia) could have a noticeable impact on DBS revenues, and could help drive upside to the Indian bottom line given the relatively low cost required to drive the business.

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An important part of this argument is the relative size of India and Singapore - in its first 10 months, digibank in India had signed up 840,000 customers, equivalent to 16% of the entire population of Singapore. If revenues were to expand in line with the branch net-work, then we could see c.7.5% of group revenues from India in five years, potentially adding 1% p.a. to our base case forecast of a 10% CAGR in the top line. This will be another contributor to our forecast for DBS' 2018-19 top-line growth of 11% (alongside ASEAN loan growth and wealth management). Longer term, the impact could be more meaningful as digibank starts to become a more material part of the whole. Currently DBS India accounts for just 2% of group equity, therefore we believe any capital impact of growing the India business will be manageable.

What is digibank by DBS?

The Concept

digibank by DBS was India's first mobile-only bank. In DBS' own words, it does "away with branches, forms, signatures and call-agents. Instead, front and centre are biometrics, artificial intelligence (AI), analytics and dynamic security". Most customers come in via the e-wallet, which is operated by downloading an Android, or iOS App onto a mobile phone. They can then migrate to a savings account. There is no need to go to a branch, and accounts can be opened using a thumbprint and Aadhaar ID, although if customers upgrade to digis-avings they need to visit one of DBS partner stores (eg. Feno, or Cafe Coffee Day) for biometric ID verification. There is a call centre for digi-bank customers, however DBS state that 80% of calls are handled by an AI driven Chatbot. The capabilities of this Chatbot should improve over time. Ultimately, DBS believe that only 12% of interactions will go through agents.

The Product Suite

The entry product is a digital wallet, which allows the customer to make payments via an e-Visa card. DBS then tries to encourage cus-tomers to open a savings account and offers attractive rates to do this (currently 7%). At the moment c.28% of wallet customers have been converted to a savings account, and DBS is restricted to only using agents for eKYC verification who are within 5km of a DBS branch (although this will be less of an issue when DBS moves to a subsidiary structure and can roll out more branches). DBS estimates that c.71% of digisavings customers are active (i.e. they have carried out at least one transaction in the last three months). These cus-tomers are taking full advantage of UPI, with more than 70% of inbound and more than 50% of outbound transactions done through UPI. DBS will roll out more products over the coming months, including mortgages and unsecured personal loans as well as invest-ment and insurance products.

Where we could be wrong: We see two main risks for the DBS digi-bank roll-out. The first is that they execute too slowly, and lose out to larger competitors such as HDFC or Kotak. The second is that they get their credit scoring wrong and build up credit problems for later once they begin to offer lending products.

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India offers significant value potential for Naspers given increasing eCommerce penetration and from a shift towards online payments. Naspers has exposure to the leading eCommerce players and owns and controls some payment gateway companies.

India offers significant value potential for Naspers and it is not priced in. Naspers is a South African based conglomerate that owns a 33% stake in Tencent as well as stakes in a number of other internet businesses and Pay TV. The current valuation implies a market cap of US$98bn versus its Tencent stake which is worth US$131bn. Naspers invested early in China through Tencent, and its investments in India were a logical next step given the market potential. We currently value its Indian investments at >US$5bn and see potential for addi-tional upside as companies like Flipkart continue to compound growth and classifieds start to monetize.

For our investment case see Naspers: Can the discount get any wider? (12 Jul 2017)

Naspers should benefit from increasing eCommerce penetra-tion… Naspers has exposure to leading players in all the key verticals including online travel (MakeMyTrip covered by Parag Gupta), online retail (Flipkart), classifieds (OLX) and food delivery (Swiggy & Delivery Hero / foodpanda).

...and from the shift towards online payments. Naspers owns and controls payments gateway company PayU, e-wallet Citrus Pay and a 37% stake in digital banking services provider Kreditech. Whilst we believe it is smaller in scale relative to Paytm, growth is so significant that we believe there is room for multiple players.

Naspers Flipkart: As of August this year, Naspers owned a 16.5% stake in Flip-kart (it has subsequently raised capital from Softbank and others). Naspers estimates that the Flipkart Group is India’s largest e-com-merce marketplace and had a 55% market share of Indian e-com-merce gross sales in March 2017. Amazon is its largest competitor. Group companies include Flipkart, Myntra, Jabong and PhonePe. Flip-kart offers over 80m products across 80+ categories.

OLX: OLX is the leading generalist online classifieds platform in India. The app has already been downloaded 35m times in the last two years alone and we believe this could increase to 116m in the next five years. Classifieds require building a strong network for monetiza-tion and given the potential to add on more subscribers we believe the company will take a little longer to monetize, but we see it poten-tially generating US$100m+ of EBITDA on a five-year framework. Its main competitor is currently Quikr. Amazon recently announced it is also launching a classified offering.

PayU: PayU is a regulated financial institution and holds licenses from several national banks and local regulators. Its products include a digital consumer wallet, a PCI DSS certified payment gateway, anti-fraud systems and an online Visa/MasterCard acquirer. PayU acquired e-wallet Citrus Pay for US$130m in September 2016. As dis-cussed in detail in this report, the growth prospects for online pay-ments in India are material.

Exhibit 164:Naspers' Exposure to India

Business Estimated value Ownership

Value to

Naspers % of NAV Notes

U$m % U$m

%

MakeMyTrip 4,842 40% 1,937 1.4% Valued on our target price for MMYT

Flipkart 11,600 17% 1,914 1.4% Valued on funding round in August 2017

OLX India 876 100% 876 0.7% We estimate that India could represent ~12% of the total OLX value

PayU / Citrus Pay unknown unknown 660 0.5% Pay U acquired Citrus Pay for $130m in September 2016

Delivery Hero 4,842 11% NM NM $513m is full value of stake in DH. India would be a small portion of this

Swiggy unknown unknown NM NM Assumes Naspers led 50% of the recent $80m funding round in Swiggy

5,387 4.0%


https://ny.matrix.ms.com/eqr/article/webapp/f833935e-5a80-11e7-aac6-e86d11269a9a?ch=rpint&sch=cc

https://ny.matrix.ms.com/eqr/article/webapp/f833935e-5a80-11e7-aac6-e86d11269a9a?ch=rpint&sch=cc

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Swiggy / Delivery Hero: Naspers recently led a US$80m funding round in Swiggy. It also has an 11% stake in Delivery Hero, which owns foodpanda in India. They are both leading players in the market com-peting with Zomato and UberEATS. Swiggy has attracted over 12,000 restaurants to its platform and has experienced a six-fold growth in revenue over the past 12 months. The company runs its own delivery fleet and claims to have an industry-best average of 37 minutes per order. For more on Delivery Hero see Guardians of the ganoush (8 Aug 2017)

MakeMyTrip: Covered by Parag Gupta. After the merger of Ibibo and MakeMyTrip, the company has become the undisputed leader in Indian Travel. See Street Comparing Apples to Oranges; Opportunity to Buy (15 Aug 2017).

Where we could be wrong: Slower growth in the Indian internet industry, higher burn rates or significant slowdown in investment activity could hurt the value of the portfolio companies.

https://ny.matrix.ms.com/eqr/article/webapp/8830d6fa-6879-11e7-8383-52e3d9f3b385?ch=rpint&sch=cfr

https://ny.matrix.ms.com/eqr/article/webapp/8830d6fa-6879-11e7-8383-52e3d9f3b385?ch=rpint&sch=cfr

https://ny.matrix.ms.com/eqr/article/webapp/0aee613c-7e5c-11e7-ae04-32d0453860be?ch=rpint&sch=cc

https://ny.matrix.ms.com/eqr/article/webapp/0aee613c-7e5c-11e7-ae04-32d0453860be?ch=rpint&sch=cc

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High level of commitment to investing in platform busi-nesses in India. Softbank’s investments in India are focused on platform business, undertaken with a medium- to long-term view, we believe. A ~US$200bn (by F2027) Indian eCommerce market becomes an attractive opportunity for the company. Softbank is keen to hone platformer capabilities in anticipation of IoT.

We estimate that Softbank has thus far invested a total of about US$4bn in India, starting with its application of a stake on online marketplace Snapdeal in 2014. In December 2016, Softbank president Masayoshi Son indicated that the company plans to invest more than US$10bn in India over the next 10 years. In con-junction with other investors including Saudia Arabia’s Public Investment Fund (PIF), the company established the Softbank Vision Fund, through which it plans further aggressive invest-ment activities.

Softbank’s investments in India are focused on platform business and we recognize that they are undertaken with a medium- to long-term view. We also think that Softbank’s investment stance (not only in India) is, at this point, guided less by the pursuit of clear synergies with existing business than by the incremental coalition-building through capital participation with the founding families of the com-panies in which it is investing, with the aim of securing business opportunities at an increasing pace over the longer term.

Softbank’s major investment returns in India

1) B2C e-commerce: Softbank has invested in the domestic e-com-merce leader Flipkart (August 2017) and the number three in the online market Snapdeal (October 2014). It has also already invested in e-commerce platformers in other regions, and is generating returns on its investments in Alibaba (China), Tokopedia (Indonesia), and Coupang (Korea).

2) Transportation services: Softbank invested in ride-hailing com-pany Ola in October 2014. The company has also invested in similar

Softbank 3) Financial settlement: Softbank invested in India’s Paypayments company in May 2017. The company’s subsidiarhad previously taken a stake as well. The company has ntaken significant investments in financial settlement sother regions, but it did invest in US online loan arrangFinance, Inc., in October 2015.

Where we could be wrong: Softbank's global investment htrack record as its aggregate performance, but it also rsome significant write-offs. If the major portion of theinvestment in India becomes at risk, then it might shift intargets to other regions.

Exhibit 165:Softbank’s Major Investment Returns in India

Company name Business category

2014/10 Snapdeal B2C EC platform

2014/10 Ola Transportation service

2014/10 Housing .com Real estate information si

2017/5 Paytm Payment service

2017/8 Flipkart B2C EC platform

Source: Company data, Nikkei and Morgan Stanley Research

Morgan Stanley is acting as financial advisor to Fortress InGroup LLC (“Fortress”), in connection with its definitive aunder which SoftBank Group Corp. will acquire Forannounced on February 12, 2017. The transaction is sapproval by Fortress shareholders, certain regulatory approther customary closing conditions. This report and the inprovided herein is not intended to (i) provide voting advice, (an endorsement of the proposed transaction, or (iii) result curement, withholding or revocation of a proxy or any othera security holder. Fortress has agreed to pay fees to Morgafor its financial advice, including a transaction fee that is cupon the consummation of the proposed transaction. Pleathe notes at the end of the report.

106

companies in China (Didi Chuxing) and South-east Asia (Grab), as it steadily builds a global structure for transportation services.

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Beneficiary of Credit Expansion in India

With the strong growth of the Indian economy and the emerging middle class in the early stages of becoming credit active, we expect TRU to be a key beneficiary, as it owns 92% of TransUnion CIBIL Ltd, India's leading credit information company.

Large and growing database: TransUnion CIBIL has over 2,400 members including all leading banks, financial institutions, non-banking financial companies and housing finance companies. As of February 2007, its credit database includes information on over 270 million consumers and 13 million businesses, a ~30-35% increase from its disclosure of over 200 million consumers and 10 million business entities as of February 2016. To enhance its solutions, CIBIL also pulls from non-credit data sources including the national voters registry with 750 million recorders, the national ID database with over 1.1 billion records, as well as the confirmed and suspected fraud registry, property registry, and tax ID database. Using its extensive database and TransUnion's analytics capabilities, TransUnion CIBIL developed and launched the first generic credit score for India, which is the most widely adopted credit score across the country.

Data drives lending: Increased availability of data drives additional lending, as lenders can make a more educated decision on the risk of the borrower. This has led to strong growth in retail loans, as well as a shortened time period for loan approvals. A 2016 CIBIL report found that retail loans were growing at a 28% CAGR over the prior three years, and the average time of a loan approval accelerated to 3-4 days from 7-9 days over the same time period. CIBIL also indicated that increasing data has improved the quality of loans, with delin-quency of repayments (90 days and more) coming down from 1.06%

TransUnion at the end of 2010 to 0.57% in 1Q15. Due to additional data and ana-lytics, we would also expect that over time credit will be further extended to lower score borrowers, with CIBIL indicating that as of June 2015, 79% of all retail loans across India were for individuals with scores above 750. TRU's revenue model is volume-based, as financial institutions purchase data and solutions to determine whether to lend money to a business or individual. Thus, an increase in credit application volumes drive additional growth within TRU's Interna-tional segment. CIBIL products sold include analytics and decision-making solutions for banks, telecommunication companies, and insurance companies, as well as online credit reports and scores for consumers.

India contribution currently small, but growing fast with high potential. Though CIBIL was started in 2000, TRU has rapidly increased its stake in the last few years, going from 27.5% ownership in 2013 to 92% today. Back in 2013, TRU's equity stake in CIBIL dis-closed on its balance sheet implied a US$103mn book value, while its most recent 10% increase in ownership implied a ~US$587mn valua-tion. Though TRU does not explicitly disclose the revenue contribu-tion, we estimate CIBIL generated ~US$45mn of revenue in 2015 (~3% of TRU revenue), but expect this unit to be growing faster than the overall business. In TRU's emerging market business, we forecast a ~9% CAGR between 2016-2021, with the India business being a large driver of this. With a large opportunity for growth in credit and CIBIL currently the only meaningful credit bureau, we see strong upside for TRU in the Indian market.

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Exhibit 166:Emerging Markets, Which Incorporate India, Will Drive a Larger Portion of Growth in the Coming Years

in $ millions

TransUnion 2013 2016 2019 13-'16 16-'19 13-'16 16-'19

U.S. Information Services 749 1,045 1,325 12% 8% 52% 64%

International

Developed Markets 89 109 139 7% 8% 3% 7%

Emerging Markets 152 205 270 10% 10% 9% 15%

Total International 241 314 409 9% 9% 13% 22%

Consumer Interactive 204 407 470 26% 5% 36% 14%

Total Revenue (Ex-Eliminations) 1,194 1,766 2,204 14% 8% 100% 100%

Emerging Market Contribution to Int'l Growth 73% 68%

3-Year CAGR Contrib. to Growth

Source: Company Reports, Morgan Stanley Research estimates

Where we could be wrong: We see the following potential risks:

l An economic slowdown could drive lower demand for credit information.

l Higher US interest rates could pressure mortgage and card applications.

l Contributing data to free or freemium consumer moni-toring service providers could cannibalize TRU's existing direct-to-consumer business.

l Leverage remains at the high-end of our Analytics cov-erage.

l Increased regulation as a result of EFX cybersecurity breach could lead to industry changes or increased costs of compliance.

Equifax data breach implications: Over the long term, we think the fundamental strength of TransUnion's business is intact and believe India represents a compelling growth opportunity. However, with the disclosure that credit bureau competitor Equifax suffered a mas-sive data breach (with 143 million US consumers impacted), near-term stock movements for TRU will likely center around the news flow around the breach. We believe that TRU could benefit from share shift (as customers may decide to switch from EFX to one of the other bureaus), and TRU's consumer business may see increased business from customers more worried about ID protection. On the other hand, it is at risk of tighter industry regulation. As it relates to cybersecurity, TRU management has indicated that it continues to focus on having the best processes, software, partners, and tech-nology to help mitigate their risk.

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Digitization Should Grow the Pie for Visa and Master-Card

Card payments represent only 5-7% of PCE (Personal Consumption Expenditure) in India. As recent regulatory and technological devel-opments steepen the digital adoption curve in India, we expect the absolute value of non-cash payments, including utilization of card networks, to grow rapidly. As the digital payments pie grows, both networks (Visa and Mastercard) should benefit, particularly as initia-tives like BharatQR allow merchants in India to leapfrog the tradi-tional (and more expensive) POS card acceptance terminal investments. At the same time, the lack of a well-established card acceptance infrastructure and the rapid pace of change should allow newer, non-card digital payment innovations to also gain traction. Credit and debit cards may see their mathematical grip on digital pay-ments loosen, but the pie should grow for everyone.

Can Visa and Mastercard remain dominant players in the India market amidst growth of new entrants?

A key question is whether Visa's and Mastercard’s differentiation in terms of global operability, superior security tools, and experience in innovation can enable them to remain among the dominant players in the market. We believe the answer is yes.

l Global scale and reach: Visa and MasterCard are interna-tional schemes with global acceptance at ~40mn merchant locations worldwide. Many of the new entrants sprouting in India are still working to develop domestic acceptance with no presence internationally. Meanwhile, thanks to a combination of lower travel costs and a growing affluent/middle class in India –– affluent income categories in India are growing the fastest and driving a disproportionate share of increasing consumption –– India is rapidly becoming one of the fastest-growing outbound travel mar-kets in the world, second only to China. This will likely favor growth and usage of global payment schemes such as Visa and Mastercard in the affluent income categories, in our view. Additionally, the underlying specifications for BharatQR developed by Visa, Mastercard, and NPCI (National Payments Corporation of India) can be imple-mented in other countries to deliver a globally interoper-able solution for credentials issued digitally in India.

Visa and Mastercardl Innovations such as BharatQR should allow rapid growth

in card acceptance: Over 1 million new acceptance points have been added in India since demonetization (November 2016), relative to only 250,000 new acceptance points added in the 12 months prior to that. Of these, 200,000 are QR code based acceptance points. Innovations like BharatQR, which have been developed by collaborative efforts among Visa, Mastercard, and the NPCI, allow mer-chants in India to leapfrog the traditional (and more expen-sive) POS card acceptance terminal investments. Visa believes that QR and contactless will comprise 25% of its total transactions in the next 3-5 years. Additionally, mobile point of sale or mPOS devices, which also provide a low cost acceptance solution to merchants, are starting to gain traction and are anticipated to grow rapidly.

l Strong growth in card issuance: There are approximately 850 million credit and debit cards outstanding in India, giving the networks a head start versus any new digital payment types that have yet to build scale. New players are also fast gaining traction –– e.g. Paytm exceeded 200mn registered users earlier this year. But Visa and Mas-tercard also plan to accelerate card issuance. Visa has stated that over the next 3-5 years, it expects to issue an incremental 200 million cards, both physical and digital.

l Ability to leverage global innovations: Visa and Mastercard have a broad suite of product innovations globally that can be leveraged on to suit the unique needs of the Indian dig-ital payments market. The Government of India's collabora-tion with the networks for development of the BharatQR code is a reflection of that.

l Marketing and advertising engine: Having done this in many markets over and over, Visa and Mastercard have well developed tools in their standard playbook on building brand awareness and preference and improving card usage at the POS. Both are investing in marketing activities, which are being amplified by issuing and mer-chant partners. e.g. seven public sector banks in India that account for ~20% of debit cards in-force leveraged Visa's campaign and placed it within their marketing toolkit on their bank web pages and digital channels.

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Risks to Visa and Mastercard dominance:

Fee regulation may curtail interest from card issuers: Reserve Bank of India has a new proposal for regulation of Merchant Discount Rates (MDRs) (See Exhibit 21 ). A significant reduction in MDRs could be a deterrent for issuing and acquiring banks (as all acquirers in India are issuers as well), although we have not found this to be the case in other markets where interchange fees have been regulated (Australia, UK, Spain, US debit, and so on). While lower economics may not be viable for banks in the near term given that the card busi-nesses are subscale, this could change if digitization takes off materi-ally as the increase in volumes could more than offset the loss in spread for the issuing/acquiring banks.

Networks may have less flexibility on pricing versus new disrup-tors: As new entrants try to build share, some may be aggressive on pricing in order to build usage. e.g. new disruptor Paytm waived off the merchant fee to Zero temporarily. Although it may be a money-losing proposition in the near term, Paytm has access to some fairly deep pockets (Alibaba and Softbank) and is likely to view these losses as investment in acquiring customers at scale, which can be monetized later. Visa and MasterCard may be restricted in their ability to compete on price, despite their low cost structure, as they need buy-in from the issuing and acquiring banks to forego eco-nomics from merchants in exchange for volumes. And banks may be more averse to cutting their card revenue pools relative to tech dis-ruptors.

Sizing the Addressable Opportunity: Growth Off a Negligible Base

Credit and debit card spend aggregated to ~US$88bn in total pur-chase volume in India in CY2016. This is a rounding error for Visa/Mas-tercard payment volumes today at <1% of Visa's and Mastercard’s combined 2016 purchase volume and ~3% of Visa's and Mastercard’s combined volume in the APAC/APMEA region. Credit and debit card spend made up ~90% of total digital spend (credit + debit + Rupay + m-wallets + UPI) in India during this period.

Our base case assumption is for digital payments to grow from 8% of PCE in F2017 to 36% in F2027. If this comes true, ~US$1.2 trillion of payments would be transacted digitally in F2027, which is a good proxy for CY2026. If card networks can maintain 45% share (versus ~90% today), total purchase volumes on card would be ~US$600bn, representing a CAGR of ~20%. The exhibit below shows some sce-narios of what the network revenue contribution from India could potentially look like in 2026, assuming much lower than average net-work yields given the potential for fee regulation in India. Our anal-ysis assumes that Visa and Mastercard make up the majority of share of the credit and non-Rupay debit card market. While American Express and Discover cards may also have a presence in India, we expect their share is fairly low.

Exhibit 167:Visa and Mastercard Aggregate Revenue Potential from India in 2026

2016

India Digital Payment Volume ($bn) 98

CAGR assumption

Estimated Revenue Potential in $millions

V/MA Market share 90% 25% 35% 45% 55% 65%

0.050% 150 210 270 330 390

0.055% 165 231 297 363 429

0.060% 180 252 324 396 468

0.065% 195 273 351 429 507

0.070% 210 294 378 462 546

Network Fee yield

2026e

1200

28.0%

Source: Company Data, RBI, Morgan Stanley Research. e = Morgan Stanley Research estimates.

Note that given the solid potential for growth in purchase volumes in developed parts of the world, India may remain a relatively small contributor to overall growth rates for Visa and Mastercard longer term, but it represents one of many growth drivers that could help sustain the double-digit growth rates for the companies for an extended period of time.

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Current State of India's Card Payment market

India's card market is dominated by debit cards...

The total number of credit and debit cards outstanding has grown rapidly from 280mn cards at the end of 2011 to 739mn cards at the end of August 2016, representing an increase from 0.23 cards per capita to 0.56 cards per capita over this period. The growth in card issuance has largely been driven by debit cards and is in part attributable to the introduction of India's domestic cards, Rupay. Debit cards represented ~96% of total cards outstanding as recently as 1H2017. Rupay debit card issuance has grown rapidly from 17mn or less than 5% of all debit cards outstanding in India at the end of 2014 to 321mn or nearly half of all debit cards, based on recent data from India's Department of Financial Services.

Exhibit 168:Visa and Mastercard Cards Dominate Transaction Volume, Even Though Rupay Has a High Share of Total Cards

1

Rupay debit cards

45%

All other debit cards

55%

Debit cards - Rupay vs. V and MA

Rupay transaction

8%

All other debit

transaction 92%

Debit card POS transactions - Rupay vs. V and MA

Source: National Payment Corporation of India, PMJDY (Department of Financial Services, Government of India)

… but credit cards dominate card spending at POS

Credit cards account for only 4% of total outstanding cards, but they constitute a majority of the card-based spend at the POS, although the mix of credit card transactions has been declining and more recently at an accelerating pace. In 2017, credit cards represented ~50% of total card-based POS spend, down from >60% in 2012.

Debit cards have gained some share, largely after the demonetization initiative in November 2016. But use of Rupay cards for retail transactions still remains relatively low versus overall debit card utilization at the POS, at 8% during the month of August 2016. One of the reasons for this divergence could be that the growth of Rupay card issuance has been relatively high in remote/rural areas, which have limited POS acceptance infrastructure and low consumer education/awareness.

Rupay domestic scheme Card type: The Rupay card scheme was launched in 2012 by the National Payments Corporation of India (NPCI) as a debit only scheme. This domestic scheme was conceived to promote financial inclusion in India, while offering banks a more affordable payment solution vis-à-vis what was being offered by international schemes like Visa and MasterCard. Although NPCI had plans to eventually launch Rupay credit cards as well, that could take some time.

Acceptance: Rupay started off with limited acceptance, but through partnership with acquiring banks, Rupay cards are now accepted at all ATMs and POS terminals in India. Rupay expanded acceptance to online transactions in April 2013 and is now accepted at over 20,000 e-commerce merchants in India. Internationally, through an agreement with Discover, Rupay cards can be used at all Discover and Diner POS and ATM networks.

Transaction costs: Rupay was designed to be a low-cost scheme for banks with a fixed fee of INR 0.45 per transaction for ATM use and INR 0.90 per transaction for POS or e-commerce transactions. This compares to international schemes like Visa and MasterCard that typically charge variable fees based on the transaction value.

Issuing banks: Rupay cards are offered by ~40 or so public, private and small cooperative banks in India. The international schemes typically work with the larger public and private banks and may not include the small rural cooperative banks in their networks.

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Three major trends ("JAM") have emerged in India over the past 6-7 years – creation of a universal identification / authentication mechanism for the entire population; ensuring every household in India has access to a bank account; and a surge in mobile penetration and a rapid pickup in smartphone usage. Government and policy-makers realized that leveraging the combination of these trends would yield a powerful force for economic devel-opment, and this has given rise to the JAM initiative.

Appendix 1 - JAM: Catalyzing Digitization

Jan Dhan Yojana - The government launched this plan in August 2014 to ensure complete financial inclusion for the country's citizenry. Since then, ~285mn bank accounts have been opened under this scheme. This is a no frills account offered to economically weaker sections of the society. Prior to the launch of JDY, ~35% of house-holds in India did not have a bank account. But, since August 2014, most Indian households, we believe, have gained access to a bank account.

Exhibit 169:~285mn Bank Accounts Have Been Opened Under the PMJDY Scheme (~23% of India's Population, and Much Greater Proportion of Households)

Particlualrs

(Data in Mn)RURAL URBAN TOTAL

BALANCE IN

ACCOUNTS

% OF ZERO-

BALANCE-

ACCOUNTS

Balance Per

A/C (Rs)

F1Q15 0.0 0.0 0.0 0 NA NA

F2Q15 31.7 22.1 53.8 42,732 76.8 795

F3Q15 62.3 42.1 104.5 83,534 73.3 800

F4Q15 87.8 59.3 147.2 156,703 57.9 1,065

F1Q16 99.0 65.3 164.3 190,154 51.8 1,158

F2Q16 112.6 72.8 185.4 249,392 40.3 1,345

F3Q16 121.0 77.3 198.4 292,256 31.8 1,473

F4Q16 131.7 82.6 214.3 356,720 27.4 1,665

F1Q17 136.9 86.0 222.9 392,516 25.3 1,761

F2Q17 151.8 95.5 247.4 435,327 24.1 1,760

F3Q17 159.6 102.4 262.0 710,366 24.1 2,711

F4Q17 168.7 113.0 281.7 629,724 2,236

F1Q18 171.0 115.3 286.3 643,649 2,248

Source: PMJDY website

Exhibit 170:Percentage of Population Over the Age of 15 With Accounts at a Financial Institution, Across Countries (2014)

99

99

99

98

98

97

97

96

94

88

88

87

82

82

81

79

70

69

68

63

53

50

39

36

31

25

13

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50

75

100

United K

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Au

str

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Germ

any

Sw

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Sp

ain

Jap

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Fra

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Sin

ga

pore

United S

tate

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Gre

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Gre

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Italy

Mauritius

Cze

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Mala

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Chin

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So

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Afr

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Sa

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Bra

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India

Arg

entina

Mexic

o

Indonesia

Ph

ilippin

es

Jord

an

Pa

kis

tan

Source: World Bank Findex Database, Morgan Stanley Research

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Aadhaar - The intent of this programme (launched in 2010) was to ensure that every Indian has an officially recorded identity. Over 6-7 years, this has created a biometric digital database of 1.2bn people, ~92% of the country's population. Prior to this, nearly half of the country didn’t have any form of identification. Individuals in the Aad-haar database have a 12-digit digital identity, which can be authenti-cated by fingerprints and retina scans.

Mobile phone penetration - There has also been sharp surge in mobile phone usage in India, with the current number of mobile con-nections at ~90% of the population. Fairly cheap telecom tariffs and the launch of no-frills low-priced phones has aided penetration. There has also been a sharp increase in smartphone penetration, with ~25% of mobile phones in the country today being smartphones. Since 2012, the share of smartphones in total shipments has increased from 7% then to 50%, and this could reach 100% by 2020. We expect smartphone penetration to surge further, reaching over 50% of total mobile penetration by F2021.

Exhibit 173:India: Smartphone Penetration Has Surged

283 322

401

490

570

673

764

140 223 292

347 426

546

685

11%

22%

31%

49%

0%

10%

20%

30%

40%

50%

60%

-

100

200

300

400

500

600

700

800

900

CY14 CY15 CY16 CY17E CY18E CY19E CY20E

Wireless Data Subs Net Smartphone Penetration

4G phones (Penetration) % Smartphone penetration

(mn)

Source: Statista, TRAI, Morgan Stanley Research, E= Morgan Stanley Research Estimates

Exhibit 174:India: Sharp Pickup in Data Subscribers

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

F1Q

13

F2Q

13

F3Q

13

F4Q

13

F1Q

14

F2Q

14

F3Q

14

F4Q

14

F1Q

15

F2Q

15

F3Q

15

F4Q

15

F1Q

16

F2Q

16

F3Q

16

F4Q

16

F1Q

17

F2Q

17

F3Q

17

F4Q

17

Total Data Subscribers ('000)

Source: TRAI, Morgan Stanley Research

Exhibit 171:Number of Aadhaar Accounts

0

200

400

600

800

1000

1200

1400

2010

2011

2012

2013

2014

2015

2016

Aug-2017

Source: UIDAI, Morgan Stanley Research

Exhibit 172:Authentications Using Aadhaar

0

200

400

600

800

1000

1200

Jun-16

Jul-16

Aug-16

Sep-16

Oct-16

Nov-16

Dec-16

Jan-17

Feb-17

Mar-17

Apr-17

May-17

Jun-17

Jul-17

Aug-17

Total AuthenticationTransactions (Rs Mn)

Source: UIDAI, Morgan Stanley Research

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Exhibit 175:India: Wireless Data Cost

-

50

100

150

200

250

300

350

400

450

F4

Q1

2

F1

Q1

3

F2

Q1

3

F3

Q1

3

F4

Q1

3

F1

Q1

4

F2

Q1

4

F3

Q1

4

F4

Q1

4

F1

Q1

5

F2

Q1

5

F3

Q1

5

F4

Q1

5

F1

Q1

6

F2

Q1

6

F3

Q1

6

F4

Q1

6

F1

Q1

7

F2

Q1

7

F3

Q1

7

F4

Q1

7

F1

Q1

8

Airtel blended data price (Rs/GB)

RJio data price (post promo) Rs/GB


A challenge in an emerging economy such as India had been that a large proportion of the population was undocumented; they did not have access to financial services, and there was no proper way to con-nect them with the rest of the world. This has been solved through the implementation of JAM.

Exhibit 176:India: The JAM Trinity

J

Jan Dhan Yojana – Banking for all. ~285 mn new accounts in last three years

A Aadhaar – Unique identifier for all Indians. About 1.2 bn people enrolled

M

Mobile – Increased usage lowers the need for bank branches


Exhibit 177:Various APIs of India Stack

Source: India Software Product Industry Round Table (iSPIRT)

India Stack - Bringing this all together

The success of the above three trends (JAM) has ensured that mecha-nisms to solve identity issues, lack of banking access, and need for physical infrastructure have been set up. The subsequent leap over the past year or so has been bringing these together into single eco-system. This is being driven by India Stack. India stack is a set of appli-cation programming interfaces (APIs) that leverage this infrastructure, moving towards presence-less, paperless, and cash-less service delivery.

A number of APIs have been launched, with full regulatory backing, which utilise this infrastructure. Five of the key APIs are e-KYC (which allows electronic know-your-customer verifications, making cus-tomer acquisition quick and very low cost); UPI (which allows mobile-based payments on a real-time basis across individuals and businesses); Bharat QR code (an interoperable QR code system with all the key payment gateways and banks on board); Bharat Bill Pay System (moving all bill payments in India - telecom, utilities, govern-ment, and so on - to one platform); and Aadhaar Enabled Pay System (enables customers to conduct transactions using Aadhaar Card and fingerprints for biometric authentication).

This may appear to be a long list of initiatives. But they essentially cover the entire range of payments in the country. All one needs to make these payments is a mobile phone and bank account. These are real time and, given that these systems are also regulator backed, they are interoperable - which should help kickstart digital payments in the country. We explain these five in some detail.

1. e-KYC - Electronic know-your-customer systems enable individ-uals to grant service providers access to personal identification infor-mation. This makes KYC almost instantaneous – and secure and paperless – as compared with traditional KYC practices (e.g., opening a bank account, which generally can take a few days, making such a process relatively costly). Under e-KYC, UIDAI only shares demo-graphic information (name, address, date of birth, gender, photo-graph, mobile number) that is collected during Aadhaar enrollment with the consent of the customer.

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RBI has also allowed banks to open some new accounts using one-time PINs (OTPs) on mobile phones. This is likely to quicken the process of opening such accounts. These are relatively small value accounts, with a maximum deposit of Rs100,000. Still, banks are required to conduct proper due diligence on the customer within a year of opening these accounts, after which they can become stan-dard customer accounts; such due diligence can be achieved just by taking the fingerprint of a customer to authenticate the Aadhar details.

This is enabling customer acquisition at banks – quickly and at a very low cost. e-KYC reduces the number of people needed to acquire new customers, frees up physical space, and reduces requirements for back-office personnel for customer acquisition. This also applies to other services in which customer onboarding requires KYC – for instance, selling mutual funds to new customers, and targeting new customers for mobile phone subscriptions.

An example of banks using this feature is the launch of '811' accounts by Kotak Bank. In April 2017, Kotak Bank announced the launch of 811 bank accounts. These accounts are set up using e-KYC (Aadhaar number, tax number, and a onetime password). Depositors can use such accounts for basic banking services, and maintain balances of up to Rs100,000. No human interface is needed to open these accounts; customers download the 811 app and open the bank account on their own. Kotak has ambitious growth plans through 811 – targeting a doubling of its total customer base over 18-24 months, from 8 million to 16 million.

2. Unified Payment Interface (UPI) - This is the killer app for pay-ments in India, in our view. This protocol enables instant funds transfer (24x7, both payment and collection) via a smartphone (only) with the use of a virtual address (e.g., Aadhaar card, mobile number), just like a text message (avoiding multiple card/bank account details/OTP, and so on). The only thing needed to transfer money is the vir-tual payment address (for instance [email protected]); there is no need to share bank account details.

Exhibit 178:Monthly Transactions Using UPI

0.0

7.0

14.0

21.0

28.0

35.0

42.0

Apr-16

May-16

Jun-16

Jul-16

Aug-16

Sep-16

Oct-16

Nov-16

Dec-16

Jan-17

Feb-17

Mar-17

Apr-17

May-17

Jun-17

Jul-17

Unified Payment Interface, Transaction Values (Rs Bn)

Source: NPCI, Morgan Stanley Research

There have been other mobile phone apps that allow easy transfer of funds, for example digital wallets. However, these are not inter-oper-able, i.e., there's no common system. The attraction of UPI lies in the fact that a consumer can link any number of bank accounts to a single UPI app. So, if an individual's primary account is, for example, at HDFC Bank, and that person has other accounts, for instance at ICICI and HSBC, the customer can use a single app (i.e., any bank or payment service provider's UPI-based app) and link all the accounts to that one app. When the account owner transfers money, they choose among their linked accounts. The cost of a UPI transfer on P2P is also fairly low, at ~Rs.0.5 per transaction, which will likely aid its growth.

The other significant advantage of UPI is that it is a push (payer initi-ates transaction) as well as a pull product. While push is useful for P2P transactions, pull will be important for merchant transactions. This allows merchants to ask for payment from a customer as long as both parties have mobile phones and a bank account. This obviates the need for payment infrastructure.

However, banks are still charging MDR (merchant discount rate) on these transactions in line with debit card MDRs. Over time, we expect these MDRs to decline sharply, causing a sharp increase in merchant acceptance of payments through UPI. Also, given the lack of required infrastructure, even small transactions (e.g., paying cab fares) can be made through UPI.

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Exhibit 179:UPI Merchant Transaction - Schematic Representation of a Merchant Transaction

vpa@abcbank MPIN

Submit Submit

Merchant Customer

Customer's Bank

Merchant's Bank

PSP APP (Merchant) PSP App (Customer)

NPCI (UPI)Merchant's

PSPPayer's PSP

1 Customer's virtual address

2 Identifies customer's PSP ABC bank

and routes to ABC bank

5 PSP validates the customer details Send the financial details to UPI for debit to customer account

9 Successful

credit

7 Successful debit basis

6 Debit

Request

3 Send notification for

payment

4 MPIN entered by

Customer

8 Credit

Request

10 Transaction Confirmation


Bharat QR (Quick Response) System: The lack of payment infra-structure has been one of the significant challenges in making elec-tronic payments in India. To circumvent this problem, various payment gateways (Visa, Master, Amex) had their own QR-code-based systems. However, these were not interoperable. In 1Q17, NPCI collaborated with the three payment networks to launch the Bharat QR-code-based payment system. In this payment method, the mer-chant has to download the QR code - either static or dynamic - and this can be scanned by the customer on his mobile, enabling him to make a payment.

Customers can use their bank apps to scan a merchant's QR code, and pay using any of the payment networks (Visa, Master, Amex or Rupay). Alternatively, the customer can also use the UPI app to scan the QR code and make payment from their bank accounts (similar to a debit card transaction).

This is in addition to UPI as a payment app. In our view, customers may still want to pay using cards – as they get a credit period on credit cards, collect points, and so on. For those customers, Bharat QR code removes the hinderance of lack of payment infrastructure available at merchant establishments.

Exhibit 180:Bharat QR Code: An Introduction


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Bharat Bill Pay System (BBPS) - A major component of any retail payment transaction is bill payment. An RBI committee studying the feasibility of giro-based payments in India estimated that in the top 20 cities, almost 31 billion bills are generated annually, with Rs6 tril-lion in payments every year. Over 70% of these transactions are still predominantly being carried out by cash or cheques.

Additionally, the present bill payment infrastructure in India is largely biller-specific in terms of modes of payment accepted and channels (payment gateways) supported. Its not interoperable and does not offer and 'anytime, anywhere' payment option to cus-tomers.

The Bharat Bill Payment System (BBPS) has been launched to cir-cumvent these constraints. It is an integrated bill payment system that offers interoperable bill payment services to customers through a network of agents, enabling multiple payment modes, and pro-viding instant confirmation of payment. Initially, BBPS covers regular payments, for instance at various utilities. The intent is to gradually increase coverage to other types of regular payments, such as munic-ipal taxes, educational fees, and so on.

There will be multiple operational entities to facilitate bill payments. The operating units will on-board billers, aggregators and payment gateways, and will set up the agent network and customer touch points to handle bill payments via various delivery channels (self- ser-vice, assisted, electronic and manual modes). So far, >60 approved operating units (called BBPOUs) have been identified, of which ~52 are banking entities.

Exhibit 181: BBPS Overview


Aadhaar-enabled Payment System (AEPS) - This is primarily geared toward servicing economically weaker sections of the society. It facilitates inclusion in online interoperable financial transactions at PoS (MicroATMs) through the business correspondent (BC) of any bank using Aadhaar authentication. AEPS enables payments at a PoS (MicroATM) without requiring a mobile phone or a debit / credit card. The only inputs required for a customer transaction under this sce-nario are Aadhaar number, fingerprint, and bank account number. Regular banking services (e.g., balance enquiry, cash withdrawal / deposit, funds transfer to other Aadhaar-based accounts) can be made through this route. This should help accelerate financial inclu-sion, as BCs can use microATMs to travel from village to village and help individuals conduct simple transactions.

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Every business needs a disruptor that jolts incumbents into changing the business-as-usual nature of going about their activities. We believe that in India, Paytm may well be such a disruptor. Paytm (which stands for Pay Through Mobile) started as a mobile wallet company that was ini-tially focussed on prepaid mobile recharging (the bulk of Indian mobile subscribers have prepaid connections). It subsequently started delving into other forms of small payment activities such as movie tickets, bus tickets and Uber. Over time it has become India's largest mobile pay-ments platform. It has also secured a payments bank licence from the RBI.

It now has almost 250 million customers and aims to increase this to ~500 million by 2020. It has been offering multiple products to these customers, ranging from simple payments to micro insurance. However, although it was becoming a big mobile wallet company, it was not impacting the formal banking payment transactions in a very meaningful manner. But this is now changing. If we look at total mobile wallet transactions in India (not just Paytm), the value has been increasing rapidly in the country, increasing from Rs10bn in F2013 to Rs530bn in F2017. In fact the value is now equivalent to about ~10% of the total merchant transactions on debit and credit cards.

Appendix 2 - Paytm - The Disruptor That Is Becoming a Big Player

Exhibit 182:PAYTM Customer Base (mn)

0

60

120

180

240

300

Nov-14

Feb-15

May-15

Aug-15

Nov-15

Feb-16

May-16

Aug-16

Nov-16

Feb-17

May-17

Aug-17

Source: Media including Times of India, Morgan Stanley Research

Exhibit 183:India: Digital Payments (Rs Bn)

0

2,000

4,000

6,000

8,000

10,000

F2004

F2005

F2006

F2007

F2008

F2009

F2010

F2011

F2012

F2013

F2014

F2015

F2016

F2017

F1Q

18

Digital Payments Values, Rs Bn

Credit Cards POS

Debit Cards POS Ex Rupay

M Wallet

Rupay Cards POS

UPI

Source: RBI, NPCI, Morgan Stanley Research

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We expect the total value of mobile wallet transactions to surge from F2018 onwards. Historically, Paytm was not big in merchant payments. But since the Currency Replacement Programme in November 2016, it has started focusing on this part of the business in a much more active manner. It has been on an aggressive drive to acquire new merchants on its platform and now has ~5 million mer-chants accepting payments through Paytm (QR based). This com-pares with ~2 million merchants who accept credit and debit cards through the POS network.

AlphaWise - Our survey also shows the significantly higher aware-ness and usage of Paytm since the end of 2016 (post CRP); 68% of our surveyed customers said they have been using Paytm since the CRP and 77% said they have increased usage since then. Historically Paytm was primarily used as a P2P payment option - but clearly usage with merchants is increasing.

The reasons for the surge in usage of Paytm and other mobile wallets are as follows:

1. Increased awareness and ease of use - Paytm has been fairly aggressive in ensuring the increase in awareness of its product. It has also been on a merchant acquisition spree which has helped add ~ 5 million merchants who can now accept payments through Paytm.

2. Low transaction cost - One of the key reasons why merchants have historically avoided digital payments was the cost - including the cost of POS machines and MDR (Merchant Discount Rate). Paytm has brought down the cost for merchants significantly. Since pay-ments are based on QR code technology, the incremental cost of the payment infrastructure is very low. And Paytm is charging no MDR to the merchants. Paytm does charge an inter-change fee during the cash-out process, though.

Is Paytm losing money on this? Yes. It has invested more than US$600 million in creating and driving adoption of digital payment network on the platform. As the number of customers on the plat-form increases, Paytm can start offering multiple products to these customers - with almost zero incremental cost - potentially driving a parabolic increase in profitability. Do we know if and when will this happen? No. But given fairly deep access to funding (Alibaba and Softbank are amongst its biggest investors), it can afford to keep losing money for a few years and acquire more customers. Paytm is essentially hoovering up the 500 million people who constitute the under-banked market.

Exhibit 184:Digital Payment Options

32%

31%

24%

68%

94%

68%

69%

76%

32%

6%

Debit Card

Credit Card

Direct Transfer

PayTM

BHIM / UPI

Since less than a year ago Since a year or more ago

Base: Those using these options. Source: AlphaWise, Morgan Stanley Research

Exhibit 185:Change in Usage of Digital Payment Options in Recent Months

25%

58%

71%

64%

72%

77%

63%

56%

10%

19%

13%

15%

15%

13%

17%

28%

64%

23%

16%

21%

12%

10%

19%

16%

Cash

Cheque

Debit Card

Credit Card

Direct Transfer

PayTM

PayTM QR code

BHIM

Increase No change Decrease

Base: Those using these options. Source: AlphaWise, Morgan Stanley Research

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Disclosure SectionThe information and opinions in Morgan Stanley Research were prepared or are disseminated by Morgan Stanley Asia Limited (which accepts the responsibility for its contents) and/or Morgan Stanley Asia (Singapore) Pte. (Registration number 199206298Z) and/or Morgan Stanley Asia (Singapore) Securities Pte Ltd (Registration number 200008434H), regulated by the Monetary Authority of Singapore (which accepts legal responsibility for its contents and should be contacted with respect to any matters arising from, or in connection with, Morgan Stanley Research), and/or Morgan Stanley Taiwan Limited and/or Morgan Stanley & Co International plc, Seoul Branch, and/or Morgan Stanley Australia Limited (A.B.N. 67 003 734 576, holder of Australian financial services license No. 233742, which accepts responsibility for its contents), and/or Morgan Stanley Wealth Management Australia Pty Ltd (A.B.N. 19 009 145 555, holder of Australian financial services license No. 240813, which accepts responsibility for its contents), and/or Morgan Stanley India Company Private Limited, regulated by the Securities and Exchange Board of India (“SEBI”) and holder of licenses as a Research Analyst (SEBI Registration No. INH000001105); Stock Broker (BSE Registration No. INB011054237 and NSE Registration No. INB/INF231054231), Merchant Banker (SEBI Registration No. INM000011203), and depository participant with National Securities Depository Limited (SEBI Registration No. IN-DP-NSDL-372-2014) which accepts the responsi-bility for its contents and should be contacted with respect to any matters arising from, or in connection with, Morgan Stanley Research, and/or PT. Morgan Stanley Sekuritas Indonesia and their affiliates (collectively, "Morgan Stanley").

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The following analysts hereby certify that their views about the companies and their securities discussed in this report are accurately expressed and that they have not received and will not receive direct or indirect compensation in exchange for expressing specific recommendations or views in this report: Anil Agarwal; Grace Chen; Ridham Desai; James E Faucette; Andrea Ferraz, CFA; Vasundhara Govil; Parag Gupta; Rahul Gupta; Subramanian Iyer; Toni Kaplan; Sumeet Kariwala; Nick Lord; Brian Nowak, CFA; Gaurav Rateria; Sheela Rathi; Tetsuro Tsusaka, CFA.

Unless otherwise stated, the individuals listed on the cover page of this report are research analysts.

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Important US Regulatory Disclosures on Subject Companies

The following analyst or strategist (or a household member) owns securities (or related derivatives) in a company that he or she covers or recommends in Morgan Stanley Research: Ridham Desai - Edelweiss Financial Services Ltd.(common or preferred stock), Kotak Mahindra Bank(common or preferred stock); James E Faucette - MasterCard Inc(common or preferred stock); Gaurav Rateria - Multi Commodity Exchange of India Ltd(common or preferred stock); Sheela Rathi - Edelweiss Financial Services Ltd.(common or preferred stock), Kotak Mahindra Bank(common or preferred stock), Multi Commodity Exchange of India Ltd(common or preferred stock).

As of August 31, 2017, Morgan Stanley beneficially owned 1% or more of a class of common equity securities of the following companies covered in Morgan Stanley Research: Amazon.com Inc, Axis Bank, Bank of Baroda, Bharat Financial Inclusion Ltd, Edelweiss Financial Services Ltd., Federal Bank, HDFC, HDFC Bank, ICICI Bank, Indiabulls Housing Finance, IndusInd Bank, LIC Housing Finance Ltd., MakeMyTrip Limited, MasterCard Inc, Multi Commodity Exchange of India Ltd, Naspers, Shriram City Union Finance Ltd, Shriram Transport Finance Co. Ltd., Visa Inc., Yes Bank.

Within the last 12 months, Morgan Stanley managed or co-managed a public offering (or 144A offering) of securities of Indiabulls Housing Finance, Kotak Mahindra Bank, MasterCard Inc, PNB Housing Finance Ltd, Punjab National Bank, Softbank Group, TransUnion.

Within the last 12 months, Morgan Stanley has received compensation for investment banking services from Alibaba Group Holding, IndusInd Bank, Kotak Mahindra Bank, MasterCard Inc, Naspers, PNB Housing Finance Ltd, Punjab National Bank, Softbank Group, TransUnion.

In the next 3 months, Morgan Stanley expects to receive or intends to seek compensation for investment banking services from Alibaba Group Holding, Amazon.com Inc, Axis Bank, Bank of India, DBS Group Holdings, EICHER MOTORS, Eicher Motors Ltd., Federal Bank, HDFC, HDFC Bank, ICICI Bank, ICICI Prudential Life Insurance, IndusInd Bank, Kotak Mahindra Bank, LIC Housing Finance Ltd., Mahindra and Mahindra Financial Services, MakeMyTrip Limited, MasterCard Inc, Multi Commodity Exchange of India Ltd, Naspers, PNB Housing Finance Ltd, Punjab National Bank, RBL Bank Limited, Shriram City Union Finance Ltd, Shriram Transport Finance Co. Ltd., Softbank Group, State Bank of India, TransUnion, Visa Inc., Yes Bank.

Within the last 12 months, Morgan Stanley has received compensation for products and services other than investment banking services from Alibaba Group Holding, Axis Bank, Bank of Baroda, Bank of India, DBS Group Holdings, HDFC, HDFC Bank, ICICI Bank, ICICI Prudential Life Insurance, IDFC Bank, Indiabulls Housing Finance, IndusInd Bank, Kotak Mahindra Bank, MasterCard Inc, Naspers, Softbank Group, State Bank of India, Yes Bank.

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Morgan Stanley & Co. LLC makes a market in the securities of Alibaba Group Holding, Amazon.com Inc, HDFC Bank, ICICI Bank, MakeMyTrip Limited, MasterCard Inc, Softbank Group, TransUnion, Visa Inc..

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The equity research analysts or strategists principally responsible for the preparation of Morgan Stanley Research have received compensation based upon various factors, including quality of research, investor client feedback, stock picking, competitive factors, firm revenues and overall investment banking revenues. Equity Research analysts' or strategists' compensation is not linked to investment banking or capital markets transactions performed by Morgan Stanley or the profitability or revenues of particular trading desks.

Morgan Stanley and its affiliates do business that relates to companies/instruments covered in Morgan Stanley Research, including market making, providing liquidity, fund management, commercial banking, extension of credit, investment services and investment banking. Morgan Stanley sells to and buys from customers the securities/instruments of companies covered in Morgan Stanley Research on a principal basis. Morgan Stanley may have a position in the debt of the Company or instruments discussed in this report. Morgan Stanley trades or may trade as principal in the debt securities (or in related derivatives) that are the subject of the debt research report.

Certain disclosures listed above are also for compliance with applicable regulations in non-US jurisdictions.

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Morgan Stanley uses a relative rating system using terms such as Overweight, Equal-weight, Not-Rated or Underweight (see definitions below). Morgan Stanley does not assign ratings of Buy, Hold or Sell to the stocks we cover. Overweight, Equal-weight, Not-Rated and Underweight are not the equivalent of buy, hold and sell. Investors should carefully read the definitions of all ratings used in Morgan Stanley Research. In addition, since Morgan Stanley Research contains more complete information concerning the analyst's views, investors should carefully read Morgan Stanley Research, in its entirety, and not infer the contents from the rating alone. In any case, ratings (or research) should not be used or relied upon as investment advice. An investor's decision to buy or sell a stock should depend on individual circumstances (such as the investor's existing holdings) and other considerations.

Global Stock Ratings Distribution

(as of August 31, 2017)

The Stock Ratings described below apply to Morgan Stanley's Fundamental Equity Research and do not apply to Debt Research produced by the Firm.

For disclosure purposes only (in accordance with NASD and NYSE requirements), we include the category headings of Buy, Hold, and Sell alongside our ratings of Overweight, Equal-weight, Not-Rated and Underweight. Morgan Stanley does not assign ratings of Buy, Hold or Sell to the stocks we cover. Overweight, Equal-weight, Not-Rated and Underweight are not the equivalent of buy, hold, and sell but represent recommended relative weightings (see definitions below). To satisfy regulatory requirements, we correspond Overweight, our most positive stock rating, with a buy recommendation; we correspond Equal-weight and Not-Rated to hold and Underweight to sell recommendations, respectively.

Coverage Universe Investment Banking Clients (IBC)Other Material Investment Services Clients

(MISC)Stock Rating Cate-

goryCount % of Total Count % of Total IBC % of Rating Category Count % of Total Other MISC

Overweight/Buy 1164 36% 306 41% 26% 555 37%Equal-weight/Hold 1425 44% 349 46% 24% 701 46%

Not-Rated/Hold 61 2% 6 1% 10% 10 1%Underweight/Sell 606 19% 91 12% 15% 242 16%

Total 3,256 752 1508

Data include common stock and ADRs currently assigned ratings. Investment Banking Clients are companies from whom Morgan Stanley received investment banking compensation in the last 12 months. Due to rounding off of decimals, the percentages provided in the "% of total" column may not add up to exactly 100 percent.

Analyst Stock Ratings

Overweight (O). The stock's total return is expected to exceed the average total return of the analyst's industry (or industry team's) coverage universe, on a risk-adjusted basis, over the next 12-18 months.

Equal-weight (E). The stock's total return is expected to be in line with the average total return of the analyst's industry (or industry team's) coverage universe, on a risk-adjusted basis, over the next 12-18 months.

Not-Rated (NR). Currently the analyst does not have adequate conviction about the stock's total return relative to the average total return of the analyst's industry (or industry team's) coverage universe, on a risk-adjusted basis, over the next 12-18 months.

Underweight (U). The stock's total return is expected to be below the average total return of the analyst's industry (or industry team's) coverage universe, on a risk-adjusted basis, over the next 12-18 months.

Unless otherwise specified, the time frame for price targets included in Morgan Stanley Research is 12 to 18 months.

Analyst Industry Views

Attractive (A): The analyst expects the performance of his or her industry coverage universe over the next 12-18 months to be attractive vs. the relevant broad market benchmark, as indicated below.

In-Line (I): The analyst expects the performance of his or her industry coverage universe over the next 12-18 months to be in line with the relevant broad market benchmark, as indicated below.

Cautious (C): The analyst views the performance of his or her industry coverage universe over the next 12-18 months with caution vs. the relevant broad market benchmark, as indicated below.

Benchmarks for each region are as follows: North America - S&P 500; Latin America - relevant MSCI country index or MSCI Latin America Index; Europe - MSCI Europe; Japan - TOPIX; Asia - relevant MSCI country index or MSCI sub-regional index or MSCI AC Asia Pacific ex Japan Index.

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