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Safeguarding Digital Transformation:Understanding the Digital Impact on Banking Business Models and Risk Management

December 2017

POINT OF VIEW

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Introduction

The adoption of digital technology in the banking industry is shifting the economic fundamentals of the market, giving rise to a widening gap between business aspirations and operational reality in the sector. Incumbent banks’ legacy systems and infrastructure are often incompatible with the rapidly evolving digital landscape. Banks’ supply chains have become more complex through a process of digitalisation, which challenges the capability and integrity of banks’ controls and oversight. The rise of non-bank market participants broadens the provision of banking services beyond the reach of industry regulators.

These market dynamics contribute to a changing mechanism through which risks emerge, intensify and spread. The net outcome is heightened vulnerability to conduct risks and financial crime, greater inter-dependency between financial and non-financial risks and a potential threat to financial stability at an organisational and systemic level.

Almost a decade has passed since the beginning of the global financial crisis. The overriding focus for many firms throughout this time has been on coping with more stringent regulations. Regulators have sought to raise standards, conduct and prudential across the board, while implementing new resolution mechanisms. Within the EU Single Market, for example, the financial industry witnessed what has been referred to as a regulatory tsunami wave: CRD III and IV, AIFM, EMIR, MiFID 2, the revised Deposit Guarantee Scheme – and the list goes on.

The aim of policymakers, naturally, was to ensure a more sound and resilient financial sector. Achieving a greater degree of financial stability became the key regulatory driver. But too much stability, in the shape of too much regulation, risked choking innovation and profitability. Regulators needed to strike a balance.

The impact of post-crisis regulation has been good in parts but less so in others. Financial stability has been for the most part achieved. The global banking industry is much more liquid and well capitalised: the industry’s tier-1 capital ratio climbed to a ten-year high in 2016, while the loan-to-deposit ratio fell to the lowest in decades. Other measures such as low market volatility since the crisis further support the assertion that the financial system is stable to a large degree.

But a decade of prudential enhancements has had an adverse effect. A combination of high capital thresholds and low interest rates as a response to the global financial crisis has undermined banks’ profitability. The heavy compliance and litigation burden has distracted banks from seeking new avenues of growth. This at a time when new competitive threats have emerged from niche FinTech players, big technology (BigTech) companies and incumbents from adjacent industries.1

New banking reality

1 McKinsey, Remaking the banking for an ecosystem world, October 2017.

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The facts bear this out – the banking industry’s revenue growth over the past two years dropped below 3% – half of the average growth rate registered between 2010 and 2015. Profitability has also declined since 2015, despite significant cost reduction efforts. Investors are doubtful of the industry’s future potential. The average PE ratio of banking incumbents – an indicator of investor expectations of future earnings – has barely shifted since 2010 and is nearly 50% lower than other industries.

The impact of subdued financial performance is not only on shareholders and markets, but also on end-users, the corporate and retail clients who rely on access to a wide array of banking services which support activity in the wider economy.

Banking performance: a financial overview

3

15

PE

Rat

io

2

10

15

0 0

4

20

%

5

25

6

30

7

8

9

Subdued revenue growth RoE declined over recent years, despite cost reduction

Banking lags other industries in value creation

2012 2014

6.0%

4.8%

7.0%

6.0%

2.7%

Banking

Other industries

2013 20102014 2015 20172016 2016

Source: McKinsey Global Banking Review 2017

2014RoE:9.6%

Margin

Risk costCost

EfficiencyFines & others

0.1%

1.6%-0.6%

-0.6%

-1.5%

Capital

2016RoE:8.6%

21.8

13.0

-40%

-48%

27.5

14.2

52 Finextra, HSBC to slash jobs and overhaul IT, 09 June 2015.

Time for a paradigm shift

The status quo is not sustainable. Banking incumbents need to grow their top line, rescue their margins, and restore investor confidence. This triple mandate is looking increasingly challenging given the traditional and enduring business and operating models in banking.

Without re-configuring their operating models, banks are exhausting easy options for efficiency gains. The industry’s digitalisation, to date, has focused on streamlining customer interactions (e.g. providing self-service customer banking models) and substituting back-office activities with computerised efficiency (e.g. automating mundane processes). The low-hanging fruit would appear to be running out.

Without re-imagining their business models, striking the balance between seeking new growth and improving legacy business will be harder. Over-commitment to the legacy business is becoming riskier due to the shortening of product and business lifecycles, an increased speed of market collapse and the existence of more non-traditional competitors. Exploring new growth opportunities is also getting trickier. In the digital world, what is “new” is appearing, maturing and being monetised faster than ever before, thanks to collaborative approaches to innovation, faster scaling driven by platforms and contracting-for-everything models.

The impetus for banks to realise that transformation – profound changes to business activities, processes and models using digital technologies and capabilities – is pervasive.

Early movers are seeing the benefits. HSBC embarked on an end-to-end digital transformation in 2015. Through re-platforming all its IT mainframes, the bank removed 750 legacy systems to create an end-to-end digitisation of its branch network alongside online and mobile offerings. The digital transformation is expected to unlock $5 billion of savings across the bank and lays the foundation for HSBC to leverage its global scale.2

More and more leading banks are embarking on wholescale digital transformation to get a foothold in the next phase of digital banking. But two key questions remain to guide successful transformation efforts. Where and how does digital re-set banking economics? And how will the risk agenda change as a result of digital transformation?

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Where and how does digital re-set banking economics?

The World Economic Forum (WEF) described the impact of technology on financial services as having “materially changed the basis of competition”, but having “not yet materially changed the competitive landscape”.3 That is, while technology lends new-comers a competitive edge, the economic fundamentals of the banking industry, such as high barriers to entry and economies of scale and scope, cannot be overcome yet.

This has been true to date. But, as key technologies reach a critical mass in adoption, digital is starting to reshape the foundation of banking economics. The coming of age of big data analytics, Cloud computing, artificial intelligence and blockchain all have the power to drive the next wave of bank transformation.

3 World Economic Forum, Beyond FinTech: A pragmatic assessment of disruptive potential in financial services, August 2017. 4 App Developer Magazine, More data will be created in 2017 than the previous 5,000 years of humanity, 23 December 2016. 5 Forbes, Big data: 20 mind-boggling facts everyone must read, 30 September 2015.

Data is said to be the oil of the 21st century. A major trend over recent years has been the meteoric rise in the volume of data generation, discovery and refinement. More data will be created in 2017 than in the previous 5,000 years.4 By 2020, about 1.7 megabytes a second of new information will be created for every human being on the planet.5 The rising volume and variety of data enable new possibilities of correlations. This, combined with advanced analytics, gives data a greater monetary value.

Analytics has become the entry ticket to digital finance. Many FinTech start-ups have predicated their business models on this and have successfully established themselves in the heart of retail banking. But the real threat to incumbents will likely be from the likes of Amazon and Google: BigTech platforms with the investment capacity and data architecture that can drive insight on scale. In stark contrast, the legacy IT estate is often an incumbent bank’s Achilles’ heel in the age of digital banking. As data is trapped in siloes and cannot be interrogated easily, banks are inevitably missing opportunities as a result of not being able to drive insight from the big data within their own systems.

Amount spent on data-related programmes by financial firms

in 2015

Amount such spending is to expected to rise to in 2019

Source: Accenture, 2017

$6.4 Billion

$16 Billion

Potential saving that G-SIBs could make per year

through adopting simplified data repositories and new

analytics methods to generate regulatory reports

Source: McKinsey, 2017

$1 Billion

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The Cloud is re-defining the agility and scalability of banking operations. It radically reduces the need for upfront investment to run any business by moving technology platforms from dedicated in-house facilities to those hosted by a third-party infrastructure provider with an extensive network of data centres. This shifts the cost structure of data and tech-intensive industries, banking included, and enables on-demand scalability and a spectrum of “as a service” business models.

Artificial Intelligence (AI), a category encompassing multiple technologies that use algorithms to sense, comprehend and act, is catalysing productivity in the industry. The effect is akin to that of employing more people or investing more in capital, except that unlike traditional productive factors that depreciate over time, AI improves itself with data – “data is to AI what food is to humans”.6

Banks with more than $1bn in assets could improve returns on tangible common equity by 20 to 40 basis points following

migration to the Cloud

Source: Strategy&, 2016

20-40Basis Points

It takes artificial intelligence 1/4 second to reconcile a

failed trade vs. 5–10 minutes by a human

Source: BNY Mellon, 2017

Blockchain, a decentralised digital network that enables transactions safely and without the need for a trusted central party, captures the essence of disruption. A mechanism that engineers trust by design, Blockchain sidesteps the need for institutions in the business of being the “middle man” – banking included – and can pose existential threat to traditional banking business models. Potential disruption aside, the possibility of sharing a common ledger across financial institutions could also radically reduce the cost of financial intermediation – something that hasn’t changed for the past century.7

30%Potential reduction to bank

infrastructure costs by blockchain adoption

Source: Accenture, 2017

6 Accenture, Why artificial intelligence is the future of growth, 2017. 7 Philippon, T., Has the U.S. Finance Industry Become Less Efficient? On the Theory and Measurement of Financial Intermediation, September 2014.

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Barriers to participation in banking are being eroded by the advent of Cloud processing. Economies of scale and scope will be increasingly centred on data collection and use. New frameworks of financial intermediation are emerging with Blockchain. These factors, individually and collectively, force the future of banking away from the traditional banking model predicated on rates and fees from financial intermediation.

At the same time, the regulatory push for openness in banking is becoming a global trend. On January 13th 2018, the Second Payment Services Directive (PSD2) will become law in the EU. PSD2 requires banks to open up their Application Programming Interfaces (APIs) to facilitate third-party partners’ access to bank customers’ data (with consent). In the UK, the Competition and Markets Authority (CMA) is going a step further with Open Banking to transform banks from a one-stop-shop of financial services to open platforms hosting a range of financial services providers. Open Banking also enables third parties, rather than incumbent banks, to become the owners of primary customer relationships. These changes will likely decouple banking products from their distribution and propel banks’ pivot to platform strategies – we outline three below.

Whichever platform strategy incumbents choose to adopt, they will need to repurpose their activities. On top of the existing focus of financial intermediation, banks may need to define rules of how they engage with the ecosystem, intermediate capabilities offered on their platforms, and explore strategies to monetise proprietary IP and data. The operational model and technology architecture to support this business aspiration will likely be radically different from the operating reality of today.

DescriptionModel

The ability to open up access to a bank’s software system to third parties. This enables programmatic integration between third party applications and a bank’s internal applications via bank-grade security and standards.

The prospect of banks offering certain capabilities in a programmatic fashion to enable third parties to deliver their own financial products or services.

The potential for a bank to create a digital place hosting third parties who demonstrate and sell their products and services to the bank’s customers.

Integrate to a service the bank needs or open up greater choices for its customers through programmatic integration.

Establishing access, volume, and pricing policies.

Exploring new non-interest income revenues and identifying economies of scale in delivering existing capabilities.

Defining the rules of engagement (e.g. vendor selection and monetisation), data security and privacy, and the level of technology integration.

Offer AML/KYC or secure data storage capabilities or software licensing in trade finance to FinTech players, other banks, or non-banks.

Banking app store, service match-making, financial services comparison platform.

Case examples Strategic focus

Types of platform strategies for banks

Banking as a service

Banking as a marketplace

API banking

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How digital changes the banking risk landscape?

A full-scale transformation is key to remaining competitive in the next phase of digital banking. But as re-imagined business and operating models open up new opportunities, so they also contribute to a changed mechanism through which risks emerge, intensify and spread, with the net outcome being heightened non-financial risks and greater inter-dependency between different risk types.

Multi-speed IT organisations: legacy systems not meeting the new digital demands

Changing consumer preferences have been a primary driver of the banking industry’s digitalisation. Consumers expect a similarly seamless experience from banking as they would from other aspects of their lives, such as shopping or travelling. This has given rise to a greater need to adopt new technologies at pace in retail banking, with initiatives such as online banking, mobile apps, and smart ID. To date, these digital innovations have largely been executed in an “add-on” manner. New digitally-enabled capabilities are plugged into banks’ legacy systems and architecture. These legacy IT estates require a significant amount of ongoing investment to maintain, are often not agile enough to underpin new technologies or compete in terms of costs, and cannot be transformed into digital platforms easily.

The net effect is a “decoupling” of digital maturity between the innovations on the consumer-facing side of banking and the day-to-day running on the institutional side. This leaves banks between a rock and a hard place when it comes to digital transformation. Significant risks are associated with both the status quo and in the case for change. A “multi-speed IT” within the bank creates an ongoing vulnerability: particular concerns are around cyber-attacks and threats to customer data privacy and security. Upgrading to “new” technology and more advanced platforms carry risks of disruption too, as well as the strategic risks associated with the mis-timing of the digital development.

A regulatory framework, primarily borne out of the legacy age, struggles to adapt to the digital banking landscape. This is highlighted by the current debate over the asset class of cryptocurrency. The mixed signals currently emanating from financial regulations create further uncertainty. For example, regulations scrutinising data and technology use and those promoting competition and market entry pose a key source of tension. In Europe, the upcoming General Data Protection Regulation (GDPR) could impose an eye-watering fine of up to 4% of firms’ global revenue in the case of a data breach. Yet incumbent banks are mandated to provide access to their current accounts under PSD 2, therefore introducing greater vulnerability to data security. More generally, these also add to the alphabet soup of regulations that are already compressing incumbents’ margins.

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A network of financial activities: banking supply chains outgrowing banks’ oversight

Platform strategies are key to harnessing incumbent banks’ proprietary capabilities and customer relationships to drive new sources of income. But these would require banks to evolve from “institutions of finance” to “networks of financial activities”.

But as banks’ ecosystems grow, so will their definable risk landscape. A proliferation of risks from different types of providers heightens the third- and fourth-party risks banks will face. These risks may not be proportionate to the size of the supplier or the size of the bank’s balance sheet either – greater institutional interdependencies mean that small service providers could have an amplified impact on financial stability.

Cyber risk is probably the most prominent form of threat to the financial system. Not only are cyber-attacks growing in number and sophistication, but they also spread more rapidly in the expansive and vested network of the banking industry. According to IBM, the financial sector was attacked 65% more frequently than any other sector in 2016, resulting in more than 200 million records being breached, a 937% increase over 2015.8 Lloyd’s of London estimates that a single global cyber-attack could result in as much as US$121 billion of financial loss.9

Given the extensive supply chains in banking, global protocols will be key to building cyber resilience. This requires a common definition and measurement of financial firms’ cyber vulnerability, such as the classification of data breach and the quantification of loss to cyber-attacks. A globally accepted regulatory framework of cyber will also be crucial to prevent arbitrage in data regulations.

Risk symbiosis in FinTech: financial stability concerns migrating from the technology sector

The symbiotic relationship between finance and technology is core to the next phase of digital banking. This presents new opportunities for collaboration, but also vulnerabilities of risk correlations. The speed of technology advancement and the market concentration among technology providers, in particular, pose stability concerns to the financial system.

Institutional interdependencies and risk correlations are central to financial crises and market crashes. Technology advancement accelerates the speed at which risks could spread across the financial system. The Flash Crash in 2010 was an example of this: triggered by an automated algorithmic trade, US stocks and futures markets saw a 10% fall in market value in a matter of minutes, only to recover hours later.10

9 The Guardian, Lloyd’s says cyber-attack could cost $120bn, same as Hurricane Katrina, 17 July 2017. 10 The Economist, One big, bad trade, 1 October 2010.

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11 Fortune, Amazon still leads Cloud rankings, but competitions is coming on strong, 15 June 2017.

The speed of trading in markets has been ramped up significantly since 2010 driven by a quantum shift in the computing power used in automated trading operations. The prospect for algorithms to cause market volatility or to crash markets has become far more significant. In its latest report, the Financial Stability Board (FSB) highlighted that the lack of transparency and auditability of AI algorithms in trading poses macro-level risks, particularly as many AI models are being trained during a period of low market volatility. Applications of AI could also result in new and unexpected forms of interconnectedness between financial markets, for instance, based on the use of previously unrelated data sources in designing trading and hedging strategies. Monitoring macro-financial risks that emerge from FinTech activities is therefore a priority for both financial firms and their regulators.

Another potential threat to financial stability relates to market concentration among technology providers. A strong network effect and first-mover advantage common in the technology sector reinforces a winner-takes-all dynamic. “Word of mouth” and scalability of new technologies mean that solutions are increasingly being offered by a few large technology firms. This could heighten third-party dependencies already prevalent in the financial sector, and trigger systemic risks if a large technology provider were to face a major disruption or insolvency. In Cloud, this financial stability concern is particularly prominent: the three largest Cloud infrastructure providers occupy nearly two thirds of the Infrastructure as a Service market; Amazon Web Services alone have a share of 40%.11

Systemic risks to financial stability can be difficult to detect and quantify from the perspective of firms and financial regulators. It is not inconceivable that the next financial crisis may emerge from the technology sector. This calls for the harmonisation of technology standards and a greater regulatory coordination across industries to safeguard financial stability.

A Call for Action – Digital transformation as a necessity

The foundation of banking economics is shifting with digital. Barriers to participation in banking are being eroded by the advent of Cloud based applications and services. Economies of scale and scope will be increasingly centred on data collection and use. New frameworks of financial intermediation are emerging with Blockchain. These factors, individually and collectively, are catalysing a shift away from the traditional banking models predicated on rates and fees from financial intermediation, towards platform models that drive new incomes from banks’ trusted customer relationships, proprietary data and capabilities.

A full-scale transformation – profound changes to business activities, processes and models using digital technologies and capabilities – is key to sustainability over the longer term. The forward-looking agenda should highlight the impact of digital transformation on the banking industry’s risk landscape. The emphasis for banking incumbents and regulatory bodies will be on non-financial risks, including technology risk, cyber security, data privacy and digital conduct. To address this emerging risk landscape requires a reconfiguration of banks’ operating models as well as a more globalised regulatory approach to digital financial services and the impact of FinTech.

To safeguard their organisations through the digital transformation journey, incumbent banks need to close the gap between their digital banking aspirations and the reality of their legacy IT estates. There are some no-regret moves to get banks started: reducing reliance on legacy systems; de-cluttering and decommissioning redundant systems; and using analytics to provide modelling on key non-financial risks. But to fully harness the power of digital, incumbents may need to re-build the technology architecture and re-design their operating models. In fact, launching an entirely new, digital bank alongside the legacy bank may be necessary, so might be the integration of global scalability in operating models to harness the benefits of implementing key technologies such as the Cloud on a supranational basis. Regardless of the path chosen, the digital transformation of banks is both inevitable and necessary. Those that embrace a transformation agenda and manage the inherent risks that come with that are likely to be the banks that thrive in the longer term

At Parker Fitzgerald, we help clients through each stage of their digital transformation journey. This includes ensuring that clients understand how future regulations can affect their digital transformation strategies, how key technologies such as AI, Blockchain and the Cloud can be safely adopted within their operating models, and how their risk frameworks can be adapted to take account of new risks and threat vectors arising from cyber and technology risk, as well as data privacy and protection considerations amplified by PSD2 and GDPR.

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Kuangyi Wei is Parker Fitzgerald’s Head of Strategic Research. In her role Kuangyi leads the firm’s Strategic Research programme, working in close collaboration with the Advisory Board, the Managing Partner and senior leaders. Kuangyi also leads Parker Fitzgerald’s engagement with industry groups, regulators and policymakers.

Prior to joining Parker Fitzgerald, Kuangyi has held various research roles at both policy think tanks and commercial organisations, including Chatham House, the State Council of China and Accenture. Her roles focused on offering strategic content and advisory for C-level executives and senior government officials. Most recently, Kuangyi was a Principal Researcher at Accenture’s internal think tank, responsible for authoring the company’s flagship publications at the World Economic Forum in Davos and leading cross-industry thought leadership programmes.

Kuangyi is a published author at leading business and academic journals including Harvard Business Review and Business Economics. Kuangyi holds an MPhil in Economics from the University of Oxford, where she specialised in theory and policy relating to competition and regulation.

About the authors

Kuangyi Wei Head of Strategic Research Parker Fitzgerald Group

Matthew is a Partner at Parker Fitzgerald, leading the firm’s Global Solutions Group, who solve our clients’ most complex problems through the innovative application of technology.

He has responsibility for the definition of the Solutions service offering including Parker Fitzgerald’s multi-client Cloud utilities.

Matthew has more than 20 years’ experience in designig and delivering risk technology solutions to Tier-1 and Tier-2 investment banks, global insurers, commodities houses, hedge funds and large institutional asset managers.

He brings practical experience of the esoterica of the financial markets and risk technology, including industry standards and best practice, in addition to designing and implementing risk and trading systems change.

Matthew holds a BSc in Mathematics and Physics from Durham University.

Matthew Hayday Parter - Solutions Parker Fitzgerald Group

Michael is a Partner at Parker Fitzgerald, leading the firms Transformation practice in offering a unique blend of entrepreneurial thinking and deep risk and regulatory expertise to empower established businesses to become the financial institutions of the future.

He has over a decade of experience in helping complex organisations adopt smart solutions through a combination of regulatory efficacy, new technology, partnerships and best practice operating model design. His clients include Global Tier 1 Banks who value the depth that his risk and regulatory expertise brings to help them ensure the integrity of their control framework as they transform.

Michael has taught at several leading universities including Warwick, as well as Cambridge’s Judge Business School where he taught entrepreneurial skills to PhD students.

Michael has a number of advanced qualifications including a BSc(Hons) in Neuroscience and an MSc in Human-Centred Computer Systems. He is a published academic in the field of Human Computer Interaction and regularly appears in the national press, financial services publications and at industry conferences.

Michael Soppitt Partner - Transformation Parker Fitzgerald Group

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Parker Fitzgerald is a strategic advisor and consulting partner to the world’s leading financial institutions and regulatory authorities.

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Disclaimer The information contained in this document has been compiled by Parker Fitzgerald and includes material which may have been obtained from information provided by various sources and discussions with management but has not been verified or audited. This document also contains confidential material proprietary to Parker Fitzgerald. Except in the general context of evaluating our capabilities, no reliance may be placed for any purposes whatsoever on the contents of this document or on its completeness. No representation or warranty, express or implied, is given and no responsibility or liability is or will be accepted by or on behalf of Parker Fitzgerald or by any of its partners, members, employees, agents or any other person as to the accuracy, completeness or correctness of the information contained in this document or any other oral information made available and any such liability is expressly disclaimed. © 2017 Parker Fitzgerald

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