Testing Resilience of the Czech Testing Resilience of the Czech Financial SystemFinancial System

Smilovice 2009

Jan FraitJan Frait

Deputy Head of Economic Research and Deputy Head of Economic Research and Financial Stability Financial Stability DepartmentDepartment

2

• for assessing resilience of the financial system to shocks other than liquidity shocks, the CNB conducts stress tests of banking sector since 2003

• three (slightly overlapping) stages in development of the stress testing framework for banks

simple static stress testing/sensitivity analysis (2003-2006) static stress testing based on (consistent) macroeconomic

scenarios, satellite models and with some interbank contagion (2005-2009)

dynamic model-based stress testing (2009++)• Macro-stress tests have semi-top-down style, CNB also runs

bottom-up tests with banks• since 2007, the CNB conducts stress tests of insurance companies (market

risk, insurance-specific risks) and pension funds (market risk)

Stress testing in the CNBStress testing in the CNB

3

• the CNB was always very open in communication of stress test results to the industry and public

• traditional means of publication is Financial Stability Report (since FSR 2004 published in January 2005)

• results first published in a special feature/article, since FSR 2007 in the main text (chapter Financial Sector – part „assessment of the financial sector‘s resilience“)

• stress tests conducted nowadays quarterly (for the CNB macrofinancial panel),

results sometimes published in Bank Board members‘ presentations, now ready for regular release of results starting from next quarterly

exercise (February 2010)

Publication of stress test resultsPublication of stress test results

4

Stage I

Simple static stress testing/sensitivity analysis

(2003-2006)

FSR 2004, FSR 2005, FSR 2006

Stress testing in the CNBStress testing in the CNB

5

Simple static stress testing Simple static stress testing

• methodology based on the IMF FSAP approach, developed in co-operation with the IMF

• for testing credit risk and market risk (interest rate risk and FX risk)

• based on „static“ balance sheets of individual banks and assumptions how balance sheets would change if (a) interest rates, (b) exchange rate, (c) NPL changed

• impact horizon of 1 year

• suitable for simulations of the impact of single shocks (sensitivity analysis) like increase of NPLs by 20%, ad hoc scenarios defined as combination of risk factors that have direct

impact on banks‘ balance sheets (interest rate, exchange rate, NPL)

6

Mechanics of the stress test I Mechanics of the stress test I

Transmission of risk factors:

• impact of a change in NPL: increase in NPL leads to increase in loan loss provisions (using information about banks‘ provisioning rate)

• impact of a change (increase) in interest rates: change in net interest income (gap analysis) plus re-pricing of debt securities (duration analysis)

• impact of a change in exchange rate: change in value of FX-denominated assets and liabilities (using data on net FX position) plus indirect effect on NPL (loans denominated in FX)

7

Mechanics of the stress test II Mechanics of the stress test II

Other assumptions:

• in the absence of shocks, banks are assumed to generate profit at the level of the average of the last 5 years

• profit is used to raise capital to the initial level of capital adequacy (if the profit is sufficient to counterbalance the impact of shocks), the rest (if any) is distributed via dividends

• risk-weighted assets (RWA) after shock are calculated as initial RWA minus 80% of the overal impact of shocks

• results of the stress tests are presented in percentage points of the initial capital adequacy

8

Ad hoc scenarios in the simple stress Ad hoc scenarios in the simple stress testtest

• the CNB used so-called „historical scenarios“ I and II, i.e. combination of shocks that mimic past crisis (1997-1998) and past volatility of variables (see the table taken from FSR 2004)

• shocks can be alternatively calibrated for example as 1 p.p. confidence level (roughly 3 standard deviations)

• combination of shocks should be plausible and reflect possible reaction of authorities and markets (e.g.. central bank raises interest rates to defend currency from further depreciation etc.)

9

Presentation of results of an ad hoc Presentation of results of an ad hoc scenario I (FRS 2005, p. 79)scenario I (FRS 2005, p. 79)

10

Advantages of simple stress tests I Advantages of simple stress tests I

• can be used to quickly assess resilience to specific risks (sensitivity analysis)

• respond to questions like „how much would the interest rates have to increase to get post-test capital adequacy equal to the minimum value of 8 % (see chart from FSR 2005)

• served as a necessary first step in developing more comprehensive framework

11

Stage II

Static stress testing based on (consistent) macroeconomic scenarios and satellite models

(2005-2009)

FSR 2005, FSR 2006, FSR 2007, FSR 2008/2009

Stress testing in the CNBStress testing in the CNB

12

• based on the static simple stress testing, i.e. same risk factors (credit risk, interest rate risk, FX risk) same transmission channels (impact on net interest income,

revaluation of bonds, FX profit/losses, loan loss provisions) same horizon of 1Y same assumptions about profit, CAR etc. (but from FSR 2008/2009,

pre-provision income instead of profits used)

• new features explicit (consistent, i.e. model-generated) macroeconomic scenarios satellite models to transmit changes in macro variables into risk

factors a new risk factor – interbank contagion

Basic building blocksBasic building blocks

13

The framework The framework

• QPM model (or since late 2008 G3 DSGE model) generates both baseline forecast (the official CNB forecast produced quarterly) as well as alternative „adverse“ macroeconomic scenarios

• satellite models are credit growth model (ECM model of aggregated credit growth) and credit risk models (corporate, households)

14

Transmission Channels Transmission Channels of Credit Riskof Credit Risk 14

• dependent variable of credit risk models: 12M default rate (i.e. new bad loans over initial portfolio)

• 12M default rate is also used by commercial banks; the Basel II „PD“ used for IRB approach in credit risk should be „a long-run average of default rates“

• model and explanatory variables Corporate Sector

Merton modelmacroeconomic shocks (explanatory variables); GDP growth,

exchange rate, inflation, debt Households

Merton model + naive econometric modelsunemployment rate, real interest rates, GDP

15

Transmission Channels Transmission Channels of Credit Riskof Credit Risk 15

• other parameters entering the stress tests were derived using sub-models and expert estimates

• NPL ratio - the ratio of non-performing loans to total loans - was generated using

credit risk models credit growth model expert judgment/assumptions about NPL outflow a

NPL(2)/L(2) = approx. [NPL(1) + L(1)*df - a*NPL(1)]/L(2)

• approximate relationship, because it depends on the time horizon (new loans can also turn bad)

16

Credit Risk ModelingCredit Risk Modeling 16

• Macroeconomic credit risk model for the Czech and Germany corporates were estimated (Jakubík and Schmieder 2008)

• Czech:

• German:

Variable Notation

Constant -3.060*** 0.358 -2.6997*** 0.07141

Nominal Interest Rate (b 1 ) ir NA -1 2.2194*** 0.4919

Real Exchange Rate (b 2 ) e -2 1.062*** 0.323 NA

Inflation (b 3 ) p -1 -4.850*** 0.636 NA

GDP (b 4,1 ) gdp 0 -4.609*** 1.079 0 -3.3677*** 0.328

Industry production (b 4,2 ) indprod NA -3 -0.8215*** 0.1464

Credit-to-GDP ratio (b 5 ) debt -4 3.006*** 0.246 -4 1.0871*** 0.1213

Dummy variable (b 6 ) dum 0 0.238*** 0.043 0 0.0400*** 0.0125Significance level: **: Significant at 5% level; ***: Significant at 1% level;

Czech case German caseLag Coefficient Std. error Lag Coefficient Std. error

)( 6451,41322 tttttt dumdebtgdpecdf bbbpbb

)( 4532,41,411 ttttt debtindprodgdpircdf bbbb

17

Credit Risk ModelingCredit Risk Modeling 17

• Macroeconomic credit risk model for the Czech and German households

were estimated (Jakubík and Schmieder 2008)

• Households models: less successful than for corporates, additional (socio-

economic) indicators may improve modelling

Variable Notation

Lag Coefficient Std. error Lag Coefficient Std. errorConstant -2.224*** 0.071 -5.5656*** 0.1072Household Income (b1) inc NA NA NA 0 -5.7912*** 0.9244

Credit-to-GDP ratio (b2) debthouse NA NA NA -4 5.7186*** 0.2788

Unemployment Rate (b3,1) u -4 3.695*** 0.846 NA NA NA

Real Interest Rate (b3,2) r -3 1.808** 0.596 NA NA NA

Significance level: **: Significant at 5% level; ***: Significant at 1% level;

Czech case German case

18

• possible to construct scenarios without a macroeconomic model, but to achieve the highest possible consistency, using a macro model (QPM, DSGE, VAR) is of advantage

• scenarios should be of a typ „low probability – high impact“, but plausible and have some „story“ behind

• should react to risks identified in risk assessment; in case of double-sided risk, opposite scenarios can be built (e.g. appreciation/depreciation, increase/decrease in interest rates)

• the story can be reflected in the name of the scenario (makes it easier to remember); „sexy“ names are of advantage

• use baseline scenario (official forecast) as benchmark; however, problems with interpreting the results if the stress testing model/models calibrated conservatively

Scenario buildingScenario building

19

Example FSR 2007: sExample FSR 2007: stress tress ttest est sscenarioscenarios 19

• Three alternative model-consistent scenarios in FSR 2007 (scenarios for the year 2008

A - safe haven (appreciation of currency) B - property market crisis (internal shock with direct impact on banks) C - loss of confidence (external shock – increase in risk aversion)

Calibration of baseline and alternative scenarios(2008 averages)

Baseline Scenario A Scenario B Scenario CReal GDP growth (%; y-o-y) 4.1 2.4 0.3 2.8Inflation rate - CPI (%; y-o-y) 6.2 7.0 5.3 8.0Unemployment rate (%) 6.0 6.3 6.7 6.31Y PRIBOR (%) 3.8 2.8 1.5 8.7

CZK/EUR exchange rate ... 1) 25.6 27.0 30.5Source: CNB

Note: 1) In 2008, the baseline expects an correction of the record values initially and then a slight appreciation

21

FSR 2007: FSR 2007: Impact of Alternative Scenarios on the Impact of Alternative Scenarios on the Banking SectorBanking Sector

21

• Example of presentation of the results

• The results were interpreted as follows:

The banking sector seems to be resilient to a wide range of risks

Only an extreme macroeconomic scenario would necessitate capital injections to maintain sufficient capitalization

Results of bank stress tests(capital adequacy; % and p.p.)Scenario type Baseline Scenario A Scenario B Scenario C

2007 2007 2007 2007

Capital adequacy (CAR) 1) 11.5 11.5 11.5 11.5Results for chosen scenario type Overall impact of shocks (p.p. CAR) -2.1 -2.8 -3.0 -6.3 Interest rate shock 0.2 0.1 0.6 -2.6 Exchange rate shock -0.1 -0.2 0.0 0.5 Credit shock -2.0 -2.4 -3.3 -3.6 … households -0.5 -0.5 -0.5 -0.5 … non-financial corporations -1.0 -1.5 -2.0 -0.6

Interbank contagion2) -0.2 -0.2 -0.2 -0.7 CAR before profit allocation 9.4 8.7 8.5 5.2

Profit allocation (p.p. CAR)3) 1.8 2.3 2.2 2.8Post-shock CAR 11.3 11.0 10.8 8.1

Capital injection (% of GDP)4) 0.0 0.1 0.1 1.1

Share of banks with negative capital after shock5) 0.0 0.0 0.0 14.9Notes:

1) CAR means the capital adequacy ratio defined in accordance with the relevant CNB regulations (in particular those

governing the capital adequacy of banks and other prudential business rules).

2) Test integrated with interbank contagion and expected level of loss given default (LGD) 100%

and chosen probability of the banks' failure (default) on the basis of the CAR.

3) The scenarios assume that in the absence of shocks each bank would generate profit (or loss) equal to the average for the previous five

years and that it would use any profit (income) as a first line of defence against a declining CAR.

4) The capital needed to ensure that each bank has a post-shock CAR of at least 8%.

5) Market share of banks with negative capital after the impact of the assumed shocks (as a percentage of total assets).

22

FSR 2007: FSR 2007: Impact of Alternative Scenarios on the Impact of Alternative Scenarios on the Banking SectorBanking Sector

22

• alternative – graphic – presentation of the results

• scenario C would have the strongest impact on banking sector

0

2

4

6

8

10

12

14

16

18

20

22

24

26

2006 2007 2008

Capital adequacy (%)

Growth of total loans (%)

Baseline ____Scenario A ____Scenario B ____Scenario C ____

Share of default loans(%)

Note: Growth in total loans is defined as the average annual rate of growth. The share of new non-performing loans (NPLs) relates to the estimation of the loan volume at the end of 2007.

Source: CNB

23

Example FSR 2008/2009: macroeconomic Example FSR 2008/2009: macroeconomic scenariosscenarios

23

• Three scenarios reflecting the risks from the global financial crisis

Europe in recession (= baseline prediction) Nervousness of the markets (a la „loss of confidence“, i.e.

increase in risk aversion) Economic depression (very large decline in GDP)

Stress-Test Scenarios

in CNB's Financial Stability Report (June 2009)

Development of key macroeconomic variables in 2009Real GDP (%, y-o-y) -2.4 -3.9 -6.2Inflation (%, y-o-y) 1.2 1.7 1.3Interest rate 1Y PRIBOR (%) 2.4 4.6 2.6Exchange rate CZK/EUR 26.6 28.8 27.8

Europe in recession

Nervousness of markets

Economic depression

24

FSR 2008/2009: capital adequacy looks FSR 2008/2009: capital adequacy looks satisfactory even in large depression satisfactory even in large depression

• Horizon of stress tests is just one year.

• In a longer horizon, the NPL share continues to grow and capital adequacy deteriorates further.

• Still, unless recession is very long and very deep, the banks should manage without public funds.

Results of stress testing scenarios

(%; banking sector)

Source: CNB

0

2

4

6

8

10

12

14

16

06/2007 12/2007 06/2008 12/2008 06/2009 12/2009

Europa in recession

Nervousness of markets

Economic depression

Capital adequacy development (%)

Share of non-performing loans (%)

25

FSR 2008/2009: presentation of the FSR 2008/2009: presentation of the resultsresults

• same style of presentation

• information about the capital injections needed

Results of bank stress tests

(capital adequacy; % and p.p.)Scenario type

Capital adequacy (CAR) at the end 2008 1/ 12.3 12.3 12.3

Overall impact of shocks (p.p. CAR) -3.2 -5.4 -5.0 Interest rate shock 1.3 0.0 1.2 Exchange rate shock 0.0 0.1 0.1 Credit shock -4.4 -5.4 -6.2 … households -1.3 -1.5 -1.8 … non-financial corporations -3.0 -3.1 -3.9 Interbank contagion -0.1 -0.1 -0.1

Income allocation 2/ 2.2 3.1 2.4

Post-shock CAR 11.3 10.0 9.7

Capital injection (CZK billions) 3/ 8.0 15.7 15.5

Capital injection (% of GDP) 3/ 0.2 0.4 0.4

Number of banks (CAR below 8 %) 4/ 4 8 4

Share of banks (CAR below 8 %) 4/ 8.2 21.8 5.0

Number of banks with negative capital 5/ 0 0 1

Share of banks with negative capital 5/ 0.0 0.0 5.2

Europe in recession

Nervousness of markets

Economic depression

1/ CAR means the capital adequacy ratio defined in accordance with the relevant CNB regulations (in particular those governing the capital adequacy of banks and other prudential business rules).2/ We assume that banks would generate income in all adverse scenarios which would be used to strengthen the capital. The level of income for individual banks is estimated using the past development of income and parameters of the scenario. Every bank allocates the income to reach the starting CAR level.3/ The capital needed to ensure that each bank has a post-shock CAR of at least 8%.4/ Banks with post-shock CAR 0 - 8 %.5/ Banks with post-shock negative capital.

26

Stage III

Dynamic model-based stress testing

(2009++)

FSR 2008/2009

Stress testing in the CNBStress testing in the CNB

27

• Existing framework limited as regards its ability to analyze the impact of shocks in a longer horizon than a one-year

horizon (up to two to three years), capture the effects of credit, interest and currency shocks over

time in a more dynamic way, estimate the pre-provision income as a function of both the

macroeconomic development and a bank’s business model, be expressed in the variables used in current regulatory

framework (PD, LGD) and thus mimick the stress testing done by individual banks within Pillar II of Basel II

capture pro-cyclical nature of current Basel II regulation, integrate fully the funding liquidity shock within the

macroeconomic stress testing framework, link the interbank contagion and second-round liquidity shocks

to development of the individual bank’s capital and liquidity conditions in a non-linear way, and

capture potential two-way interaction between the banking system and the macroeconomic environment (feedback effect).

Problems with static stress testingProblems with static stress testing

28

• difference in time horizon between the effects of market and credit risks

impact of a change in interest rates or other market variables (the exchange rate or stock prices) on the balance sheets of financial institutions is virtually immediate (revaluation of securities)

credit risk accumulates over a longer time frame (one to three years) as loans gradually shift into the NPL category

• existing CNB stress testing framework was addressing this discrepancy with a compromise assuming an impact horizon of one year

• macro variables of the projected year were averaged to produce the „shock“ as the difference between initial and average future value = underestimates peaks in possible crisis (Lehman September 2008)

Example of the „time“ problem: Example of the „time“ problem: market vs credit riskmarket vs credit risk

29

• „experimental“ dynamic stress test in FSR 2008/2009• scenario „nervousness of markets“ assumes losses due to

unfavourable interest rate changes in some quarters, but these losses are fully reversed in the following periods

• this dynamics of the directional changes in the shocks over time generates stress situations in the financial sector that cannot be captured by the standard stress tests using averages for the entire test period.

Example of the evolution of the Example of the evolution of the impact of shocksimpact of shocks

30

• Pillar I: change in credit risk terminology/risk factors explicit PD (probabilities of default, proxied by default

rates), LGD (loss given default), EL (expected loss) loan segments very close to Basel II segments (corporate,

retail, other) for banks in IRB approach, application of Basel II formula

to determine capital requirements• Pillar II: exchange of views with banks on stress testing

methodology adjustments in interest rate impact (use of derivatives,

interest rate sensitivity of current accounts etc.) explicit (expert) modelling of yield curve and interest rate

risk

Bringing the stress tests in line with Bringing the stress tests in line with Basel IIBasel II

31

Interest rate shock revisedInterest rate shock revised

• The new framework for assessing the impact of interest rate shock

partially set following the research of banks practices regarding interest risk management

assumption that only on some part (cca 20 %) of short-term liabilities (mostly sight deposits) banks adjust client rates according to the money market

the change in value of bonds is muted for banks using hedging via IRS

revaluation of long-term bonds is calculated with a forecast of 5Y rate which is linked to 1Y rate, 5Y Bund rate and assumption on risk premium (spread between 5Y euro rate and 5Y CZK rate)

32

• regular consultations with commercial banks on stress testing methodology

• verification of the models and assumptions (over time, banking sector changes thus the stress testing framework should react as well - Basel II, use of derivatives etc.)

how to assess results of verification? use baselines, but assymetric assessment needed (better to

overestimate risks than underestimate) in crisis periods, alternatives might be better benchmarks than

baselines conservative calibration of models and/or additional expert‘s

adjustments are needed

Regular cross-check of the stress Regular cross-check of the stress testing frameworktesting framework

33

Last Stress Testing Exercise – Assumptions and Results

Stress testing in the CNBStress testing in the CNB

34

Basic framework of CNB‘s stress testsBasic framework of CNB‘s stress tests

• This part will focus on methodology and some results of stress tests of the Czech banking sector.

• CNB now performs stress tests with every new quarterly macroeconomic forecasts (i.e. 4 times a year)

alternative macro scenarios: one scenario reflects actual CNB‘s macroeconomist forecast, one or two adverse scenarios run in DSGE model are outlined by the financial stability team together with modelling division experts (14 variables used),

the horizon is set to 8 quarters - actual (internal) stress tests performed on mid-2009 portfolios with July 2009 forecasts focusing on horizon 3Q2009 – 2Q2011.

• The results presented below are taken from July 2009 exercise (to some extent „work in progress“ as a part of dynamic stress testing methodology development.

34

Two macroeconomic scenariosTwo macroeconomic scenarios

• The July bank stress test worked with two scenarios: Scenario A: “baseline” reflects the CNB’s July forecast Scenario B: “protracted recession” expects a greater and

longer decline in GDP compared to the baseline scenario

• These scenarios were updates to the scenarios published in the Financial Stability Report in June 2009Scenario

2009 2010 2009 2010

Real GDP growth (%, y-o-y) -3,8 0,8 -5,2 -1,1Inflation (%, y-o-y) 1,2 1,1 1,2 1,2Interest rate 3M PRIBOR (%) 2,1 1,8 2,3 2,0

Exchange rate CZK/EUR 26,6 25,7 27,0 27,0

Baseline Protracted recession

35

36

Two macroeconomic scenariosTwo macroeconomic scenariosAlternative scenarios: real GDP growth(in %)

-10

-8

-6

-4

-2

0

2

4

6

8

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

Alternative scenarios: 3M Pribor rate(in %)

0

1

2

3

4

5

6

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

Alternative scenarios: inflation rate(in %)

0

1

2

3

4

5

6

7

8

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

Alternative scenarios: exchange rate(CZK/EUR)

23

24

25

26

27

28

29

30

31

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

36

37

Credit risk Credit risk in CNB‘s stress testsin CNB‘s stress tests

• Credit risk and credit growth assumptions: outputs of satellite models utilizing macro scenarios (4 separate loan portfolios modelled).

• Dependent variable of credit risk models: 12M default rate (i.e. new bad loans over initial portfolio).

• 12M default rate is also used by commercial banks; the Basel II „PD“ used for IRB approach in credit risk should be „a long-run average of default rates“

• NPL ratio - the ratio of non-performing loans to total loans - generated using expert judgment/assumptions about NPL outflow (15% in a quarter):

NPL(2)/L(2) = approx. [NPL(1) + L(1)*df - a*NPL(1)]/L(2)

37

38

Dynamic features of CNB‘s stress Dynamic features of CNB‘s stress teststests

• Credit growth is estimated for each portfolio via simple macroeconomic model.

• Forecast of default rates and credit dynamics are transformed to predictions of main balance sheet and flow variables of banks.

• Four key risks are tested then (credit, interest rate, currency and interbank contagion).

• Tests are set as dynamic – for every item in assets, liabilities, income and costs there is an initial state to which the impact of shocks is added in one quarter and the results serve as the initial state for following quarter – this is repeated in next 8 quarters for which the prediction is generated.

38

39

Credit developments in two Credit developments in two scenariosscenarios

Alternative scenarios: corporate default rate developments

(in %)

5

7

9

11

13

15

17

19

03/09 06/09 09/09 12/09 03/10 06/10 09/10 12/10 03/11 06/11

baseline protracted recession

Alternative scenarios: household default rate developments

(in %)

4

5

6

7

8

9

10

11

03/09 06/09 09/09 12/09 03/10 06/10 09/10 12/10 03/11 06/11

baseline protracted recession

Alternative scenarios: corporate credit growth rate

(in %)

-20

-15

-10

-5

0

5

10

03/09 06/09 09/09 12/09 03/10 06/10 09/10 12/10 03/11 06/11

baseline protracted recession

Alternative scenarios: household credit growth rate

(in %)

-10

-5

0

5

10

15

20

03/09 06/09 09/09 12/09 03/10 06/10 09/10 12/10 03/11 06/11

baseline protracted recession

39

• NPLs in major segments (corporates, households) higher relative to FSR 2008/2009...

• ... due to higher predicted default rates corporates - 2009/20010 - baseline 11,8/11,1 % - adverse 13,4/11,6 % households - 2009/2010 - baseline 5,7/6 % - adverse 7/9 %

NPLs in current stress testsNPLs in current stress tests

NPLs in corporate sector

(in %)

0

2

4

6

8

10

12

14

16

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession Baseline May 2009

NPLs in household sector

(in %)

0

2

4

6

8

10

12

14

16

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession Baseline May 2009

40

• Assumptions regarding behaviour of net income, profits and regulatory capital

pre-provision income is expertly set at x % of average of past 2 years (x < 100%, thus additional stress applied in the sense of lower intermediation activity).

• Profit/loss is generated using the pre-provision income and the impact of shocks

in current accounting period pre-provision income serves as a first line „buffer“ against the impact of shocks,

only after the „buffer“ is exhausted, the impacts are deducted from the capital.

• Regulatory capital is adjusted every 2nd Q of calendar year to get back to initial CAR, if there are sufficient profits generated in previous accounting year ...

• ... thus, a P/L account and balance sheet of all banks generated every quarter = possible to cross-check with reality later on.

How we work with pre-provision How we work with pre-provision income, profits and capitalincome, profits and capital

41

Regulatory capital

RWA CARLoss from

shock impactNet

incomeP/L

Regulatory capital

RWA CAR

Example 1 100 1000 10.0% 20 30 +10 100 1020 9.8%

Example 2 100 1000 10.0% 40 30 -10 90 1020 8.8%

Final stateEstimate of P&L over quarterInitial state

Net income, P/L and capital Net income, P/L and capital adequacy: an exampleadequacy: an example

• For final evaluation of banks‘ resilience capital adequacy is estimated.

• Link between shocks impact and capital adequacy must reflect

(net) income generated by banks even under stress, asymmetric treatment of profits in calculation of regulatory

capital,

topping up of regulatory capital in 2nd Q.

42

Current ST results in detailCurrent ST results in detail

• Strong resilience confirmed despite recessionary scenarios.

• CAR higher than at the end of 2008 (effect of high capital buffer + relatively strong income generation capacity)

Detailed results of stress testsScenario

2Q2009-

2Q2010

2Q2010-

2Q2011

2Q2009-

2Q2010

2Q2010-

2Q2011

Capital adequacy (CAR) 13,5 13,1 13,5 12,9

Overall impact of shocks (p.p. CAR) -2,8 -2,1 -4,3 -2,6

Interest rate shock -0,1 -0,1 -0,2 0,0

Exchange rate shock 0,0 0,0 0,0 0,0

Credit shock -2,5 -1,9 -4,1 -2,5

… non-financial corporations -1,9 -1,5 -2,7 -1,5

… households - housing loans -0,2 -0,1 -0,5 -0,4

… households - consumer loans -0,3 -0,2 -0,7 -0,5

Interbank contagion -0,1 -0,1 -0,1 0,0

Income allocation 2,4 1,9 3,7 2,5

Post-test CAR 13,1 12,9 12,9 12,8

Capital injection (CZK billions) 0,0 0,0 0,0 0,0

Capital injection (% of GDP) 0,0 0,0 0,0 0,0

No. of banks with CAR between 0% and 8% 0 0 0 0

Share of banks with CAR between 0% and 8% in total assets 0,0 0,0 0,0 0,0

No. of banks with negative capital 0 0 0 0

Share of banks with negative capital in total assets 0,0 0,0 0,0 0,0

(capital adequacy in %, and p.p.)

Baseline Protracted recession

43

• Banks remain stable in both scenarios.

• Net income (profit prior to shocks): 90 (70) % of previous 2Y average in baseline (in protracted recession).

• Potential „deleveraging“ leads to higher CAR in protracted recession.

• For comparison a scenario with credit growth constructed too: negative impact on CAR confirmed.

Current ST: capital adequacyCurrent ST: capital adequacyCapital ratio: model-based (negative) credit growth(in %)

8

9

10

11

12

13

14

15

16

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

Capital ratio: 8% credit growth assumption(in %)

8

9

10

11

12

13

14

15

16

06/07 12/07 06/08 12/08 06/09 12/09 06/10 12/10 06/11

Baseline Protracted recession

44

……. the banking sector remains . the banking sector remains strong … so farstrong … so far

• The Czech banking sector has remained profitable and the profits have not shown a tendency to decline thus far.

• Capital adequacy went up as banks retained a large part of generated profit as a buffer against the expected increase in credit risk.

Net profits in the Czech banking sector(bil. CZK)

Source: CNB

0

10

20

30

40

50

60

70

IV-0

5

VII-05

X-05

I-06

IV-0

6

VII-06

X-06

I-07

IV-0

7

VII-07

X-07

I-08

IV-0

8

VII-08

X-08

I-09

IV-0

9

VII-09

net profit (last 3M annualized)net profit (last 1M annualized)

Capital and capital requirements for the banking risks

(CZK billions; %)

Source: CNB

0

2

1

1

0

2

1

#REF! #REF! #REF! #REF! #REF! #REF! #REF! #REF!

#REF! #REF!

0

50

100

150

200

250

XII2006

III2007

VI2007

IX2007

XII2007

III2008

VI2008

IX2008

XII2008

III2009

VI2009

8

9

10

11

12

13

14

Regulatory capital

Credit risk

Market risks

Operational and other risks

Capital adequacy (%, right-hang scale)

Capital adequacy Tier I (%, right-hang scale)

45

46

Thank You for Your Attention!Thank You for Your Attention!

Contact:Contact:

Jan FraitCzech National Bank

Na Prikope 28CZ-11503 Prague

Tel.: +420 224 414 430E-mail: jan.frait@cnb.cz

Financial Stability Team in the CNBFinancial Stability Team in the CNBfinancial.stability@cnb.czfinancial.stability@cnb.cz