This is about my personal view on stress-testing for Basel 2 & ICAAP requirements, but on a practical basis

1. Stress Testing in the
context of ICAAP
Stress Testing: The Challenges &
Practical Issues of Implementation
- A Personal Perspective
Khoo Guan Seng, PhD
Head, Group Risk (Models Validation)
Standard Chartered Bank
Khoo.Guan-Seng@standardchartered.com
gskhoo@gmail.com

2. Agenda –
• Introduction and backdrop
• What is stress testing? - Definition
• Why stress test (Supervisory & banks’ expectations)
• Stress Test - External Drivers
• Stress Test - Internal Drivers
• Key Elements of a Stress Testing Process
• Types of Risk Factors
• Categories of Stress Tests
• Sound & Best Practices
• Implementation challenges
• Liquidity Risk Stress Test (Example)

3. The 3 Pillars & Stress Testing
Minimum requirements provide economic
incentives - in the form of lower capital
charges*
*For those banks that develop better
Minimum
measures for their exposures to risk
Capital
and better techniques for managing
Requirement
their risks
Hence, banks perform
back-tests on their risk
models to ensure they are
Pillar 1 valid and measure risk
exposures appropriately
Generate capital
requirements

4. Supervisors evaluate how
bank performs internal
processes for risk
management
Supervisory
Review Process
Supervisors check that
parameters and conditions
used to evaluate risk
Pillar 2
measures are sound and
rigorous – How?
One such tool/approach:
Outcome of Stress Testing

5. The third pillar seeks to
leverage the ability of
markets to provide discipline
Market
to banks to ensure that they
Discipline
are not holding unrealistically
Requirements
low levels of capital
Pillar 3
Hence, banks perform
stress tests to ensure
banks’ capital adequacy in
times of shocks
Enhanced market
transparency & reputation

6. Pillar 2 Overview
Supervisory
Firm assessment
assessment
Identify and assess material Review and evaluate all risk
risks and control factors
Identify mitigating controls
Identify amount of capital in Dialogue Review and assess the
and
relation to business plan, firm’s risk assessment
challenge
strategies, and profile
Produce capital number and
Supervisory conclusion
assessment

7. Capital Planning and Stress
Testing
Objective:
• That the firm can meet its capital requirements at all times
through out a reasonably severe economic recession.
Why capital planning?
• Elements 1 to 3 are static
• Assure the firm will have sufficient capital tomorrow
Two aspects:
• Capital planning, and
• Stress testing

8. Capital Planning and Stress
Testing
Illustration: pre/post management actions
£
CRR (pre)
• Cut dividends • Raised extra
• Reduced costs capital Capital (post)
CRR (post)
•Reduced business volumes Capital (pre)
time
Yr 1 Yr 2 Yr 3 Yr 4 Yr 5

9. Cyclicality Credit Stress Test
• A subset of Pillar 2 capital planning and
stress tests
8Scope is narrower than Pillar 2
8Static balance sheet
• Same degree of severity (1:25)
• The gross test must be assessed under Pillar
1
• The benefit of management actions and
capital impact is considered under Pillar 2

10. Pillar 2
Interest Rate Risk in the
Banking Book
(IRRBB)

11. Rules – a selection (paraphrased)
• GENPRU 1.2.30R
8 Firm must have in place sound, efficient and complete processes, strategies and
systems to identify and manage …. interest rate risk
• GENPRU 1.2.42
8 A firm must carry out stress tests and scenario analyses appropriate to its
business based on realistic adverse circumstances, and estimate the financial
resources needed
• BIPRU 2.3.2 G
8 IRRBB will normally be a major source of risk for a bank, building society (and
investment firm with non-trading book >15% of total).
• BIPRU 2.3.3G
8 Interest rate risk can arise from:
• Mismatch of repricing periods (yield curve risk)
• Inaccurate hedging where the hedge reprices on a different basis to the exposure
(basis risk)
• Uncertainties in the timing or occurrence of future transactions (model risk)
• Early redemption of fixed rate products (embedded optionality risk)
• BIPRU 2.3.7R & 2.3.12
8 Requirement to stress test exposure to interest risk generally (annually) and to a
200bp parallel yield curve shift (at least 1/4ly)

12. Regulatory approach
• IRRBB will be one of the top three Pillar 2 risks on
which supervisors will focus when reviewing an ICAAP.
• The CRD’s approach to assessment of risk is based
principally on changes to economic value arising from a
change in interest rates
8Key test is whether a 200bp parallel yield curve shift in either
direction reduces economic value by >20% of capital
resources
• The FSA recognises that firms will normally measure
their risks both from an earnings and an economic
value perspective
8Relative importance of these measures will vary from firm to
firm
8Accept that measures to hedge earnings may increase
economic value at risk on an ongoing concern basis

13. Stress testing
• Sudden 200 bp parallel shift in both directions is at
best a crude measure
• FSA expects firms to apply stresses more relevant to
the composition of their Non-Trading Book
8Effect of earnings hedges may be neutralised in
assessing economic value at risk
8Allowance may be made for behavioural expectations
• Need to document key assumptions
8FSA will particularly wish to understand basis for
behavioural adjustments

14. Proportionality
• IRRBB approach is as for other Pillar 2 risks:
8 Firms with relatively non-complex business profiles can
apply less sophisticated approaches to capturing and
measuring their risks
8 Larger and/or more complex firms may be expected to
adopt more advanced modelling techniques, e.g.
• Dynamic rather than static balance sheet modelling
• Simulation modelling to capture non-linear/option risks
• Behavioural models to determine hedging strategies

15. Non-prescription
• FSA has not sought to prescribe how IRRBB should be
measured, nor how capital should be attributed.
8Such prescription would in their view be contrary to the
principles underlying Pillar 2
8A recent thematic review undertaken by the Risk Review
Department identified a range of approaches/market practices
in this area
8However, the objective is still that risk should be measured &
mitigated
• Some overseas regulators are taking a different
approach: e.g. APRA
8Has chosen to include IRRBB within Pillar 1
8IRRBB models need to meet general and specific
requirements before approval is given for their use
8Calibration is to 99% over a one year holding period

16. From Pillar 1 to 3
Risk management process
• Basle document (Jan ’96) – spells out stress testing as one of the
prerequisites for internal model approval
• Capital viewed as the last line of defense in a bank. When risk
management is insufficient, when reserves are exhausted, capital
absorbs losses to prevent a bank’s failure.
• But when capital runs out, the bank may become insolvent, leaving
public authorities and taxpayers responsible for restoring depositors’
savings
The challenge is determining how much capital is sufficient
• Stress testing is considered to be an effective and necessary tool that
complements statistical models for quantifying & monitoring risk and
capital adequacy
• By its very nature, stress testing also sets a high qualitative and
quantitative standard for risk management

17. 2. What is Stress Testing?
(in banking)
• Stress testing refers to
“the analytical process involved in subjecting a bank’s
portfolio to a series of battery of tests, designed to study
the performance of the bank’s portfolio under extreme
adverse conditions to generate the potential risk
measures under plausible events in abnormal markets”.

18. Definition
Key Points
• Series of Battery of Tests
- More than 1 test or set of results
• Extreme Conditions
- Degree of severity critical
• Plausible Events in Abnormal Markets
- Unexpected and could have happened to competitors
or in other countries
- Paradigm shift in global financial markets
- Historical (local) worst case

19. 3. Why Stress Test
(Supervisory & Banks’ Expectations)
What does the regulator What does the bank hope to
hope to achieve? achieve?
- Able to understand mechanism - Identify where the risk
through which stress develops, concentrations are?
- Understand impact on bank if
- Able to implement measures
biggest customers default?
when the effects of stress events
- Impact on bank if historical
evolve into a vicious circle
worst-case scenario recur?
involving the real economy,
- Impact on bank if it is hit by a
financial markets and the
similar severe credit loss event
banking sector
that affected competitors in the
- etc……
past?
- etc…..

20. Other Considerations
Why?
• Economic downturns always follow
buoyant periods and economic expansions
• Unknown issue is when, the severity and
scale of the economic recession
• Can’t afford to be complacent
• Proof of certainty of global recession –
next few slides

21. Stress-testing and Impact on
Economic Capital in Validation

22. Basel II-compliant Integrated Approach to Risk Management
– Objective at End Point
Key:
Reporting Reports
Basel 2
Basel 2
Fulfill Requirements of the 3 Pillars
Data
of Basel II
IAS
IAS
Shared Regulatory
Shared Regulatory
Internal or
Internal or Analysis
Analysis
management
management
Market
• Organization, • Profitability
Discipline
Regulatory Reporting Data Mart
Regulatory Reporting Data Mart
Disclosure
Disclosure
Policies, Procedures Analysis
Requirements
• Human Resource, • Portfolio Risk
Culture Concentrations &
Mitigation Analysis Internal
Internal
• IT & Systems
• Impact Analysis
• Process, Culture &
from Stress Tests &
Regulatory Disclosure Capability
Regulatory Disclosure
Economic Capital Analysis
Analysis
Quantification
• Risk & Economic
• Organization, • Investor Relations Capital
• Risk Transfer &
Policies, Procedures Information Quantification
Diversification
• Human Resource, • Stress Test results • Portfolio Risk-
• Challenges &
Culture Return
• Risk & Economic competition
Capital Quantification Concentrations
• IT & Systems
• Environmental Financial and
Financial and
• Process, Culture & change analysis Management
Management
GL
GL
Capability Accounting
Accounting
• etc.
• Risk & Economic
Capital Quantification

23. Basel II-compliant Integrated Approach to Risk Management
- Risk Models & Measurements/Scenario Analysis
Key:
Calculation engines act on Ratings, Calculators Reporting Reports
Basel 2
Basel 2
Loss Distribution to yield the PD Data
IAS
IAS
(PE), LGD (LE), EAD, VaR as well
Shared Regulatory
Shared as EC (CaR) Regulatory
Basel II
Basel II
Severity
Severity Calculation
Calculation
Regulatory Reporting Data Mart
Regulatory Reporting Data Mart
Disclosure
Disclosure
Engines
Engines
Monte-Carlo
economic capital (EC) by Internal
Internal
simulation
scenario type
Frequency Market &
Market &
External
External
De-pegging of USD/RMB CaR1
Asian Financial crisis/Pandemic flu CaR2
Terrorist threat & rise in NPL CaR3
Succession & general election CaR4
IAS Calculation
IAS Calculation
Sectoral distress, e.g., dotcom bust Engines CaR5
Engines Financial and
Financial and
Fall in FDI (threat from China/India) CaR6 Management
Management
GL
GL
Bank merger & loss of market share CaR7 Accounting
Accounting
_____
Average Economic Capital
Adjust severity & frequency
distribution

24. RECAP: Volatility in EL
• For Stress Tests, exaggerate changes in risk drivers
according to different levels of severity
Rating Data
Rating Data
• Change in portfolio’s EL,
Severity
∆EL, dependent on key risk Severity
PD, LGD, EL
PD, LGD, EL
factors/drivers, e.g.,
Rating migration
Rating migration
∆EL = c1∆I + D + c2∆FX + c3∆GDP
+ c4∆DR + c5∆CGV + …….
99.99% level Risk Weights
99.99% level Risk Weights
• Volatility in EL leads to Loss
distribution => @99% Loss Distribution
Loss Distribution
confidence level = UL => EC

25. U.S. Yield Curve Inverts Before Last Five Recessions
(5-year Treasury bond - 3-month Treasury bill)
% GDP Growth/
Yield Curve
8 % Real annual GDP growth
6
4
2
Yield curve
0
-2
Recession Recession ?
Recession
Correct Correct
Correct
-4 Recession
Correct 2 Recessions Data though 12/5/00
Correct
-6
9
1
3
5
7
9
1
3
5
7
9
1
3
5
7
9
1
-6
-7
-7
-7
-7
-7
-8
-8
-8
-8
-8
-9
-9
-9
-9
-9
-0
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
ar
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M

26. Getting the
Basics Right –
The Importance
of Data
Considerations

27. Validation via Recessionary Stress Test
Remarks by Governor Susan S. Bies
At the Annual International Symposium on Derivatives and Risk Management,
Fordham University School of Law, New York, New York
October 8, 2002
Corporate Governance and Risk Management
I want to thank Dean Treanor and Alan Rechtschaffen for the invitation to participate in
this timely symposium on corporate governance issues. When I joined the Federal
Reserve Board of Governors last December, I knew I would be doing more than helping
to set short-term interest rates. ……..
Another major category of risk is credit risk, which also has become much more
quantified. …… the borrower's likely exposure at the time of default, taking into
consideration future draw-downs. The greater use of credit models in retail transactions
provides a stronger framework to assess risk and ensure that pricing reflects credit
quality. For consumer credit, however, models are less proven, since data
collection and loss estimates generally evolved after the 1990-91 recession and
so have not been proven under stress conditions or for subprime borrowers.
Because many of these borrowers did not have significant access to credit in
previous recessions, their ultimate default rate in the current cycle should help to
validate the strength of the new statistical models. ………….

28. Ensure reliable data
KEY ELEMENTS in
STRESS TESTING Survey Portfolio & Environment
Framework
Identify Risk Factors
Construct Stress Tests
Yes No
Does the bank possess
quantitative risk measurement
systems?
Estimate bottomline of
Run Stress-tests using
counterparties under
counterparty & portfolio
stressful conditions
risk models
Calculate Stress Loss
Report Results
Take Corrective Action, if reqd
Reassess Stress tests for
appropriateness

29. Minimum requirements for the
Foundation IRB Approach
• …….
• Completeness & integrity of ratings
• Min. requirements for estimation of PD
• …….
• Use of internal ratings
Internal ratings to be used in credit approval process
Stress testing, performed at least semi-annually, to
be used in the internal assessment of capital
adequacy. Such stress tests to cover the impact of
broad, downward rating migration and the impact of
higher than predicted default rates (PDs) & LGDs
At least 3 years’ usage of internal ratings information
……

30. VI. Portfolio level stress testing,
practical application and range
of practice - Pillar 2 principles

31. Implications for Stress Test
• Top-down Approach/Macro-view
• Relate to Objective
– impact is bank-wide
• Basel compliant framework
– PD and LGD are critical elements of the
Standardized and IRB Approaches in the Basel
Accord
• Risk weight calculations also affected*
– Hence, portfolio or sub-portfolio approach
recommended
• Stress test within generic framework

32. Identify the Main Objective
What does the bank hope to achieve?
• Identify where the risk concentrations are?
• Impact on bank
– if biggest customers default?
– if historical worst-case scenario recur?
– if it is hit by a similar severe loss event that
affected competitors in the past?
– etc…..

33. Risk Monitoring (Stress Test)
&
Risk Concentration
• What’s the relationship?
• Worthwhile & logical to start somewhere:
– Where?
– What?
– How?
– Why?

34. Where to Start?
• First place to start is to examine the
portfolio of weak assets
– findings arise from risk monitoring
• The weak assets are typically the first
to default
• Then, proceed with all customer
segments as during the Asian crisis,
even highly-rated customers were
affected

35. What to Do?
• With weak assets or customers, one stress
test model (scenario) is for all of them to
default
• With the other customers including the
highly rated ones, one possible scenario is
to have all of them downgraded in credit
quality by a few notches or severely
downgraded to default status

36. How to Do It?
Perform the stress tests at the portfolio level:
• Using scenario analysis (multiple scenarios)
– e.g. a scenario where all are downgraded with some
defaulting or all defaulting,
– etc.
• Performing sensitivity analysis within each
scenario
– e.g. varying severity of downgrades (one notch
instead of 2 notches),
– or increasing the PD or LGD for different customer
rating,
– etc.

37. Why Do It?
I. Stress Tests will yield info about:
• Extent of unexpected loss based on different
scenarios as well as degree of severity & risk
drivers
II. The info above will help provide early warning signs
• of where the bulk of the likely credit risk exposures
are going to come from and
III. Prepare the bank to strategize
• on how to avoid or minimize them in case they
occur

38. OVERVIEW
Corporates
Listed
CREDIT
PORTFOLIO
1st LEVEL 2nd LEVEL
SME’s
Consumers
Unlisted
GENERIC (I) SCENARIO ANALYSIS
STRESS Downgrade customer
rating through several
TESTING notches (have a range of (II) SENSITIVITY ANALYSIS
scale, for example: one
FRAMEWORK notch down or 2 notches Vary PD and LDG for each
down) item
Mixture of downgrades &
defaults
Default some categories of
customers

39. OVERVIEW OR STRESS
TESTING THE
WHOLE CREDIT
PORTFOLIO OF
CUSTOMERS USING
A GENERIC
FRAMEWORK
Corporates
Listed
STRESS TEST
PORTFOLIO OF
CORPORATES
USING a Generic
FRAMEWORK
STRESS TEST
PORTFOLIO OF
SMES USING a
CREDIT Generic
STRESS TEST
FRAMEWORK
PORTFOLIO OF
PORTFOLIO
CONSUMERS
USING a Generic
FRAMEWORK
SME’s
Consumers
Unlisted

40. Stress Test Outputs
• Can yield
– several types of reports for different
customer segments
• corporates, SMEs, consumers
– several reports
• for different scenarios
• different degree of severity
– bankwide portfolio reports for different
scenarios & degree of severity

41. IMPACT OF STRESSED ENVIRONMENT
Credit Portfolio
1) Credit ratings
downgraded
Corporates
Unlisted & SMEs Consumer
(Listed)
2) Higher default
incidences
Ratings Ratings Ratings
AAA 3) Lower recovery
rate or higher LGD
AA
A+
A- A-
BBB BBB
BB+ BB+
BB- BB- BB-
B B B
CCC CCC CCC
D (default) D (default) D (default)

42. Probability of Default (PD)
& Loss Given Default (LGD)
• Both concepts are tied and intimately linked
to negative risk factors and economic
environments, be it a rise in interest rate,
higher unemployment, loss of FDIs, etc.
• Changes in PDs and LGDs are the
manifestation of negative stressed
environments or periods of economic
contractions irrespective of the causes

44. Behavioral Credit Risk Monitoring as a
Measure of Impairment Incidences
31 MAY
Group 6 Risk Migration - Changes in CRR of Existing Accounts (YTD)
2000
•The same assessment needs to be made 31 MAY
Group 1 Risk Migration - Changes in CRR of Existing Accounts (YTD)
2000
for existing customer relationships within 31 MAY
Risk Migration - Changes in CRR of Existing Accounts (YTD) 2000
the portfolio to keep track of risk
movements. CRR Illustrative
SGD ‘millions
•The risk migration of existing account are
aggregated at the Year to Date level for the 10 8 16
effect on the portfolio risk as the annual 9 1 18 12 SGD ‘millions
revisions of the customer relationship are
progressively done. 8 Improve
13 10
17
d = 242
7 5 12 12 12
Key Insights Unchange
d= 267
last 6 12 27 74 16 5 22
• tracking of YTD CRR changes of existing period Declined
customers and the corresponding impact 5 16 19 52 19 10 = 240
on overall asset quality
4 28 21 26 25 9 Total
• early warning signal for deteriorating approved
accounts 3 18
30 22 18 15 22 limits revised
= 749
12 13 22 22
12
2
28
1
CRR
1 2 3 4 5 6 7 8 9 10
No. of
this period
customers
Total
1 2 3 4 5 6 7 8 9 10
CRR
- 4 7 11 18 24 9 10 13 3 99
improved
declined 0 7 6 4 10 5 4 6 0 ... 42
net effect 0 -3 +1 +7 +8 +19 +5 +4 +13 +3 + 57

45. Example of Downgrades in Risk
Migration for Stress Test Scenario
Distribution of Accounts
0.12000
0.10000
Recent Sample
Development Sample
0.08000
Proportion
0.06000
0.04000
0.02000
0.00000
Score
Score

46. Application to economic capital
calculation and allocation
Table 1 Calculating the IRB Risk Weights
CALCULATING
THE IRB RISK
WEIGHTS RISK WEIGHTS: Foundations Advanced
EAD PD % LGD % G(PD) 1st paren N(col.F) (1-PD)/PD RW RW
Rating $mil LGD=50% actualLGD
-
AA 210 0.01 0.01 3.719090272 -2.869942924 0.002052795 57.5382393 7.425464426 0.001485093
-
A 15 0.05 0.02 3.290559929 -2.390846001 0.008404792 28.32931 19.13508759 0.007654035
-
BBB 0 0.77 0.44 2.422833007 -1.420727302 0.077698074 8.44475535 105.9860987 0.932677669
-
BB 0 1.11 0.87 2.286927358 -1.268784787 0.102258982 7.16490219 133.4824091 2.322593919
-
B 125 3.45 44.81 1.818419019 -0.744992463 0.228138065 4.24728962 267.2481112 239.5077573
-
<B 210 5.69 57.62 1.581341423 -0.479939711 0.315635136 3.32895824 356.4417735 410.7634998
-
Unrated 95 4.33 63.22 1.713611669 -0.627817846 0.265061575 3.80821185 305.1600339 385.8443468
Total 655

47. Table 2: Calculating the Minimum Capital Requirement
CALCULATING THE MINIMUM CAPITAL REQUIREMENT: January 2001 Proposals
Stan
dard Foundations
EAD ized RWA RW RWA Adv. IRB RW RWA CAPITAL REQUIREMENTS
$mil
lion EAD * Standar Foundations Advanced
s RW RW RW EAD*RW EAD*RW dized IRB IRB
210 0.2 42 0.074254644 15.59347529 1.48509E-05 0.0031187 3.36 1.247478023 0.000249496
AA
15 0.5 7.5 0.191350876 2.870263139 7.65404E-05 0.00114811 0.6 0.229621051 9.18484E-05
A
0 1 0 1.059860987 0 0.009326777 0 0 0 0
BBB
0 1 0 1.334824091 0 0.023225939 0 0 0 0
BB
125 1.5 187.5 2.672481112 334.060139 2.395077573 299.384697 15 26.72481112 23.95077573
B
210 1.5 315 3.564417735 748.5277244 4.107634998 862.60335 25.2 59.88221795 69.00826797
<B
95 1 95 3.051600339 289.9020322 3.858443468 366.552129 7.6 23.19216257 29.32417036
Unrated
Total Capital
655 647 51.76 111.2762907 122.2835554
TOTALS Requirement=
Capital/Assets
0.07902 0.169887467 0.186692451
=

49. 6. Key Elements of a
Stress Testing Process
Background Understanding
• Majority of banks’ failures: Credit Risk (recent: Oprisk & liquidity)
• Recession cycle: typically 2 years or more
• Default likelihood of counterparties or obligors: usually not within the
1st year of getting the loan
Before embarking on stress testing, what are the lessons?
• Data history
• NPL, PD & LGD definitely increase in recessionary times
• Consider stress testing at every stage of credit risk management
process, including credit assessment & application stage (e.g.
cutoff/limit at credit scoring), etc.
• Don’t neglect market & operational risks aspects

50. Key Elements
(Assumptions)
1. “Infrastructure” readiness:
• Sufficiency & types of data to cover good & bad times
• MIS & Data-warehouse capability
• Expertise (in-house or external)
2. Scenario selection & appropriateness (The 3 “Rs”):
• Relevance: Europe-centric events (Euro crisis) may not
apply in Asia
• Realistic: Hypothetical Scenarios should be plausible in
local context, e.g., LTCM-type loss events may not be
applicable to some Asian markets
• Reliable & Readily Available Database: The Scenario
chosen should be one where the institution is able to
collate and analyze the data pertaining to it

51. Ensure reliable data
KEY ELEMENTS in
STRESS TESTING Survey Portfolio & Environment
Framework
Identify Risk Factors
Construct Stress Tests
Yes No
Does the bank possess
quantitative risk measurement
systems?
Estimate bottomline of
Run Stress-tests using
counterparties under
counterparty & portfolio
stressful conditions
risk models
Calculate Stress Loss
Report Results
Take Corrective Action, if reqd
Reassess Stress tests for
appropriateness

52. Reliability of Data
• Stress Testing involves the use of models based
on unexpected events on a practical basis
• Documentation and Access to database is
important
• Data should be sufficient to capture the
downside change as well as the pre-event and
post-event dynamics so that the critical risk
factors are also captured
• Choice of risk factors in determining the
explanatory power

53. Survey Portfolio & Environment
Preliminary work necessary:
• Management & personnel in bank
involved in stress-testing have to arrive
at a consensus regarding the scenario or
series of scenarios to be “stressed”,
• An agreed upon “benchmark” which can
also be used in subsequent studies, e.g.
historical worst-case scenario and to
help define the KRIs for future
benchmarking

54. Identify Risk Factors
• This process will go hand-in-hand with the
model and scenario chosen
• Different types of risk factors may suit different
economic environments or types of stress tests,
e.g.,
- with Asian financial crisis, risk factors could be
market factors like interest rates, and currency
exchange fluctuations
- with dotcom bust, default probabilities, corporate
bankruptcies or unemployment figures could be
used as risk factors

55. Construct Stress Tests
• Once the basic prerequisites are satisfied:
scenario chosen, KRFs defined, relevant
data collated
• Next step is to construct the stress test
based on the above in terms of dimensions
of evaluation and interpretation of results

56. Dimensions of Evaluation
• Risk:
– Severity & range: Loss Quantum & Range of
loss quantum, e.g., varying the loss given
default (recovery rate)
– Frequency & range: Probability of loss, e.g.,
varying the probability of default

57. Scenario Analysis
Causes Scenario (s) Evaluation
(Potential Event)
Severity of potential loss
Scenarios 1, 2, …
Range of severity
Failure of
relevant risk Typical severity
factors
Frequency of potential loss
Failure of
Range of frequency
relevant risk
factors
e.g. THB crash
Typical frequency
(+ ∆THB) – sensitivity analysis
Severity of change in KRF

58. 7. Types of Risk Factors
Counterparty Environmental Model Analytics
Deterioration in ability • Financial Market factors • Assumptions • Correlation
and/or willingness to
• Industry • Holding period • Transition Matrices
pay:
• Economic • Product • Volatility
• PDs
complexity
• Regulatory
• LGDs
• Political
• Credit Spreads
• Sociological
• Ecological

59. Session 2
Includes examples for stress testing in:
• Market risk
• Credit risk

60. 9. Sound & Best Practices
Stress Testing Decision Sequence
Type of risk model
Market risk Credit Risk Other
(interest rate risk, (liquidity, operational)
exchange rate risk, etc.)
Type of stress test
Sensitivity single factor Scenario Other
(multiple factors) (extreme value,
maximum loss)
Type of shock
Individual market variables Underlying volatilities Underlying correlations
Type of scenario
Historical Hypothetical Monte Carlo simulation
Core assets to be shocked,
Assumption: Data & MIS size of shocks, and
Sufficient & Capable – ideal time horizons
state
Aggregation, comparison with present portfolio

61. Examples – Market & Credit Risk
• Type of risk model – market & credit risk
• Type of stress test – scenario (multiple factors)
• Type of shock – underlying volatilities
• Type of scenario – Monte Carlo simulation
• Allowance for re-test – for varying degrees of
shocks or sensitivity analysis
Examples – Risk Optimizer, etc.

62. 10. Implementation Challenges
Alternatives
1. Lack of data
• Boot-strapping
• Theoretical distributions & model
• Proxy benchmarking
• Peer group (overseas) comparison, e.g.
mortgage loan default in neighboring
countries
• etc

63. Example: Credit Stress Test Roadmap
Balance Sheet Accounting Asset-Liability IRB Compliant Portfolio
LLP/NPL Model
Model Model Model Stress Test Model
Based on Basel 2
Lack of Data on Financial ratio- ALM model
Financial ratio- Use of IRB factors
PD, LGD, based model like PD, LGD and
based model
customer ratings Use of equity RW formulations
indicators like
Altman’s Z-score
Emphasis on
Incorporates share price and
model & Incorporates
macroeconomic ratios related to market cap
derivatives downgrade of
factors – more ratings & increase
liquidity and
easily available Monte Carlo
Trend Analysis of in defaults
solvency
simulations with
Z-scores over a
LLP/NPL data adjustments to
couple of years Relate results
from bank itself Augment with forecasts of directly to capital
returns, volatility requirements
profitability &
e.g., Linear and liabilities
efficiency ratios
Regression Applicable to sub-
Analysis portfolios of
Value-add on LLP different customer
segments
Model
Continuous collation of customer data, PD, LGD

64. Linear or non-linear regression
of own internal model
• Change in firm’s NPL, ∆NPL, dependent on key
risk factors, e.g.,
– Change in interest rate, ∆I
– Change in currency rate, ∆FX
– Change in GDP growth, ∆GDP
– Dummy variable, D (D = 0, when no terrorist threat, D
= 3 when there is terrorist threat)
– Coefficients, ci
∆NPL = c1∆I + D + c2∆FX + c3∆GDP + …….

65. Q&A: Implementation Challenges
Alternatives
2. Lack of risk analysis tools
• Qualitative judgement (expert opinion)
regarding choice of parameters and risk
factors & model – expert system
• Macro-impact of changes in Balance Sheet,
Asset&Liability
• etc

66. Low High
Balance Sheet Stress Test Stress Stress
2 1 or less
Liquidity
– Current ratio
Related KRIs 30% 60% or more
Solvency
from Financial – Debt to Asset ratio
Analysis Profitability
Negative
– Net Operating Income
5% 1% or less
- Rate of return on assets
10% 5% or less
Example - Rate of return on equity
135% 110% or less
Repayment Capacity
- Debt coverage ratio
60% 80% or more
Efficiency
- Operating expense ratio
10% 20% or more
- Interest expense ratio
40% 20% or less
- Asset turnover ratio

67. Linking market and credit stress
testing
Modigliani-Miller (1958): Firm value = Equity value + Debt value; Others: look at credit spread widening & credit indices
Equity value
Liquid case (e.g. Investment
Liquid case (e.g. Investment
Firm value
Market parameters (Assets)
Portfolio):
Portfolio):
Debt
Apply Merton model to link market
Apply Merton model to link market
factors and default probability PD.
factors and default probability PD.
Merton model (structural):
Exposures (market risk) and credit
Exposures (market risk) and credit
compute default probability
quality (PD corresponds to area
quality (PD corresponds to area
Asset value distribution
below liability level) are affected
below liability level) are affected
before and after shock
simultaneously by shock of market
simultaneously by shock of market
Asset value
parameters.
parameters.
Illiquid case (e.g. Retail Portfolio):
Illiquid case (e.g. Retail Portfolio):
Work through the Balance Sheet to
Work through the Balance Sheet to
understand impact of risk factor
understand impact of risk factor
Liabilities
shocks on P&L, capital etc.
shocks on P&L, capital etc.
t
Default probability

68. Credit Distress prediction horizon (in months) of
Z-score and “KMV” EDF Models
(Possible “Alert” Cases)
Company Z-score EDF
BRWY 11 7
FOHD > 10 > 10
GRPS 12 12
IPCC 6 6
LKNS 37 10
LMGS 14 19
PCIS 29 17
SHOW 9 11
VDHS 7 7

69. Q&A: Implementation Challenges
Alternatives
3. Lack of real-time MIS & expertise
• Start at sub-organization or initial group of
customers, e.g., consumers
• Training & continuing education
• Learn from others’ experiences
• etc

70. Other Considerations
• It is also important to conduct stress tests based on
assumptions that are less complicated for management
buy-in.
• Also, the stress test results ideally should yield, other
than the “loss amount”, information about say, the key
risk drivers or factors that have a high explanatory
power, i.e., they can explain the loss of the worst-case
scenario up to a high degree – see example
• Stress Tests also yield different loss amounts based on
degree of severity

71. Stress Test Scenarios:
Accounting for explanatory power
of different risk drivers
Reports Risk factors Relative Loss of Portfolio Explanatory Power
changes Value
Report 1 DJIA -13% 206% 74%
DJIA -13%
Report 2 264% 94%
FTSE100 -8%
DJIA -13%
Report 3 271% 97%
FTSE100 -8%
NIK225 -5%
1. Leaving all other risk factors unchanged, a move of -13% in the DJIA would
lead to a relative loss of 206%
2. Leaving all other risk factors unchanged, a simultaneous move of -13% in the
DJIA and of -8% in the FTSE100 would lead to a relative loss of 264%
3. etc.

72. Table Loss on the cash flow in 3 different scenarios
Scenario THB IDR JPY Loss
Minor crisis -15% -15% 0% USD 58 mil
Midsize crisis -30% -30% 0% USD 116.3 mil
Major crisis -50% -50% 0% USD 183.9 mil
The results provide a considerably more drastic picture of the
loss potential of the given transaction than the VAR measure,
calculated to be USD 16 mil, by MC simulation.

73. DEPTH & BREADTH OF
STRESS TEST STUDY
Stress Test methods are hierarchical
- Sensitivity Analysis: broader in
coverage
- Scenario Analysis: more focused on
specifics
- “Full-Blown” Stress Test: the ultimate
in coincident extreme conditions
leading to:
“THE PERFECT
STORM”

74. STRESS TEST METHODS
(A) Hierarchy & Overview
Full-Blown
Depth Stress
Testing
Scenario
Analysis
Sensitivity
Analysis
Breadth

75. Overview of Stress Test methods
• Sensitivity Analysis: Shock risk factor by large no of “standard
deviations”
– Typically VAR-based
– use EVT to analyze 99.9...% quantile
– consistent with daily risk management
– takes into account probability of event
• Scenario based: Define scenarios that could hurt
– include “the unexpected” (e.g. merger risk)
– consider highly correlated crashes
– forward looking
– Other “what-if” scenarios
• Full-Blown Stress Test: The perfect storm
- subject scenarios above to multitude and coincidence of extreme
events and pressures

76. Sensitivity Analysis
a) Using EVT
b) N X Std. Deviation
c) Tweaking correlations & volatilities
Extreme Value Theory (EVT) Model
VAR 98.70%
90
98.7% confidence
80 series 1 7 mil
70
series 2 10 mil
60
Frequency
50
Series1
40
Series2
30
20
10
0
-15 -10 -5 -10 0
Loss

77. 1 c1 c2
1 c3
1 c1 + 15% c2 + 15%
1 c3 + 15%

78. Portfolio: 3 assets
$10 mil portfolio:
1) 500 Citicorp shares with nominal
value of $5 mil
2) 150 Euroyen Dec futures with
nominal value of $3 mil
3) 50 QQQ (NASDAQ ETF) shares with
nominal value of $2 mil

79. r1, r2, r3 = 0
σ1 = 15%
σ2 = 13%
σ3 = 20%
ρ12 = 0.5
ρ13 = 0.3
ρ23 = 0.4
1 ρ12 ρ13 = 1 0.5 0.3
1 ρ23 = 1 0.4 =M
1 = 1

80. VAR
Var (N std dev) = 1 0.5 0.3 15%*N*5
√(15%*N*5 13%*N*3 20%*N*2) * 1 0.4 13%*N*3
1 20%*N*2
= VAR (2 std deviation) = √ (5.88)
= 2.42
Or With a 95% confidence interval, the value of the portfolio will
not decline by $ 2.42 mil
If N = 1.65, then it’s 90% confidence interval

81. Scenario-based
Event or Scenario Risk Analysis
Historical Events User-Defined Events
Shock Names S&P NASDAQ FTSE NIKKEI JPY GBP
Black Monday -20.5% -13.4% -10.8% -2.4% 0.0% -0.5%
Gulf War -10.4% -13.1% -7.9% -16.8% -2.1% -3.4%
Euro Crisis -2.0% -0.6% 7.8% -3.2% -4.5% 8.1%
Mexican Peso Crisis 1.9% 4.3% -3.4% -8.4% -0.4% -2.2%
Asian Crisis -6.9% -7.2% -2.6% -1.9% -0.2% -1.8%
Russian Crisis -12.9% -23.5% -16.8% -13.5% -17.6% -5.5%
Tech-Wreck -11.2% -33.1% -8.3% 2.4% -2.2% 0.3%
Sept. 11 -11.7% -16.1% -11.9% -6.3% 3.7% -0.1%

82. The Asian Contagion
Liquidity
Trading Market Trading
Risk
Risk Credit Risk
Market
Asian Credit
Liquidity
Currencies Spreads
Dried
Declined Widened
Up
Enterprise Declining
Equities
Liquidity Credit
Fell
Dried Up Quality
Interest Financial
Defaults
Rates System
Increased
Unstable Under Stress

83. Annual Correlation & Volatility
EXAMPLE:
(%) matrix
STRESS TEST ASIAN CRISIS
•Pre-Thai Baht crash (July 1997)
Volatility 10 23 15 14 16 8 11
•Post-Thai (impact on other
US SG HK ID TH MY JP
markets)
**GRANULARITY OF DATA
US 1 0.6 0.7 0.56 0.61 0.34 0.41
6-month
SG 0.6 1 0.72 .. .. .. ..
correlation
& volatility
HK 0.7 0.72 1 .. .. .. ..
matrix
ID 0.56 1 .. .. ..
3-month
TH 0.61 1 .. ..
correlation
MY 0.34 1 ..
& volatility
JP 0.41 1
matrix
“PERFECT STORM” Environment :
Introduce China factor – Yuan devalued in the midst of crisis!
June 1996 June 1997 June 1998

84. Examples
• From US Markets
• Linking Market & Credit Risk
• Balance Sheet Stress Testing

85. THE US MARKET
• Scenario 1
– When US Stocks are all Down
• Scenario 2
– Using historical worst-case P-E,
P-B or P-S scenarios3

86. US Market Examples: Scenario 1
When NASDAQ stocks are all down

87. US Markets: Scenario 2 Using historical
worst-case P-E, P-B or P-S scenarios

88. Case Study Discussion
• The Sub-Prime Contagion

89. Subprime Contagion:
End-to-End Examination
Ratings agencies
Loan Origination Mortgage Lenders Investment Banks Investors
& insurers
Securitization Process Map
Subprime & Portfolio ALM info Rate the tranches
Securitize pools of Seeking high-yield
prime borrowers based on portfolio
loan receivables “investment grade”
info & facility
into tranches asset classes
Loss rates (DR)
No Income No
Doc Insurers provide
Obtain portfolio Spectrum from
Pooling of Loan guarantees based
info hedge funds,
Exotic on their AAA mutual funds &
receivables
mortgages: “reassurance”
Hire ratings pension funds, etc.
ARMS & HEL agencies &
Basel 1 or 2 status monolines
Sales Incentives
Risk Exposures?
In theory, optimal risk transfer thro’ originate & distribute model

90. EXAMPLES
CONCLUDING REMARKS
• Categories of Stress Test
• Operational Risk Illustration

91. Risks Are Integrated/Correlated!
Source: Global Risks 2007. World Economic Forum Report

92. Liquidity Risk Monitoring
The actual value of “Asset Turnover Ratio” is
39 and pointed out by black needle. The
The value 10 and 20 are two
actual value is calculated on average of all
threshold value of Interest
subsidiary in year 2004.
expense ratio.

93. Impact from OpRisk Event Types on Liquidity
Risk manifestation - Example
7 Categories of Operational Losses
Practices &
age to
Disruption
orkplace
Delivery &
Execution,
e
ploym
Practices
Business
Products
Business
External
Physical
Internal
Failures
Process
System
Clients,
Assets
safety
Fraud
Fraud
t
Mgm
Dam
and
Em
ad
W
nt
Corporate Finance
8 Business Lines
Trading & Sales
Standardized
Payment & Settlement
Approach for 6
business lines
Agency Services
Asset Management
Retail Brokerage
AMA Approach
Commercial Banking
for 2
businesses
Retail Banking
Inputs Methodologies Outputs
Regulatory
Statistical Distributions
Statistical Models
Capital
External Operational Loss Data
Risk and Control Self-Assessment Management
Self-Assessments
Workshops Tools
Internal Operational Loss Data
Reduction in
Scenario Analysis
Scenarios Operational
Losses

94. Interplay b/w Oprisk Events & Liquidity
Risk Manifestation: Sources
It can be caused by the breakdown or
inadequacies in:
- Model use / model risk
- Valuation/pricing
- Fraud, e.g. losses due to rogue trading
- Reputation
- External factors
- Others – people/business
- Etc.

95. Where Liquidity Risk could Manifest in the Context of the
Building Blocks of ORM Framework
Event Flow through income Primary focus of capital
Frequency statement allocation for operational risk
Cause of
Risk EXPECTED UNEXPECTED
LOSSES LOSSES
People
Process Liquidity
risk zone
Systems High-Freq
Low-Freq
Low
External High Impact
Impact Catastrophic
Risk & Control Assessment Impact
Severity
Loss Event Management
Risk Measures & Reporting
Risk
Management
Process Risk Bankwide
Approach
Mapping Insurance
Program
Business Continuity Program
Risk Governance

96. Completeness of Stress Tests
(environment, duration/stages,
scenario analysis including
severity, etc.)
• Documentation (thought processes)
• Scenario Analysis
• Liquidity factors/ratio calculations
• Balance Sheet stress test
• Etc.

97. Evidence/Documentation
• Model assumptions
• Identification of risk drivers/factors
• Data inputs/transformation/outputs:
macroeconomic, micro-, demand-
supply/volumetric analyses
• Liquidity portfolio management & diversification
• Risk Assessment/Monitoring
• Remedial activities (next slide)

98. Risk Mitigation Strategies
• Risk management strategies need to be determined and
maximized.
RETAIN
AVOID TRANSFER
REDUCE EXPLOIT
• Divest • Accept
• Disperse • Insure • Allocate
• Prohibit • Re-price
• Control • Reinsure • Diversify
• Stop • Self insure
• Hedge • Expand
• Target • Offset
• Securitize • Create
• Screen • Plan
• Share • Redesign
• Eliminate • Outsource • Reorganize
• Indemnify • Price
• Arbitrage
• Negotiate
• Influence

99. Example of calculation of the liquidity ratio
and the observation ratios
Capital charges
Residual maturities of
Calculation of the liquidity ratio and the
due on demand over 1 month over 3 months over 6 months
observation ratios
up to one month up to 3 months up to 6 months up to 12 months
Maturity band 1 Maturity band 2 Maturity band 3 Maturity band 4
A. Total liquid assets 200 100 80 40
B. Total liabilities 160 180 60 80
C.Mismatches (A - B) + 40 - 80 + 20 - 40
D. Positive mismatches (A > B)* + 40 - + 20 -
E. Mismatches adjusted
140 60
(A. plus positive mismatches D. of the - 80
(100 + 40) (40 + 20)
preceding maturity band)
F. Liquidity ratio (A / B)
1,25 - - -
(at least equal to 1.0)
H. Observation ratios (E / B)
( No minimum levels for the observation - 0,78 1,33 0,75
ratios)
*Severity of mismatch – scenario analysis & stress tests