Macro Stress Testing and Resilience Assessment of Indian Banking

Macro Stress Testing andResilience Assessment of

Indian Banking

Pami DuaDirector, Delhi School of Economics

Chairperson, Research CouncilDean, Academic Activities

University of Delhi

October 20, 2016

Objective

Background

Four Pronged Strategy

Macro Stress Testing (MST)

Resilience Assessment (RA)

Empirical Model

Data and Methodology

Estimation Results

Policy Implications

20-Oct-16 2Macro Stress Testing and Resilience Assessment of Indian Banking

To conduct Macro Stress Testing (MST) and examine resilience of the Indian Banking Sector to various shocks

How a shock is expected to impact stability of Banking Sector measured by Financial Soundness Indicators

320-Oct-16 Macro Stress Testing and Resilience Assessment of Indian Banking

Episodes of Financial Crises highlighted

expanding role of Macro-Prudential Policy which:

Captures interrelationship between financial institutions,

financial sector and the economy

Reflects macro-financial links or channels and

Has implications for banking sector regulations


Background (past episodes) . . 1/7

Financial Stability (FS) is now an added objective in

monetary and macroeconomic policy (one of the statutory

objective of central banks) across the world:• Requires policymakers to incorporate macro-financial channels for

formulation of any successful monetary policy

• To ensure FS, Macro Stress Testing (MST) and Resilience Assessment (RA)

are integral part of macro-prudential tools

• Since banks are more vulnerable to deterioration in the overall macro-

financial environment due to adverse impact of shocks, maintaining

resilience to risk and shock is an integral part of bank management, bank

regulation and supervision.


Background (Financial Stability) . . 2/7

Role of Regulators: BASEL Norms• Basel Committee on Banking Supervision (BCBS) set up by the Bank of

International Settlements (BIS) proposed the BASEL accord in 1988

• Accord prescribed a set of minimum capital requirements of 8% for

banks to reduce credit (default) risk -- BASEL I international norms

• BASEL II and III upgraded BASEL I norms and involved the buildup of

banks’ resilience to shocks by maintaining additional Capital

Conservation Buffers (CCB), thereby ensuring both quantity and quality

[total (k) and Tier I (k1)] of capital adequacy by banks.


Background (BASEL Norms) . . 3/7

Capital Adequacy Ratio: Ratio of Capital to Risk Weighted Assets

KAR = K/RWA

K = Tier 1 K + Tier 2 K

Tier 1 K (k1): Core Capital -- component of regulatory capital which is considered to be of the highest quality because it is fully and readily available to cover losses. It mainly comprises share capital and disclosed reserves.

Tier II K (k2): Additional or Supplementary Capital over and above Tier I. It comprises certain reserves and types of subordinated debts.


Background (Capital Adequacy Ratio) . . 4/7

Risk Weighted Assets are weighted sum of assets: prescribed risk

weights are assigned to different types of assets according to

BASEL norms:

RWA = 0%*Bucket 1 + 20%*Bucket 2 + 50%*Bucket 3 + 100%*Bucket 4

Bucket 1, 2, 3 and 4 indicate assets with zero, low, medium and high

default risk with weights (0, 0.2, 0.5, 1) respectively

Capital Conservation Buffer (CCB) provides additional capital

buffer to enable banks to meet unexpected losses due to shocks

without breaching the minimum 8% KAR norm.


Background (Capital Adequacy Ratio) . . 5/7

9

BASEL I(International

norm)

BASEL II(International

norm)

BASEL II( Current RBI

norm)

BASEL III(International

norm as on 1.1.2019)

BASEL III(RBI norm as

on 31.3.2018)

1 Minimum k 8 8 9 8 9

2 Minimum k1 - 4 6 6 7

3 Maximum k2 - 4 3 2 2

4 CCB - - - 2.5 2.5

5 K + CCB 8 8 - 10.5 11.5


BASEL Norms for Total & Tier 1 Regulatory Capital Adequacy Ratio


BASEL* I (1988,94) II (2006,08) III (2019,18)

International 8 8 (4+4) 8 (6+2)+2.5India 8 9 (6+3) 9 (7+2)+2.5

BASEL I (International, Indian) =(1988, 1994)

BASEL II (International, Indian) =(2006, 2008)

BASEL III (International, Indian) =(2019, 2018)

8 = Total KAR (k)

4+4 = Tier I K (k1) + Tier II K (k2), introduced in BASEL II

6+2 = Tier I K (k1) + Tier II K (k2), modified in BASEL III

2.5 = CCB introduced in BASEL III.

BASEL III requires 10.5% KAR = Total ( Tier I (k1) + Tier II (k2)) + CCB = 8 (6+2) + 2.5


BASEL Norms for Total & Tier 1 Regulatory Capital Adequacy Ratio


An integrated approach using scenario analysis for India to conduct–

• Macro Stress Testing (MST)

and

• Resilience Assessment (RA)

of Indian Banking in compliance with BASEL II and III



Figure 1 : Four Pronged Strategy (MST & RA)

Conduct Resilience Assessment (RA)

STEP 1: Identification of a shock/stress event and Scenario AnalysisBased on Historical and/or Hypothetical Scenarios

(Mapping the impact of stress event on key macroeconomic variables)

STEP 2: (Empirical) Macro-financial Model

(Mapping the impact of stressed macroeconomic variables on Bank credit quality indicator)

STEP 3 : Examine Impact on Expected Banking Losses

STEP 4: Examine Impact on Financial Soundness Indicator (as per BASEL norms)

ConductMacro Stress Testing(MST)


Figure 2: A Simple Sketch of MST & RA Framework

Initial shock/Adverse macro-economic scenario(Historical or Hypothetical)

Macro-econometric

Model

Impact on macro

economic variable

eg. Slow down in output,

rise in unemployment

Macro Credit Stress

Testing Model

Borrower default and

credit quality

deterioration

Mapping defaults into

(expected) Credit Loss

Impact on Balance Sheet

in terms of Profit and

Capital

Threshold for Bank failurein terms of

BASEL Norms

Internal Rating based

approach

Resilience Assessment

Examine impact of Policy-based shocks and other external shocks on credit quality of banks to conduct MST and RA

Model Probability of Default as a measure of Credit Quality as a function of key macroeconomic variables.

Conduct Scenario Analysis based on simulation experiments of a SMEM for India - Historical scenarios and two types of Hypothetical scenarios (moderate and severe). Historical Scenarios explicitly capture the impact of policy measures and other

external shocks on the economy’s growth rate using a model which incorporates sufficient policy levers and global transmission channels for an integrated economy.

Assess the resilience of the Indian banks to shocks by examining the impact of stressed credit quality (due to shocks) on the KAR (total and Tier I).


Application to India – MST and RA .. 1/6

STEP 1. Designing of Scenarios

Historical:‘A SMEM For INDIA’, Dua and Kapur (2015)

Hypothetical:Zeman and Jurca (2008), NBS (Type I)FSR, RBI on MST (Type II)

STEP 2. Model

Macroeconomic credit risk model- based on Wilson (1997)

PD = f (output growth, inflation rate, interest rate, exchange rate)



EMPIRICAL MODEL:

Expected impact of Variables included in the analysis on NPA ratio (N)

16

Indicator Variable Name Expected Sign

1. Cyclical y -

2. Price Stability π or m -

3. Financial i +

4. External e -/+

N = f (y, m, i, e).



Source : Sample data 1997Q2 - 2013Q2

STEP 3. Estimation of credit risk losses

17

𝑪𝑳𝒕+𝟏 = 𝑵𝒕+𝟏 × 𝑳𝑮𝑫𝒕 × 𝑬𝑨𝑫𝒕 (2)


Credit losses are calculated in period t+1 given the estimated NPA ratio (obtained in step 2 as an estimate of probability of default due to stressed GDP growth rate due to shock) , loss given default (assumed in period t) and exposure at default in period t (which is loan amount outstanding over and above NPAs in period t, exposed to default).


STEP 4. Impact on the KAR

18

𝒌𝒕+𝟏 = 𝑲𝒕 + 𝒑𝒓𝒐𝒇𝒊𝒕𝒕+𝟏 − 𝑪𝑳𝒕+𝟏

𝑹𝑾𝑨𝒕 − 𝜟𝑵𝑷𝑨𝒕+𝟏 (𝟑)


Finally, KAR (k) is calculated using total capital, profits net of credit losses (calculated in step 3) divided by RWA net of changes in NPAs. Similarly, calculation of Tier I (k1) is also done by just replacing total capital by Tier I capital in the numerator.


PD = avg % of obligers that default (N)

LGD = % of exposure that bank might lose in case of default by borrower(0<LGD<100%)

Under Basel II, Internal Rating Based (IRB) approach, we have two options: (a) Foundation IRB (FIRB), in which we model PDs, while LGD and EAD are given and (b) Advanced IRB in which banks estimate all inputs, i.e., PD, EAD as well as LGD.

We assume FIRB and LGD =100% (a prudent assumption)

EAD = estimate of the amount outstanding in case borrower defaultsNPA = amount (principal) or interest is overdue for at least 90 daysNPA ratio (N) = Gross NPAs / Gross advances

KAR = K/RWA

K = Tier 1 K + Tier 2 K

RWA = 0(B1) + 0.2(B2) +0.5(B3) +1(B4)



Reserve Bank of India Ministry of Statistics & Programme

Implementation IMF International Financial Statistics (IFS) OECD Statistics CMIE monthly Bulletin on Indian Economy.


Data Sources

Unit Root Tests: All series are I(1) or non-stationary.

VEC Model: Cointegration exists between NPA ratio, growth rate ofIndian GDP, growth rate of broad money supply (M3), interest rate(nominal GS 10 yield rate) and exchange rate (nominal vis-à-vis USD).All signs conform to expectations.

Granger Causality: Null of no Granger causality from the factors to NPAratio is significantly rejected at 1% level for all the variables.

Generalized impulse response functions reveal that shocks to allvariables affect the NPA ratio.

Normalized generalized variance decompositions suggest thatimportant determinants of NPA ratio, in decreasing order ofimportance, are as follows: GDP growth rate, money growth rate,exchange rate and interest rate.


Estimation Results

N = f (y, i, m, e)

22

𝑵−𝟏 = −𝟏. 𝟑𝟔𝟎𝐲−𝟏 + 𝟎. 𝟓𝟏𝟒𝒊−𝟏 − 𝟎. 𝟖𝟐𝟑𝒎−𝟏 − 𝟎. 𝟒𝟑𝟖𝒆−𝟏 + 𝟒𝟕. 𝟖𝟔𝟐


Long run relationship in the VECM

Results on Scenario Analysis


Impact Analysis of Macro Credit Stress Testing Impact of stressed economy’s growth rate on NPA ratio

Impact Analysis of Resilience of Indian Banking Sector Impact of stressed NPA ratio on total KAR (k) and Tier I (k1).


Policy Based & External Shocks

A Monetary Policy shock (say, an ↑ in Repo rate impulse (one time) shock reduces the real GDP growth rate (based on simulation experiments of SMEM; Historical scenarios) initially in 2010-11 to 7.91% as compared to baseline scenario at 8.13% and then increases relative to baseline to sustain growth rate to levels prior to the shocks in around two years. The slowdown in economy’s growth rate causes an increase in NPA ratio (N), i.e. Credit Quality worsens.

A step (sustained or permanent hike) shock, however, is expected to be more effective and adversely impacts the growth rate in economy. The impact on N is also more adverse for a step shock.

25

SCENARIOS POLICY-BASED SHOCKS

Year Baseline

(1)

Monetary Policy

(2)

y N y N

2010-11

8.13

7.449 Impulse 7.91

Step 7.91

7.748

7.748

2011-12

6.06 9.457 Impulse 6.09

Step 5.78

9.416

9.838

2012-13 6.67 8.078 Impulse 6.69

Step 6.40

8.051

8.445


Monetary Policy Shock:Impact Analysis of Macro Credit Stress Testing

Note: k denotes (total) capital risk weighted asset ratio and k1 denotes tier 1 capital risk weighted asset ratio.

* Based on a more severe shock for 4 quarters at a stretch (2011Q1-Q4).

26

SCENARIOS POLICY-BASED

BaselineMonetary Policy Shock

Impulse Step

k k1 k k1 k k1

One Year Horizon

2010-11 13.4 8.38 13.1 8.11 13.1 8.11

Two Year Horizon

2011-12 11 6.32 11.1 6.36 10.7 5.94

Three Year Horizon

2012-13 10.8 6.74 10.8 6.77 10.4 6.38


Monetary Policy Shock:Impact Analysis of Resilience of Indian Banking Sector

Results indicate the estimated total KAR (k) and Tier I KAR (k1) due to policy based shocks.

Estimated values are compared to current BASEL II norms for stability (referred to as Financial Soundness Indicators) for k & k1 to 8 % & 4 % as per international standards; and 9% & 6% as per Indian (more stringent) standards.

Overall, Indian banks meet these norms as per current BASEL II requirements.

However, if we compare the estimated values to even higher forthcoming BASEL III norms, then Indian banks are marginally constrained in meeting Tier I KAR by Indian standards.


The external price shock (hike) causes a decline in growth rate (compared to base line scenario. The growth rate of the economy falls to 6.58% (against 6.67% for the base line scenario). Further, economy’s downturn due to this shock has an adverse impact on NPA ratio and it rises to 8.2 as compared to baseline 8.0.

Amongst all, it is the GS which is the most severe and significant in dropping GDP growth rate to 3.9 % in one year horizon and the NPA ratio rises to 12.4.

28

SCENARIOS OTHER EXTERNAL

SHOCKS

Year Baseline

(1)

External Price Shock

(3)

Global Shock

( 4) (5)**

y N y N y N y N

2010-11 8.13 7.449 8.05 7.558 7.38 8.469 7.38 8.469

2011-12 6.06 9.457 5.90 9.674 5.29 10.504 3.90 12.394

2012-13 6.67 8.078 6.58 8.200 6.74 7.983 6.86 7.819


External Shocks:Impact Analysis of Macro Credit Stress Testing

Note: k denotes (total) capital risk weighted asset ratio and k1 denotes tier 1 capital risk weighted asset ratio.

* Based on a more severe shock for 4 quarters at a stretch (2011Q1-Q4).

29

SCENARIOS OTHER EXTERNAL SHOCKS

Baseline External Price Shock Global Shock Global Shock*

k k1 k k1 k k1 k k1

One Year Horizon

2010-11 13.4 8.38 13.3 8.28 12.4 7.44 12.4 7.44

Two Year Horizon

2011-12 11 6.32 10.8 6.1 10 5.28 8.15 3.44

Three Year Horizon

2012-1310.8 6.74 10.7 6.62 10.9 6.83 11.1 6.99


External Shocks:Impact Analysis of Resilience of Indian Banking Sector

The results indicate the estimated total KAR (k) and Tier I KAR (k1) due to other external shocks.

These estimated values are compared to current BASEL II norms for stability (referred to as Financial Soundness Indicators) for k & k1 to 8 % & 4 % as per international standards; and 9% & 6% as per Indian (more stringent) standards.

Overall, Indian banks meet these norms as per current BASEL II requirements.

However, if we compare the estimated values to even higher forthcoming BASEL III norms, then Indian banks are marginally constrained in meeting Tier I KAR by Indian standards.


20-Oct-16 Macro Stress Testing and Resilience Assessment of Indian Banking 31

0

2

4

6

8

10

12

14

16

18

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

NPA Ratio (%)

Figure 3 : Non-Performing Asset Ratio (%)


10

11

12

13

14

15

16

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Bank regulatory capital to risk-weighted assets (%) - CAPITAL ADEQUACY RATIO

Figure 4 : Capital Adequacy Ratio (%)


5

5.5

6

6.5

7

7.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Bank capital to assets ratio (%) -TIER 1

Figure 5 : Tier I Capital Adequacy Ratio (%)

Baseline scenario: Indian banking sector sufficiently over and above thecapital adequacy threshold according to both BASEL II & III for both leveland quality.

Significant Adverse shocks- Policy, EPS, GS: Indian banking sector largely remains SOUND in terms of total k as per current BASEL

II and even BASEL III but constrained, though not severely, as per BASEL III for Tier 1capital

Impact and thus role of monetary policy is significant Indian banks remain ROBUST with strong capital positions and sufficient

buffers during shocks as per BASEL II in three year horizon but lackedTier 1 regulatory norms and CCBs as per BASEL III

Indian banking sector is not substantially vulnerable to and hence notthreatened by various significant adverse shocks as per current BASEL.


Overall Conclusions

Policy authorities may positively influence the leveland quality of capital adequacy to meet higherstandards of BASEL III Tier1 capital norms bypromoting growth since

impact and thus the role of monetary policy is expectedto be significant


Policy Implications

Thank You !


*Based on ‘‘A SMEM for India’’, Dua and Kapur(2014)

37

Alternative Scenario Maximum

POLICY SHOCK

MONETARY POLICY

(Scenario1): 𝒊 ↑

Impulse shock

Step Shock

12% for 2011Q1-Q2&

12% for 2011Q1-2013Q2

EXTERNAL SHOCK:

(Scenario5):𝐖𝐭𝐅 & 𝐖𝐭

𝐎𝐈𝐋 ↑

𝐖𝐭𝐅 187.9

𝐖𝐭𝐎𝐈𝐋 226.998 for 2011Q1-Q2

GLOBAL FINANCIAL

CRISIS(Scenario 6) : BSE ↓, FII ↓ & 𝐘𝐖 ↓

S 9177.97,

FII -138.610,

𝐘𝐭𝐖 1696436 for 2011Q1-Q2

BASELINE Same as model solution


38

VARIABLE DEFINITION SOURCE

d1 Dummy variable equal to 1 for

2004Q2 onwards and 0 otherwise.

d2 Dummy variable equal to 1 for

2002Q1 and 0 otherwise.

e Exchange Rate (INR per US $) www.rbi.org

FII Net Foreign Institutional

Investment flows

( Rs billion)

-do-

π Annualised inflation (%) calculated

as ( 𝑷𝒕 − 𝑷𝒕−𝟏 /𝑷𝒕−𝟏 *100 using

WPI

i Nominal interest rate (%) given by

GS 10 yield rate

- do -

i1 Nominal interest rate (%) given by

TB 91 day yield rate

- do -

𝒊 Policy Rate given by Repo Rate (%)

is the rate at which the RBI lends to

commercial banks against eligible

securities in order to meet their

daily liquidity requirements.

- do -


39

k (Total) Capital Adequacy ratio (KAR) or Capital to risk

weighted assets ratio (%) is the ratio of bank capital to

aggregate risk weighted assets(for credit risk, market risk and

operational risk).It is regarded as a measure of

soundness/internal health of an institution. The higher the k of

a bank, the better capitalized it is.

www.imf.org,IFS

K Regulatory total capital www.imf.org,IFS

K1 Tier I capital (or core capital) is a component of regulatory

capital which is considered to be of the highest quality because

they are fully available to cover losses. It mainly comprises of

share capital and disclosed reserves (minus goodwill, if any).

www.imf.org,IFS

k1 Tier I capital ratio www.imf.org,IFS

K2 Tier II capital (or supplementary capital) comprises of certain

reserves and certain types of subordinated debts.

www.imf.org,IFS

k2 Tier II capital ratio -

m Growth rate of broad money M3 (%) calculated year-on-year

basis, taken as a proxy of inflation.

N NPA Ratio (%) is the ratio of gross NPAs to gross advances.

NPA ratio (publicly available only on annual basis) on

quarterly basis is calculated by calibrating annual NPA based

on position of y-o-y non-food credit growth of the respective

quarters (with one quarter lag) with respect to March quarter*.

-

NPA Non-Performing Asset on which either the principal or the

interest is overdue for at least 90 days (Mar 2004).

www.rbi.org

Data variables, Definitions and Sources


40

RWA Risk Weighted Assets are derived as a weighted sum

of assets where prescribed risk weights are assigned

to different types of assets according to BASEL

norms; i.e., RWA = 0%*Bucket 1 + 20%*Bucket 2 +

50%*Bucket 3 + 100%*Bucket 4; where Bucket 1, 2,

3 and 4 indicate assets with zero, low, medium and

high default risk with weights (0, 0.2, 0.5, 1) attached

to them respectively.

www.rbi.org

S BSE SENSEX www.rbi.org

WOIL

World crude oil (petroleum) index(2005=100) www.imf.org, IFS

WF

World food price index (2005=100) www.imf.org, IFS

𝐘𝐖 OECD real GDP(Rs billion) Stats.OECD

y Growth rate of real GDP (%) calculated year-on-year

basis

-

Y Real GDP at factor cost (2004-05) www.mospi.nic.in

Data variables, Definitions and Sources


Shock ⇨ GDP growth ↓ ⇨ (↑ in unemp an

↓ incomes) PD ↑ ⇨ Credit quality ↓ ⇨ NPAs ↑

⇨ (a) banks’ losses ↑ ⇨ banks needs to tap its

capital base to make debt payments;

(b) also provisions for NPAs ↑ ⇨ KAR ↓ ,

If < min 8% (BASEL) ⇨ banks needs to be

closed or recapitalized ⇨ contagion effects

⇨ a policy issue.

20-Oct-16 41Macro Stress Testing and Resilience Assessment of Indian Banking

Documents

Macro Stress Testing and Resilience Assessment of Indian Banking