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page 1 MFF UK – March 9, 2012 Risk management in banks Leoš Souček, Komerční banka

Risk management in banks Leoš Souček, Komerční banka

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Risk management in banks Leoš Souček, Komerční banka. Introduction / Czech economic specifics … 1/ 2. Private sector indebtedness at the lower end of EU levels Indebtedness of corporate sector at 22% of GDP Indebtedness of households 30% of GDP - PowerPoint PPT Presentation

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page 1MFF UK – March 9, 2012

Risk management in banks

Leoš Souček, Komerční banka

page 2MFF UK – March 9, 2012

Introduction / Czech economic specifics… 1/2

Private sector indebtedness at the lower end of EU levels Indebtedness of corporate sector at 22% of GDP Indebtedness of households 30% of GDP Dynamic growth of mass retail exposure (above 30% yoy in 2003-

2008) slow-downed in 2010/2011 (6.6% yoy in 07/2011)

Also public sector indebtedness lower than EU peers CZ at 38.5% end of 2010 (FR: 82%, DE: 83%, HU: 80%, PL: 55%, SK:

41%, IT: 119%, GR: 143%) Budget deficit narrowed to 4.7% GDP in 2010 (SK: 7.9%, HU: ‑ ‑

4.3%, GR: 10.5%, FR: 7.0%, DE: 3.3%, AT: 4.8%)‑ ‑ ‑ ‑ ‑

Despite fragile political stability some progress in reforms, which help to secure fiscal sustainability

Health care and pension reforms under progress S&P raised the LTFC Czech Republic rating to 'AA-'

No concrete plans on EUR adoption

Limited dependence on external financing Relative low level of external debt in terms of GDP External financing needs covered by FDI and EU funds

Private debt to GDP - 2011Q1

0%

50%

100%

150%

200%

250%

300%

Cyp

rus

Luxe

mbo

urD

enm

ark

Spa

inIr

elan

dP

ortu

gal

Mal

taS

wed

enN

ethe

rland

sU

KG

reec

eA

ustr

iaIta

lyF

ranc

eE

ston

iaG

erm

any

Latv

iaF

inla

ndS

love

nia

Bul

garia

Bel

gium

Lith

uani

aH

unga

ryC

zech

Rep

.P

olan

dS

lova

kia

Rom

ania

Non-financial corporation debt to GDP

Household debt to GDP

0%

50%

100%

150%

200%

250%

CzechRepublic

Hungary Poland U.S. Germany France Austria

Public sector Private sector

Total external debt in % of GDP (Q4 2010)

page 3MFF UK – March 9, 2012

Introduction / Czech economic specifics… 2/2

Loan-to-Deposit Ratio - March 11

0%

20%

40%

60%

80%

100%

120%

140%

Cze

hR

ep

ub

lic

Slo

vaki

a

Po

lan

d

Hu

ng

ary

EM

U

Ge

rma

ny

Fra

nce

Au

stri

a

Limited share of private foreign currency debt 13.0% for private sector (in 7/2011, both residents and non

residents) 17.4% for corporate, 0.14% for households (residents only)

export-oriented corporates as main users 150% coverage ratio by foreign currency deposits (res. only)

Healthy banking sector Confirmed by CNB stress tests Sustained banking sector profitability since early 2000s Favorable loan-to-deposit ratio at 78% July 2011 Strongly capitalized (in end-June, 15.9% average regulatory

capital ratio)

Growth largely relying on external factors … Share of nominal exports on GDP at 80% in 2010 84% of exports concentrated on the EU-27 in 2010

(two predominant partners: Germany 32% and Slovakia 9%) Absence of major macroeconomic imbalances - current

account worsened to 3.8% of GDP in 2010 Substantial foreign ownership following high FDI inflows

... and on the cyclical industry sectors Industry sectors represents 30% of GDP (vs. 22% in Germany

and 12% in France) Highly cyclical (predominant car industry and machinery)

Share in GDP in %

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Agriculture,hunting, forestry &

fishing

Industry Construction Trade, transport &communi-

cationservices

Business activities &financial services

Czech Republic Euro area

page 4MFF UK – March 9, 2012

Zoom on KB:

SG Group member since 2002.

Third largest bank in ČR:

about 7 800 employees.

about 400 point of sales.

KB initially corporate bank.

Retail developed after 2000.

KB’s market share on credit lending: Mortgages: 23%

Small Business: 20%

Corporates: 30%

Municipalities: 40%

Introduction / Banking sector

As of

12/2011

Three key banks (market share at about 70%)

KB (SG Group)

ČS (ERSTE Group)

ČSOB (KBC Group)

Net profit 9,5 13,6 11,2

Deposits (Bn CZK) 586,0 783,3 721,6

Loans (Bn CZK) 441,4 483,5 440,5

Cost of Risk (Bn CZK) -7,3 -5,5 -5,0

o/w loans -2,0 -5,5 -1,8

o/w other risks (Gr) -5,3 0,0 -3,2

Cost of Risk (bps) 181bps (39bps) 114bps 36bps

Loan to Deposits 77,5% 71,9% 69,5%

LUSR 5,7% 6,0% 5,2%

CIR 41.2% 41,8% 44,8%

CAR 14,6% 13,1% 15,6%

ROE 12,3% 18,2% 17,3%

page 5MFF UK – March 9, 2012

Risk Management / Functions & Missions

Credit Risk Management Retail: model based and statistical approach (PD, LGD, EL) Individual approach for non-retail (Corporate, Banks, Sovereign) Collateral Evaluation (independent on client or distribution channel, on-site visits)

Market Risk Management FX, IR, commodity, credit risk, …

Monitoring and reporting Quality of portfolio / Focus on sensitive sections / Distribution channels / Sensitivity to market (FX, IR, ..) Back-testing of models

Recovery / Collection Pre-early collection (-5DPD - 5DPD), Soft collection (5DPD – 90DPD) Hard recovery (90DPD +)

Operational Risk Management Antifraud policy, Insurance, Business continuity plans, estimations of operational losses, …

page 6MFF UK – March 9, 2012

Supervision and Measurement

Scoring modelsMonitoring

Risk MethodologyCredit frauds

Credit Risk Assessment

Corporate deal-flow

Capital Markets

Risks

Market riskCapital markets

Assets Valuation & Recovery

Hard recoveryCollateral Evaluation

Risk Information

Systems

Risk databasis

SG RISQ

Functional links with SG RISQ departments

KB RISQA. Viry (L. Souček)

Risk Management / Zoom on KB organization

Universal Risk Management Function / OpRisk out of scope.

Matrix organization / One of largest Risk Management in the SG Group (330FTE).

page 7MFF UK – March 9, 2012

In-house score-card development since 1998 (IND, SB, Corp, Muni).

SG models used for sovereign and banks since 2002.

KB historical view:

1990 – 1997: Score-card developed by analysts (very simple expert models).

1997 – 1998: Score-card developed by statisticians (consumer loans, mortgages, corp).

2002 – 2003: Models implemented to the central rating system.

2001 – 2002: Behavioural scoring model developed (IND, SB).

2002 – 2005: Review of models with SG after acquisition.

2002 – 2007: Progressive usage of credit bureaus for retail (CBCB, SOLUS).

2005 – 2007: Implementation of Ba2 standards in KB (advanced methods for all credit portfolios).

2008 – 2011: Development and implementation of credit fraud prevention.

Risk Management / History of model development in KB

page 8MFF UK – March 9, 2012

MONITORING / REPORTING CREDIT RISK

MARKET RISKOPERATIONAL RISK

RECOVERY

NOT INTEGRATED CYCLE LOW UNDERSTANDINGMODEL RISK

3 DANGERS

Risk Management / Key risks for the bank

page 9MFF UK – March 9, 2012

CCFLGD

Default, PD= 100% “90DPD or unlikely to pay”

Off B/S

On B/S

Recovered cash

Actual Exposure = On B/S + Off B/S

Exposure at Default (EaD) = On B/S + Off B/S * CCF

Recovery processNon-Default, PD < 100%

Credit Risk / Key elements PD, LGD, EaD

Expected Loss (EL) = EaD * 1Y PD * LGD

Risk Weighted Assets (RWA) = RW * EaD

RW = Function (PD, LGD, Maturity, Regulatory correlation, Regulatory interval of conf. 99.9%)

1Y PD = Probability of Default during following 1Y

LGD = Loss Given Default

EaD = Exposure at Default

RW = Risk Weight

RWA = Risk Weighted Assets

page 10MFF UK – March 9, 2012

Probability 99,9%

Probability 0,1%

Stress Testing

SIZE OF LOSSES

FREQ

UEN

CY O

F LO

SSES

Expected Losscovered by revenues

Unexpected Losscovered by the capital

Extreme Loss

!!! DEFAULT !!!

Bank Capital

Market Risk RWA + Credit Risk RWA + Operational Risk RWA> 8%CAR =

CAR = Capital Adequacy Ratio

Regulatory minimum at 8%

Unexpected Loss as a variation of Expected Loss

Credit Risk / Ability to absorb a loss

page 11MFF UK – March 9, 2012

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

-1% 0% 1% 2% 3% 4% 5% 6% 7%12 Month Probability of Default

Loss

Giv

en D

efau

lt

Sovereigns

Large corporates

Banks

RE Developers

SME

PSE

Small Business

Project finance

Residential mortgages

Consumer loansCredit Cards

Credit Risk / Credit portfolios per PD & LGD

Expected Loss

Expected Loss

Client rate: 3,5%

Net margin1,0%

Expected Loss

0,5%

Cost of funds2,0%

Expected Loss (given by PD and LGD) is reflected in pricing.

page 12MFF UK – March 9, 2012

Economic RatingFinancial RatingBehavioural Rating

Model Rating

Final Obligor Rating

Credit analyst

Credit Risk / Corporates / Rating Model

Moody’s S&P 1Y PD CountryAaa AAA 0,01% DE, USA, FR (M)Aa1 AA+ 0,01% FR (S&P)Aa2 AA 0,02% BE, SIAa3 AA- 0,03% IT, JPA1 A+ 0,03% CZ, SK, CNA2 A 0,04% PL

A3 A- 0,06%

Baa1 BBB+ 0,13%Baa2 BBB 0,26% RU, BR

Baa3 BBB- 0,50%Ba1 BB+ 1,10% HU, RO

Ba2 BB 2,12%Ba3 BB- 3,26% BUL

B1 B+ 4,61%B2 B 7,76% UA

B3 B- 11,42%

Caa1 CCC+ 14,33%

Caa2 CCC 20,44%

Caa3 CCC- 27,25%Default 100,00% GR

Rating scales for non-retail Individual assessment is prevailing. Financial assessment (financial data) Economic assessment (position in market, …)

Model rating revised by credit analyst.

page 13MFF UK – March 9, 2012

SCORING MODEL(YES / NO)

DATA COLLECTION (COMPLEX INFORMATION ABOUT CLIENT)

APPLICATION FORM(DEMOGRAPHIC DATA)

CREDIT REGISTERS(CREDIT HISTORY)

INTERNAL BANK DATA(BEHAV. DATA)

TRANSACTION PARAMETERS

INSTALLMENT LIMIT(YES / NO)

COLLATERAL EVALUATION(YES / NO)

CREDIT ANTIFRAUD SYSTÉM (IDENTITY, EMPLOYER, DATA)

COLLATERAL

Credit Risk / Retail / Granting process

Maximally automated (95% of approvals) / Maximally parameterized / Maximally centralized.

Data collection / Independent verification / Assessment by statistical model.

page 14MFF UK – March 9, 2012

Demographic Model (application form)

Credit Register Model(data from the register)

Behavioural Model (data in the bank)

Application rating

Behavioural Models(data in subsidiaries)

MAIN DRIVER OF PREDICTING POWER • Basic Behavioural SM (Bank)

• Complex Behavioural SM (Group)

• Advanced Application SM

• Advanced Behavioural SM

3 KEY ADVANTAGES

High predicting power.

Complex assessment.

High flexibility (4 boxes).

IN KB SINCE 2002

IN KB SINCE 2007

IN KB SINCE 2006

IN KB SINCE 1998

Credit Risk / Retail / Scoring Model

page 15MFF UK – March 9, 2012

1 200 ths. clients EUR 6 400M

300 ths. clients EUR 1 200M

80 ths. clients EUR 32M

170 ths. clients EUR 400M

2002 201120062004

AO AO, CL, CCAO, CL, CCAO, CL, CCPRODUCTS

MAX LIMIT EUR 400 EUR 10 000EUR 6 000EUR 2 400

CLIENTS KB KB GROUPKBKB

3 KEY ADVANTAGES

Fast and easy process

High volume of production

Top quality of production

3 KEY RISKS

No view of expenditures

Limited assessment

Change of behaviour

Credit Risk / Retail / Scoring Model

page 16MFF UK – March 9, 2012

CONTACT

RNDr. Ing. Leoš Souček

Deputy Head of Risk Management

Komerční banka, a.s.

Tel: +420 222 435 141

Email: [email protected]