Comprehensive Assessment Stefan Kerbl, Principal Expert, ECB Sunday 26 th October 2014

Comprehensive Assessment

Stefan Kerbl, Principal Expert, ECB

Sunday 26th October 2014

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The three primary aims of the Comprehensive Assessment are transparency, repair and confidence building

Repair

Confidence building

Transparency

Identify and implement necessary corrective actions, if and where needed

Enhance the quality and quantity of information available on the condition of banks

Reassure all stakeholders that SSM banks are fundamentally sound and trustworthy

More broadly the exercise aims to facilitate banks’ provision of credit to the European economy by reducing uncertainty over their solvency

Introduction to the comprehensive assessment

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The Comprehensive Assessment comprises of two main components – an Asset Quality Review and a Stress Test

1. Asset Quality Review

• In depth review of banks’ balance sheets: ‒ Assessment of data quality, asset valuations,

classifications of non-performing exposures, collateral valuation and provisioning

‒ Covers credit and market exposures, following a risk-based, targeted approach

2. Joint ECB / EBA Stress Test

• Forward-looking view of banks’ shock-absorption capacity under defined baseline and adverse scenarios

• Conducted in collaboration with the European Banking Authority (EBA)

Results of the Asset Quality Review were incorporated into the Stress Test


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Comprehensive in scope Comprehensive in nature

• 19 participating countries

• 130 participating banks

• 82% of total SSM banking assets covered

• Every portfolio of every participating bank examined and a risk-based sub-set selected for review in extensive detail

• 816 individual portfolios examined in detail

• 119,000 debtors analysed in detail

• 170,000 collateral items (re)valued

• 825 provisioning models challenged

• 4,500 securities revalued

• 70 derivative pricing models reviewed

The exercise was comprehensive in its scope and nature

Granular analysis with 40 million data points for the Stress Test alone, equivalent to 300,000 per bank


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Scenario building blocks: four main sources of risk starting with global vulnerabilities

Global sources of risk

• Increased risk aversion, broad-based sell-offs and re-pricing

• EMEs specifically impacted, with a severe decline in world trade

• Currency depreciation and funding stress in CEEs

Domestic demand confidence-driven

shocks

Sovereign bond yield differentiation

Access to and costs of bank

funding impacted

Stress Test recap

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1. a comprehensive methodology• prescriptive also for parts of the stress that are less focussed on previously (NII,

PPP)

2. a systematic and centrally-led quality assurance process • Thoroughly defined QA approach in the CAST manual

• Each bank had to provide up to 307,000 data points (circa 40 million in aggregate)

• Involving 100FTEs at central ECB level and hundreds of FTEs across the SSM

3. The thorough assessment of starting values via the AQR• a join-up process for the AQR and stress test outcomes

• Both book values and risk parameters

• Mechanistic and comprehensive

• Detailed description of the methodology in the CAST manual

Three important features distinguish the ECB CA stress test from previous EU-wide stress test exercises

Stress Test recap

Annex

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• The join-up process connects and reinforces the ‘point-in-time’ AQR and the

‘forward-looking’ stress test, thereby strengthening the overall exercise

• The join-up is in line with some previous national exercises (e.g. Spain, Cyprus,

Slovenia) – but unparalleled on the euro area level

• The AQR findings impact on the starting point CET1 ratio of all banks

• Where the AQR identifies material issues, these is also used to adjust bank’s

forward looking stress test results (e.g. loan losses)

AQR results will be used to adjust starting point and stress test projections

Stress Test recap

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Quality assurance (QA) was a key ingredient for ensuring credible results from a constrained bottom-up stress test

Enhance accuracy and credibility by providing a systematic review of individual bank results

• Key objective to minimise the risk that banks passing the stress-test will subsequently fail

• Also key for ensuring a level playing-field in a multi-country context

Quality Assurance scope:

• Stress test results (baseline and adverse scenario)

• Stress test results including the join-up impact

• Efficient framework for QA by focusing on material issues (traffic light approach)

Stress Test recap

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A central QA framework has been put in place to review results from individual and cross-country perspectives and by risk dimension

The central QA framework

• Specify a number of quantitative checks to be performed on banks’ submitted

results. These constitute a minimum standard to be applied consistently

across all countries, with Red/ Amber/ Green (RAG) thresholds.

• employs ECB top-down stress test models, in-market and cross-market

comparisons

• harnesses complementary qualitative information on each bank (e.g. reviewing

explanatory notes)

• Three lines of defence: NCA bank teams – NCA centrally – ECB

ECB CONFIDENTIALStress Test recap

On the Results

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Comprehensive Assessment results

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Comprehensive Assessment - key figures

Key results

•The Asset Quality Review (AQR) results in a gross impact on asset carrying values of €48 billion

•In total, a €136 billion increase in non-performing exposure was identified

•Combining the AQR with the stress test the Comprehensive Assessment results in:

- €263 billion capital depletion over the three-year horizon of the exercise under the adverse stress test scenario

-Median 4% reduction of the CET1 capital ratio of in scope banks

•In aggregate, the Comprehensive Assessment resulted in a €24.6 billion capital shortfall across 25 participant banks


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Note: Numbers do not add up due to rounding

Comprehensive assessment identified a capital shortfall of €24.6 billion across 25 banks

+10.7BN

Comprehensive assessment capital shortfall by driverSSM level (€ BN)

+2.7BN

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Capital shortfall was observed at banks from 11 of the 19 countries in scope of the exercise

Comprehensive assessment capital shortfall by driverBy country, as % RWAs

Total shortfall (€ BN)

2.37 8.72 1.14 9.68 0.07 0.86 0.87 0.54 0.23 0.13 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

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• Median bank’s CET1 ratio declines from 12.4% to 8.3%

Comprehensive assessment impact on CET1 ratio under the adverse scenarioMedian by country of participating bank, %

SSM median: 4.0%

The median bank’s CET1 ratio falls by 4% in the adverse scenario

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Asset Quality Review results

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Across the SSM, the Asset Quality Review (AQR) led to a €48BN adjustment to asset carrying valuesAsset Quality Review impact on available CET1 capitalBy AQR workblock (€ billion)

Additional provisions

Other capital adjustments

Projection of findings

Impact from risk-based sample


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The AQR led to an €136 BN increase in non-performing exposure, with increases across all asset segments

Change in NPE exposure, pre- and post-AQR By asset segment (€ billion)

• Divergent bank definitions of non-performing exposures were harmonised leading to €55 billion added non-performing exposure

• Following harmonisation, an increase in non-performing exposure of €81 billion was observed in the credit file review

• In total, non-performing exposure increased by €136 billion, representing a 18% total adjustment

Commentary

NP

E e

xp

os

ure

(€

BN

)

Individually assessed (credit file review)

Collectively assessed (collective provisioning)

+33%

+19%

+18%

+31%

+36%+73%

+14%

+4%

+1%


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Individually assessed (credit file review)

Collectively assessed (collective provisioning)

Provisioning increased by a total €43 BN across all asset segments

Change in provisionsBy Asset Segment (€ billion)

• Total specific provisions increased by €43 billion, a 12% overall adjustment

• Provisions increased as a result of both the credit file review and collective provisioning workblocks

• Shipping (28%), Large SME (16%) and Large Corporates (16%) experienced largest relative increases

Commentary

Pro

vis

ion

s (

€B

N)

+16%

+16%

+10%

+28%+10% +5%

+12% +6% +5%


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ECB Quality Assurance had a tangible impact on NPE classification, ensuring harmonised treatment

• ECB identified banks in where debtors were hitting triggers but not being classified as NPE

• ECB discussed with NCAs and challenged auditor decisions at the individual debtor level

• In some cases the decision against reclassification was justified

• In a significant number of cases, decision was withdrawn and the debtor reclassified to NPE along with debtors in similar scenarios

Example of impact of ECB Quality Assurance Number of performing debtors hitting 2 or more impairment triggers, pre- and post- ECB Quality Assurance (%)

Remedial approach taken

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ECB Quality Assurance resulted in a significant increase in collateral haircut levels

Example of impact of ECB Quality Assurance Mean collateral haircuts pre- and post- ECB Quality Assurance (%)

Note: The exhibited number of banks is not necessarily exhaustive for the example NCA

• ECB reviewed haircut levels across NCAs for each asset segment

• ECB discussed with NCAs and challenged auditor decisions at the individual debtor level

• In some cases the ECB accepted the NCA submission

• In others additional haircuts were agreed and applied

Remedial approach taken


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In total, collective provisioning led to an increase in provisions of €16BN, of which 62% was IBNR

Collective provisioning adjustment – IBNRSSM-level, € billion

Collective provisioning adjustment – specific provisionsSSM-level, € billion

• In total, more than 800 portfolios across most AQR asset classes were assessed

• Collective Provisioning workblock identified the need for additional collective provisions of €16 billion,

- €6 billion of retail specific provisions

- €10 billion of additional IBNR

• Key drivers included• Application of EBA simplified

NPE definition• Credit file review findings leading

to adjustments in LGI parameter• Adjustments to RRE collateral

values impacting LGL• Bank use of non point-in-time

parameters

+23%

+6%


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Collective provisioning Quality Assurance aligned parameters to ECB defined fall back assumptions

Collective provisioning parameter distribution – emergence periodDistribution of performing exposures by emergence period


ECB defined fall back assumption

Parameter Fall back assumption

Observed average

LGL secured 60% 50.4%

LGL unsecured 90% 86.9%

Original effective interest rate 4% 3.6%

Sales ratio 75% 78.0%

Sales ratio volatility 18% 21.6%

Appraiser discount 5% 5.4%

Comparison of other fall back parameters

Nu

mb

er o

f ex

po

su

res

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The adjustment of the Fair value exposures review was €4.6 billion, with 66% from CVA adjustments

Fair value exposures review adjustmentBy workblock (€ billion)

• Non-derivative positions were assessed through independent revaluations leading to a €1.2 billion adjustment

• Adjustment on CVA reserves was significant, with a 27% increase of €3.1 billion identified

• Complex derivative pricing models were also reviewed, with modelling errors or inappropriate assumptions leading to a further €0.2 billion adjustment


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Stress Test & Join-up results

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1Stress Test results include the impact of the Join-Up

Note: Scenario capital depletion and the effect on required capital are based on the 2016 adverse scenario

Overall, total adverse scenario capital depletion is €263 billion

Contribution of the Stress Test

Comprehensive assessment adverse scenario capital depletionSSM level, (€ BN)

Key drivers

•Total gross AQR adjustment of €48 billion, and €34 billion net of tax offset

•The stress test (and Join-up with AQR results) led to a capital depletion of €182 billion in the adverse scenario

•In addition, the increase in RWA in the adverse scenario increases capital requirements in the amount of €47 billion

Gross AQR adjustment

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SSM banks' average CET1 ratio is projected to increase from 11.8% to 12.0% in the baseline

Key drivers

•Improvement in the solvency position under the baseline mainly reflects

– Projected accumulation of pre-provision profits (3.6 percentage point contribution to the change in the CET1 ratio)

– Projected loan losses (-2.5 percentage point contribution)

•The average development of participating banks’ solvency positions, however, masks variations across individual institutions and countries

Stress Test results

Aggregate post-JU stress test effect1 by risk drivers under the baseline scenario

1. Weighted means; excluding the AQR impact on starting point capital

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SSM banks' average CET1 ratio is projected to decrease from 11.8% to 8.8% in the adverse

Key drivers

•Increase in loan losses (-4.5 percentage point contribution to the change in the CET1 ratio)

•Lower pre-provision profits compared to the baseline (corresponding to a 1.3 percentage point lower positive contribution the change in the CET1 ratio)

•“Administrative and other expenses” have an impact on the overall results; however, they remain largely unchanged between the baseline and adverse scenario and mainly reflect staff and other administrative costs that regardless of the scenario have a negative impact on banks' loss absorption capacity

Stress Test results

Aggregate post-JU stress test effect by risk drivers under the adverse scenario


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Loan losses and net interest income are key drivers of divergence from baseline to adverse

Stress Test results

Aggregate post-JU stress test effect by risk drivers under the adverse scenario


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Corporate and retail portfolios are the key drivers of loan losses in both scenarios

Key drivers

•Loan losses across banks are mainly driven by the corporate and retail portfolios, both under the baseline and adverse scenarios

•Under the baseline scenario, the median CET1 percentage point reduction due to losses is:

– 0.9% in the corporate segment

– 0.5% in the retail segment

•Results under the adverse scenario are, however, more severe with a median CET1 percentage point reduction of

– 1.6% in the corporate segment

– 1.1% in the retail segment

Stress Test results

Baseline scenario Adverse scenario

Decomposition of loan losses across portfolios and banks under the baseline and adverse scenario

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Under the adverse scenario, the median decline in NII is larger and more varied across banks

Key drivers

•While the picture is heterogeneous across banks, the median decline in net interest income is larger under the adverse than the baseline scenario

•Moreover, the distribution of changes in net interest income across banks is in general wider under the adverse scenario

Stress Test results

Net interest income development across banks under the baseline and adverse scenario, year-on-year % changes

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RWAs grow in net terms across the horizon, resulting in higher capital requirements

Stress Test results

RWA development across banks under the baseline and adverse scenario, year-on-year % changes

Key drivers

•Risk-weighted assets experience net growth across the horizon, albeit at a declining rate

•For the large majority of banks under the static balance sheet assumption, the nominal balance sheet size remains the same by design

•Risk weights for the median bank grow under the baseline scenario from 1.0% in the first year to 0.7% in the third year, and under the adverse scenario 3.2% in the first year to 0.9% in the third year

•Increased RWAs result in higher capital requirements

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The stress test impact differs across banks under the static and dynamic balance sheet assumption

Stress Test results

Distribution of changes to CET1 ratios across banks following the static vs. dynamic balance sheet assumption under the baseline and adverse scenario, cumulative % changes

Key drivers

•Banks under the dynamic balance sheet assumption are less heavily affected under the baseline scenario

•In the adverse scenario larger CET1 ratio declines are observed for banks under the dynamic balance sheet assumption. This could reflect that restructuring banks

– Are generally weaker and more vulnerable to stress tests

– May be located in countries with relatively more severe scenarios

•In cases where banks provided both, static and dynamic templates, the dynamic version generally resulted in less severe effects

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Join up effect varies by bank but is driven by bank AQR impact

Join-up effect by bank in relation to AQR impact Key drivers

•Join up effect is highly correlated with the magnitude of AQR findings

•The strongest join-up effect (above 1% of RWA) is observed for banks where AQR had a major impact

•For banks with small or negligible AQR findings, the join-up effects on average were similarly small (<0.2% of RWA)

Join-up results

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Impairments are the major driver of join-up effect by change in CET1 in the baseline scenario

Join-up results

CET1 effect of join-up by type (credit vs. other effects) under the baseline scenario

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Distribution of join-up effect by type is similar, but for greater impacts overall, in the adverse scenario

Join-up results

CET1 effect of join-up by type (credit vs. other effects) under the adverse scenario

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The post-JU impact of the Stress Test is 0.2% in the baseline and -3.0% in the adverse

Stress test component (€ billion)Stress test results (post-JU)

Baseline Adverse

NII 760 686

Net fee and commission income 377 362

Net trading income 25 6

Sovereign FVO/AFS -1 -28

Admin. and other expenses -865 -865

Loan losses -209 -378

Taxes, dividends and other -45 38

Total CET1 impact (€ billion) 43 -181

Total CET1 ratio change (percentage points) 0.2% -3.0%

of which: Join-up CET1 impact (€ billion) -6 -12

Stress Test and Join-up results

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On the Scenario

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PROCESS / STORY

DERIVED RESULTS

1

4

ASSUMPTIONS / DRIVERS2

RESULTS / SEVERITY3

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Scenario building process

• The baseline scenario was prepared by the European Commission

• The adverse scenario was proposed by the ESRB, working in close collaboration with the ECB and the EBA, and it was finally approved by the EBA Board of Supervisors

• It captures the prevailing view of systemic risks facing the EU financial system, as identified by the ESRB General Board

• It includes forward-looking paths for key macroeconomic and financial variables for all EU countries and a large number of non-EU countries over a three-year horizon

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• Starting point: global sources of risk- Increased risk aversion, broad-based sell-offs and re-pricing

- EMEs specifically impacted, with a severe decline in world trade

- Currency depreciation and funding stress in CEEs

• Triggering EU-specific risks- Domestic demand confidence-driven shocks (real estate too)

- Sovereign bond yield differentiation re-appearing

- Access to and costs of bank funding impacted

Scenario narrative

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Scenario building blocks: Four main sources of risk leading to a set of drivers

Source of risk: Financial and economic shocks:

Increase in global bond yields amplified by an

abrupt reversal in risk assessment, including

towards EMEs, and pockets of market liquidity

Financial market shocks worldwide (sovereign bonds, corporate bonds, stock

prices, etc.).

Demand shocks in EMEs

EU countries: foreign demand shocks via a decline in world trade

Currency depreciation and funding stress in CEEs

Further deterioration of credit quality in countries

with feeble demand, with weak fundamentals and

still vulnerable banking sectors

EU country-specific aggregate demand shocks (via fixed capital formation and

private consumption)

EU country-specific aggregate supply shocks (via shock on user cost of capital,

nominal wages)

EU country-specific house price shocks

Stalling policy reforms jeopardising confidence in

the sustainability of public finances

EU country specific sovereign bond spread shocks

Lack of necessary bank balance sheet repair to

maintain affordable market funding

EU-wide shock to short-term interbank interest rates

EU country-specific shocks to borrowing costs for households and corporates (via

shocks to respectively, wealth and user cost of capital)

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PROCESS / STORY

DERIVED RESULTS

1

4


RESULTS / SEVERITY3

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A selection of shocks – aggregated summary

Shocks (deviations from baseline, in basis points or percentage)

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Equity price shocks for EU-countries – country specific(percentage deviation from baseline levels in 2016)

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Adverse scenario – respective role of ‘drivers’

•Global shocks account for c. 40% of the total GDP impact

•Shocks to domestic real economic variables account for c. 45-50% of the total GDP impact

•Sovereign debt shocks and bank funding shocks together account for c. 12-13% of the total GDP impact

Contributions of scenario components to GDP impact (percentage point deviation from baseline levels in 2016)

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PROCESS / STORY

DERIVED RESULTS

1

4


RESULTS / SEVERITY3

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Key scenario variables – output for the areas

Deviations from baseline levels by end-2016

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Cumulative GDP impacts in previous CEBS/EBA stress test exercises (Deviation of adverse from baseline growth rates in percentage points)

Comparison with past EU-wide stress tests

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Cumulated impact on domestic GDP (percentage deviation from baseline)

Domestic GDP levels incl. baseline(pre-stress Q0 GDP is scaled to 100)

Pre-stress GDP level

Assessing the severity of the scenario w.r.t. CCARDomestic GDP scenarios

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PROCESS / STORY

DERIVED RESULTS

1

4


RESULTS / SEVERITY3

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Market risk benchmarks – derived from the scenario

• Derived as a function of and consistent with the underlying macro-financial baseline and adverse scenarios; no additional exogenous shocks

• 170 market risk parameters including interest rates, equity prices, commodity prices, swap spreads, credit spreads, dividends, as well as volatilities of market risk parameters

• For major economies such as the euro area, the United States, the United Kingdom, Japan, other developed markets, and major emerging market regions

• Next to historical “scenarios”; different exercise

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Market risk benchmarks – already available

Calibrated market risk parameters

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Credit risk benchmarks – to come next…

• Derived as a function of and consistent with the underlying macro-financial baseline and adverse scenarios; no additional exogenous shocks

• Loss rates projections computed for the EU countries and 20 non-EU countries and regions

• Main portfolio segments includes the non-financial corporate sector (real-estate related and non- real-estate related), household mortgage loans, consumer credit, as well as financial institutions.

Documents

Comprehensive Assessment Stefan Kerbl, Principal Expert, ECB Sunday 26 th October 2014