euro area banks after the 2016 stress test - ecb banking …€¦ · · 2016-09-26euro area banks...

Euro area banks after the 2016 Stress Test

Ignazio Angeloni Member of the Supervisory Board

Conference on

“The Strengths and Weaknesses of European Banking”

Imperial College, London

26th September 2016

DRAFT

ECB-CONFIDENTIAL

Any views expressed are those of the author and do not necessarily reflect those of the ECB

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www.bankingsupervision.europa.eu ©

Overview

2

1 Introduction

3 Overview of stress test results

4 Specific issues

2 Stress test methodology and scenarios

Conclusions 5

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Background: capital of EA banks significantly strengthened in recent years

3

Phased-in and fully-loaded common equity Tier 1 (CET1) ratios of euro area significant banking groups (2009 – Q2 2016; percentages; phased-in CET1 ratio: 10th and 90th percentile and interquartile range distribution across SBGs; fully-loaded CET1 ratio: median)

Source: SNL Financial. Note: Quarterly data are based on a sample of 52 (phased-in) and 45 banks (fully-loaded).

6

8

10

12

14

16

18

20

09 10 11 12 13 14 15 Q114

Q214

Q314

Q414

Q115

Q215

Q315

Q415

Q116

Q216

phased-in CET1 ratio - median for SBGsfully-loaded CET1 ratio - median for SBGs

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Background: RWA density and leverage

4

63 large euro area banking groups. Source: ECB calculations

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Overview

5

1 Introduction


4 Specific issues


Conclusions 5

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Organizational structure

6

• The EBA coordinates the execution of the stress test at EU level

• The EU Commission forecast provides the baseline macro scenario

• The ESRB provides the adverse scenario

• For the euro area, the ECB/SSM

– conducts the EBA stress test on 37 large institutions under its direct supervision (the result are published by EBA)

– executes “supervisory” stress tests on a number of other banks under its direct supervision, using a similar methodology (the results remain internal)

– feeds these results with other information into the Supervisory Review and Examination Process (SREP), to determine the prudential requirements of each bank.

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www.bankingsupervision.europa.eu © 7

Basic methodology

• “Constrained bottom-up” approach: each bank calculates the impact of the two scenarios (baseline and adverse) on its own balance sheet, with a common methodology, subject to quality checks by the ECB

• Time horizon: Base-year is 2015; scenarios extend over a period of 3 years

• Static balance sheets: Balance sheet composition is kept constant; assets and liabilities that mature within the time horizon are replaced with similar financial instruments

• No hurdle rates: No minimum capital thresholds automatically determining capital shortfalls. The results are used in the SREP together with other supervisory information (more on this later)

• Conservative treatment of certain risks: FX lending, ratings downgrades, market risks on AFS/FVO, op. and conduct risk

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Adverse scenario assumes a severe economic downturn with interest rate rise

Methodology and Scenarios

Annual real GDP growth (%)

Adverse Macro Scenario

8

Real GDP level (year 0 = 100)

HICP/CPI inflation (%) 10-year government bond yields (%)

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

Year 0 Year 1 Year 2 Year 3

EBA 2014 EBA 2016CCAR 2016 adverse CCAR 2016 severely adversePRA 2016

95

96

97

98

99

100

101

102

103


0.0

1.0

2.0

3.0

4.0

5.0

Year 0 Year 1 Year 2 Year 3-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0


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Overview

9

1 Introduction


4 Specific issues


Conclusions 5

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Adverse CET1R impact of -3.9pp on average*

Aggregate impact

Final EBA ST Results for SSM banks

In pp

10

13.6

9.1

13.0

∆ CET1R 2018 Adverse

- Baseline

-0.5

CET1R Baseline 2018

∆ CET1R Baseline

2018-2015

+0.5

CET1R 2015 CET1R Adverse 2018

-3.9

Note: Numbers may not match due to rounding

* Weighted by RWA

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Capital depletion: comparison across different stress test exercises

Comparison with other stress tests

The comparison is not straightforward due to differing timeline and scenarios: ST horizon; EBA ST (12 quarters), CCAR ST (9 quarters), PRA ST (20 quarters); CCAR ST considers 3 scenarios: base, adverse and severely adverse.

1 Only SSM banks included in the EBA ST 2016 were included in the results of the EBA ST 2014 | 2 Severely adverse scenario. Adverse impact : 3.9pp. Note: Numbers may not match due to rounding.

PRA 2015 ST EBA ST 20141 EBA ST 2016 CCAR 2016ST2

CET1R Adv. End

S.Adv. CET1 impact

CET1R Starting

CET1R Adv. End

Adv. CET1 impact

CET1R Starting

CET1R Adv. End

Adv. CET1 impact

CET1R Starting

CET1R Adv. End

Adv. CET1 impact

CET1R Starting

11

7.1

12.3 -5.2

9.1

13.0 -3.9

Adverse CET1R Impact

8.6

-2.6 11.2

7.2

-4.0 11.2

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CET1R adverse impact

12

2018 CET1R – Adverse scenario

In pp

7.4

35.4

7.1

17.6

4.6

14.9

2.0

13.5

4.5

11.4

9.1

3.9

11.3

2.7

10.1 9.7

3.3

9.7

3.5

9.7

3.7 6.9

9.6 10.5

3.0

10.2

2.4

9.5

6.0

9.5

4.9

9.0

4.1

9.0

3.9

9.0

2.7

8.8

3.2

8.0

3.4

7.7 7.8

5.6 5.4

8.1

4.2 5.4

8.2

3.9

10.6

6.4 8.5

7.1 7.4 7.0 7.4

3.5

6.1

6.1

8.7

4.0

8.7

4.3

8.6

2.5

8.3

6.9

8.3

3.7

8.2

3.5 4.3

-2.2

14.2

3-year CET1 ratio depletion 2018 adverse CET1 ratio

Results by bank

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CET1 ratio depletion by country

Results by country

13

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Decomposition of stress test impact

14

In percentage points

+0.5

-1.3 Δ Operational Risk -0.4

Δ Administrative Expenses -10.6 ∆ Loan Losses -2.1 ∆ Market Risk +0.9

Δ Net Fees and Commissions Income

∆ Phase-in effect

Δ Net Interest Income 13.0 Trans. CET1 Ratio 2015

+9.8

-0.7

Δ CET1 Ratio

-0.4 Δ Risk Exposure Amount

∆ Non-Interest Income and Capital

13.6 CET1 Ratio 2018

+5.4

Baseline Adverse ∆ Adverse - Baseline

n/a n/a

CET1R differ.

Contri- bution

-1.3 30%

-0.4 8%

-2.0 45%

-1.7 39%

0.5 -10%

-0.4 10%

1.3 -30%

0.1 -2%

-0.5 11%

-4.5 100% 9.1

-3.8

+8.4 13.0

-3.9

-0.8 -0.6

+0.0 -0.9 -10.2

+5.0 -1.1

Decomposition of CET1R impact

Note: Numbers may not match due to rounding

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O-SII Buffer

G-SIIB Buffer

SRB²

Pillar 1

)

Countercyclical Buffer

P2G

Capital Conservation Buffer

P2R

CONFIDENTIAL

Adverse stress test

Max

imum

ap

plie

s

MDA restrictions cover dividends, AT1 distributions and bonuses.

CCAR breach results in dividend restriction (but not on restriction to AT1 distributions or bonuses)

Automatic MDA restrictions kick in after P2B exhausted.

Restrictions cover dividends, AT1 distributions and bonuses

Maximum Distribution Amount (MDA) restriction trigger point

• Use of stress test to calibrate capital requirements: euro area vs US and UK

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Overview

16

1 Introduction


4 Specific issues


Conclusions 5

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NPLs distributed heterogeneously across countries and bank types

17

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Loss rates in the stress test correlate with initial NPLs

NPLs and stress test results (source: EBA)

Enter presentation title by changing the footer. 18

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Sources: Datastream and ECB calculations. The blue line represents the ECB CoE measure derived using banks’ betas and an estimate of the euro area equity risk premium.

Euro area banks’ Cost of Equity (CoE) and RoE (Q4 1999 – Q3 2016, percentages per annum)

-10

-5

0

5

10

15

20

25

Cost of equityRoE

Determinants of price-to-book ratios for 29 large listed euro area banks (2000 – 2015, Annual observations)

Sources: Bloomberg, Consensus Economics and ECB calculations. Notes: Panel regression results; ***, ** and * denotes significance at the 1%, 5% and 10% levels respectively

Sign SignificanceRoE + ***NPL/Total loans - ***Vix Index - ***GDP expectations + ***Assets over equity + ***∆ in the yield curve + ***

R-sq 0.68N 257

CoE, RoE and stock market valuation

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CoE, RoE and stock market valuation

Sources: Datastream and ECB calculations. Notes: The line represents the standard ECB CoE measure derived using banks’ betas and an estimate of the euro area equity risk premium.

Euro area banks’ Cost of Equity (CoE) (Jan 2000 – Aug 2016, percentages per annum)

Source: Bloomberg and ECB calculations. Note: Data are based on a sample of 29 listed SBGs

RoE expectations for euro area SGBs (analyst forecasts for 2016, 2017 and 2018; percentages; 10th and 90th percentile and interquartile range distribution across SBGs)

0

2

4

6

8

10

12

14

16

18

2016 increase

Bank stock prices have been under severe pressure, while profitability expected to remain weak

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Overview

21

1 Introduction


4 Specific issues


Conclusions 5

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Challenges for European banks

22

Conclusions (1)

• NPLs – A major problem, concentrated in a few member states

– Legacy of the crisis, compounded by weak internal governance and controls

– ECB has recently launched a consultation on best practices and guidelines for NPL reduction

• Cost of equity > RoE – CoE mainly driven by high equity premium

– SSM action to support RoE focused on business model sustainability and cost structures

• Adapting to low interest rate environment – Margins are compressed by macro factors (historically low rates and flat yield curves)

– Banks need to enhance sources of non-interest income

• Efficiency and costs – Banks have further room to reduce costs – branch structure, staffing, remuneration

– Banking union and more stable regulation will enhance opportunities for consolidation

• IT and automation challenges

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Challenges for future stress tests (could potentially be fruitful areas for research)

23

Conclusions (2)

• Improve modelling techniques: Study impact of macro scenarios on bank balance sheets; introduce feedbacks from banks to the macro-economy

• Better macro-risk distribution: Scenarios are one realization in the distribution of macro outcome; study ways to take into account the full distribution of risks

• Dynamic balance sheets: Allowing banks to react to adverse macro scenarios

• Nexus between liquidity and solvency: Liquidity risks and their impact on solvency are not explicitly incorporated in current stress testing techniques

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Annex

24

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Overview of Risk Type Drivers

Background slide 1

25

Adverse CET1R Impact

Credit Risk

Net Interest Income

Market Risk

Operational Risk

Non-Interest Income and

Capital

• Stock of defaulted loans, recent default rates, and portfolio composition across asset classes and countries drive loan loss differences across banks in addition to macroeconomic scenario Unsecured retail and unsecured corporates exposure account for c. 70% of total losses Exposure to certain geographies i.e. LATAM and CEE contributes to higher losses, in part, due to

the more severe adverse scenario for these geographies

• Key contributions are the stress to the net margin and loss of any income from defaulted assets under the adverse scenario

• Lower credit quality impacts both contributions as 1. banks with higher amount of defaulted loans tend to have a lower rating and consequently tend

to experience a higher stress to funding costs 2. Income from defaulted assets is more relevant

2016 Available for Sale (AFS)/ Fair Value Option (FVO) Revaluation Losses drive Market risk impact • Non-Sov. AFS/FVO: equity positions have a high contribution to losses compared to their portfolio share • Sovereign AFS/ FVO: Loss contribution from home-country sovereign exposure varies depending on the

concentration of sovereign exposures to the home country, prescribed respective haircuts and duration of portfolio

• Projected NTI 2016-2018 exceeds the 2016 HFT revaluation losses

• Amount of operational risk loss projections correlate with size of the bank (total assets) • In some countries wide-spread issues clearly identifiable as a driver of CET1R impact

• Administrative Expenses have largest negative CET1R impact (-10.2pp CET1R impact), partially compensated by Net Fees & Commissions Income contribution (+5.0pp CET1R impact)

• Significant positive impact under adverse scenario from certain Other P&L items (e.g. other operating income) for which there is no prescribed EBA methodology

• Creation of DTAs under the ST is more than offset by the full deduction of these DTAs in 2018. Positive capital impact from usage of these DTAs is overall marginal (c. 0.1pp CET1)

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Overall impact higher in EBA ST 2016 vs. EBA ST 2014 and varies by risk type

26

Background slide 2

In pp

8.6

0.0

11.2

Other Capital -0.1

Other Profit&Loss Items Impact -5.5

Delta Adverse CET1R

-0.5

-2.6

Loan Losses Impact

Oth. Comprehensive.Income Impact

-4.4

Net Trading Income Impact +0.2

Net Interest Income Impact +8.7

Starting CET1 Ratio

Operational Risk Impact

-0.9 Risk Exposure Amount Impact

Ending Adverse CET1R

∆ST 2016 – ST 2014

+1.8

-0.1

-1.0

EBA ST 2014 EBA ST 2016

• NII impact is comparable across the 2 EBA ST exercises despite the incorporation of an idiosyncratic shock in EBA ST 2016 t

• Loan Losses impact is lower in EBA ST 2016 (-3.8pp) compared to EBA ST 2014 (-4.4pp) • AOCI impact in EBA ST 2016 is higher due to higher haircuts on non-sovereign AFS, revised treatment of hedges

(breakdown of hedged position and hedging instrument in 2016 ST) and gross of tax reporting vs. net in 2014 ST • Impact due to Operational Risk is higher in 2016 (-0.9pp) driven by increased focus in 2016 ST

Observations

+0.6

+0.1

+0.5

-0.2 1

+0.6 2

-0.5 3

-0.9 4

1

2

3

4

9.1

13.0

-3.9

-1.1

-4.9

-0.8

-0.9

-1.0

-3.8

+0.1

+8.4

-1.3

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Integration of Stress Test results into the SREP decision – General EBA Guidance

27

As communicated by the EBA as of 1 July 2016, the 2016 SREP cycle see the introduction of the concept of Pillar 2 Guidance (P2G) to the supervisors toolset complementing the formal Pillar 2 Requirements.

– Banks are expected to meet the P2G which will be set above the level of binding capital (minimum and additional) requirements and on top of the combined buffers

– If a bank does not meet its P2G, this will not result in automatic action by the supervisor and will not be used to determine the MDA trigger. Instead, the breach of P2G will be used to fine-tune remedial measures based on the individual situation of the bank.

CONFIDENTIAL Background slide 3

euro area banks after the 2016 stress test - ecb banking …€¦ · · 2016-09-26euro area banks...

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