Transcript Leading Edge Perspectives on Credit Strategies

Measuring and Managing Credit Risk – Trends
and Developments
Dave Wright
Director
Moody’s KMV
[email protected]
Agenda
1. The Trend Towards Superior credit
performance
2. Why manage credit risk?
3. How to manage Credit Risk?
11
Introduction
The Trend Towards Superior Credit Portfolio Performance: 4 Stages
Stage 4
Stage 3
Stage 2
Stage 1
Data &
Infrastructure
4
Counterparty
Risk
Management
Portfolio
Risk
Measurement
Active
Portfolio
Management
- Reduce
concentrations
- Improve returns on
risk & capital
- Measure portfolio risk
- Calculate & allocate economic capital
- Optimize credit limits
- Implement & validate internal rating models
- Measure PDs, LGDs & EADs
- Take early action for high-risk exposures
- Collect, organize & store customer data
- Implement internal rating framework
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The Trend Towards Superior Credit Portfolio Performance: 4 Stages
Stage 4
Stage 3
Stage 2
Stage 1
Data &
Infrastructure
5
Counterparty
Risk
Management
Portfolio
Risk
Measurement
Active
Portfolio
Management
- Reduce
concentrations
- Improve returns on
risk & capital
- Measure portfolio risk
- Calculate & allocate economic capital
- Optimize credit limits
- Implement & validate internal rating models
- Measure PDs, LGDs & EADs
- Take early action for high-risk exposures
- Collect, organize & store customer data
- Implement internal rating framework
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Credit Risky Assets

Treasury assets
 Credit insurance
 Receivables
 Lending portfolios
 Investment portfolio
 Financial Institutions – reinsurance
6
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22
Why mange credit risk?
Is credit risk management………
For some, managing credit risk is a defensive skill - trying to stop bad
things happening, or reduce the impact of bad things.
However its not quite that simple………………..
8
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and that is because…..….
The major concern in credit risk is seldom from large
numbers of small – even risky – borrowers but from
 excellent risks that collapse without much warning
 inadvertent concentrations of creditors that turn out to
be highly correlated…
….of which more later
9
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Investment Grade Rating Prior To Default 2002
10
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Investment Grade Rating Prior To Default 2003-2006
11
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What do we mean by managing the credit
portfolio?
Understanding the component parts of the portfolio and how they
interact together
This then enables us to measure the risk in the portfolio – the
commonly accepted way of doing this is through measuring Economic
Capital.
Economic capital loss the Language if risk in the portfolio
 Once we can measure Economic capital we can also measure risk
and return of the credit assets – either at the institution, business line
or individual asset level
12
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Why manage the credit portfolio - Benefits
 Reduces the potential for volatility in profits
 Better external communication
 Better customer profitability analysis
 Improve strategic planning – better more cohesive
 Improved risk based performance measurement
 Enables concentration management and industry exposure capacity
creation
Opens opportunities for new business lines / profit generating
activity (e.g where no appetite currently exists)
13
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33
How manage Credit Risk?
15
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Counterparty Credit Risk Rating
Data Capture
Data Infrastructure
Quantitative
Market
data
Qualitative
Other
data
Ratings and Models
Output
Credit
Review
Risk Rating Framework
Portfolio
Mgmt.
Lending: Treasury: Investment
Reinsurance: Credit Insurance
Development of Sophisticated Credit Risk Models
• Internal models
• Data drives models
• Data sources?
• External models
• Statistical
• Expert
• Enhanced risk
• management
• Ratings
CONSISTENT PROCESS ACROSS THE ORGANISATION
16
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Market Measures Have Proven
Months of Early
FIBERMto
ARKProvide
INC
Warning 1 Year EDF
Moody's Rating
S&P Rating
1-year EDF
20 Ca
C
CaaCC
15 CCC
10
7
B
5
B
Moody’s Rating
S&P’s Rating
2
BB
Ba
1
• Fibermark is based in Vermont, USA and has facilities in both USA and Europe.
Fibermark produces specialty paper and nonwoven materials that are used, for
example, in vacuum cleaner bags, insulating panels, and specialty tapes.
.50BaaBBB
• After reporting a loss of $7.69 per share at the end of March 2004, the company
filed for Chapter 11 protection.
.15
• The company failed to recover from declining income margins that started in 2001
and was not able to take advantage of a July 2003 reorganization that lead to a
reduction of its workforce by 9%.
A A
.20
.10
AA
Aa
.05
AAA
.02Aaa
08/99
17
01/00
07/00
01/01
07/01
01/02
07/02
01/03
07/03
01/04
07/04
Credit KMV
Monitor
COMPANY. ALL RIGHTS RESERVED.
COPYRIGHTSource:
© 2005 MOODY’S
Fibermark Inc. : EDF vs. Spread to Treasury
1-year EDF
• Fibermark’s EDF anticipates the change in
the cash market by 6-months
Fibermark’s
10.750% 04/15/11
spread to Treasury
Source: CreditEdge
18
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Differentiating Credit Models point-in-Time PDs from Traditional
Ratings
Models of Credit Quality
Traditional Ratings
Quantitative components
Qualitative Method
Qualitative Output
EDF = 0.02% (An actual
probability of default)
AAA = “Obligor’s capacity to meet
its financial commitment on the obligation is
extremely strong.”
Absolute (Cardinal)
Relative (Ordinal)
Precise and continuous, providing full
granularity (high resolution)
Distinct risk buckets without specifying or
targeting a specific default rate
Specific time horizon
No specific time horizon (“long term”)
No credit cycle view
Supposed to be through the cycle
Dynamic, updated daily or monthly
Stable (low ratings volatility)
Reflects issuer’s default probability
(PD), and not issue-specific LGD
Opinion on Expected Loss – combines the
effect of PD and LGD (Loss Given Default)b
Quantitative Output
19
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What is Economic Capital?
The aggregate amount of equity capital required as a cushion for
Unexpected Losses due to credit risks, given the institution’s target
financial strength

 Risk is measured objectively in terms of economic reality using
modeling techniques
 Provides a common yardstick to measure, evaluate, manage, and
price a wide range of risks
 Required economic capital has become the language of risk at
leading Financial Institutions
 An accurate, granular credit portfolio model is essential for making
good credit origination, pricing, and portfolio decisions
20
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Economic Capital Drivers
Portfolio Credit
Risk
Correlation in
Exposure Values
Exposure
Credit Risk
Default Probability
Default and Asset
Correlation
LGD
Maturity
EaD
Amount Held
• Individual Exposure Risk Drivers are PD, LGD, EAD and Maturity
Country
Industry
Size
• Portfolio Risk Drivers are Exposure Concentration and Size Exposure Correlation
•The degree to which a customer is sensitive to the business cycle and will change
credit quality together with other customers
•Key determinants - industry, geography and size
•Small firms tend to have less systematic risk and more firm specific risk
21
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What is Credit Correlation?
Financial Institutions don’t fail from the occasional default, they fail
when simultaneous defaults occur
Correlation is the degree to which a customer is sensitive to the
business cycle
Key determinants of correlation include the industry, geography and
size.
Greater correlation within a portfolio leads to higher economic capital
requirements
22
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Correlation = 0.95
5
4
3
2
1
0
-6
-4
-2
0
2
4
6
-1
-2
-3
-4
-5
Company B
23
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Importance of Concentration and Portfolio Credit Correlation
Ignoring single-name, country and industry concentration and
specific measures of systematic risk will not produce the
correct signals to manage the portfolio well
Regulatory capital does not measure the degree to which
concentration and portfolio credit correlation affect
portfolio credit risk and required economic capital
Portfolio credit correlation is not intuitive – there are too many
moving parts that affect the measure
For example even in a simple case of hedging large or
deteriorating credit exposures, without a portfolio model it
is impossible to know the right amount of hedging
24
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Expected Loss, Unexpected Loss, and Tail Risk
2.00%
Tail Risk measures the
Actual Portfolio Loss
1.80%
1.60%
likelihood of extreme losses
Portfolio 1
1.40%
1.20%
1.00%
0.80%
0.60%
Expected
Loss is the
Portfolio 2
average loss
Unexpected
Loss measures
0.40%
the variability
around the
Expected Loss
0.20%
0.00%
Year
25
(one standard
deviation)
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Portfolio Loss Distribution
2.00%
Actual Portfolio Loss
1.80%
1.60%
1.40%
1.20%
Most of the time,
the portfolio has
smaller than the
Expected Loss
Rarely, the
portfolio has
very large
losses
Sometimes, the portfolio
has losses equivalent to
the Expected Loss
1.00%
0.80%
0.60%
0.40%
0.20%
0.00%
Year
$0
26
EL
Loss
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Portfolio Required Economic Capital
Probability
• The level of economic capital implies
a probability of capital exhaustion
and an associated debt rating
• Given the portfolio loss distribution
and a target debt rating, the required
economic capital may be inferred
A Aa Aaa
Economic Capital
27
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What is the right way of thinking about portfolio risk? How do we
allocate risk?
Portfolio Capital needs to be allocated to exposures to facilitate decision making.
How should we allocate Portfolio Capital?
A simulation-based portfolio model is the only way to measure Risk Contribution
accurately
Total Stand-alone Risk
Unexpected Loss (UL)
• Systematic risk
- Undiversifiable
28
Diversified away by
the Portfolio
Risk Contribution
(Risk retained
in the Portfolio)
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Credit Monitor ®
EDF
S&P
20
C
15 C
CCC
10
7
5 B
Impact on Portfolio
Risk Contribution
D EU TSC H E TELEKOM
2
BB
1.0
.5
BBB
.20
.15 A
.10
.05
AA
.02 AAA
08/97 01/98
07/98
01/99
07/99
01/00
bps
07/00
01/01
07/01
01/02
07/02
500
400
300
200
100
0
Mar00
Mar 00
29
Sep 00
Sep 00
Mar01
Mar 01
Sep 01
Sep 01
Ju l02
Jul 02
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Credit Monitor ®
EDF
S&P
20
C
15 C
CCC
10
7
5
B
D EU T SC H E T ELEKOM
2
BB
Impact on
Return/Risk Ratio
1.0
.5
BBB
.20
.15 A
.10
.05
AA
.02 AAA
08/97 01/98
07/98
01/99
07/99
01/00
07/00
01/01
07/01
01/02
07/02
17.00
15.00
13.00
11.00
9.00
7.00
5.00
3.00
1.00
-1.00
30
Mar 00
Mar 00
Sep 00
Sep 00
Mar 01
Mar 01
Sep 01
Sep 01
02
Jul 02
Jul 02
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Mispricing (Monte Carlo) to Portfolio
using Expected Spread & Risk Contribution
Mispricing: <= -0.002
Mispricing: -0.002 .. -0.001
Mispricing: -0.001 .. 0.001
Mispricing: 0.001 .. 0.020
Mispricing: > 0.020
0.06500
0.06000
0.05500
0.05000
0.04500
0.04000
0.03500
0.03000
0.02500
0.02000
0.01500
0.01000
0.00500
0.00000
-0.00500
-0.01000
-0.01500
0.04000
0.03500
0.03000
0.02500
0.02000
0.01500
0.01000
0.00500
0.00000
-0.02000
Risk Contribution
31
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Major Trend Toward Credit Portfolio Management

32
Actively managing the credit portfolio began among a few leading
edge institutions in the late 1990s, mainly to:

Reduce concentrations and unexpected losses

Increase capital velocity

Improve returns on risk and capital

Especially since 2003, there has been an acceleration in adoption and
use of active credit portfolio management among other institutions

What convinced senior management at these institutions to pursue
active credit portfolio management?

Large credit losses in 2000 – 2002

Better liquidity in credit instruments, including CDS and CDOs

Success stories among their leading-edge peers in reducing
concentrations and improving returns on risk and economic capital
COPYRIGHT © 2005 MOODY’S KMV COMPANY. ALL RIGHTS RESERVED.
Measuring and Managing Credit Risk – Trends
and Developments
Dave Wright
Director
Moody’s KMV
[email protected]