Why New Approaches to Credit Risk Measurement and

Management?

Why Now?

2

Structural Increase in Bankruptcy• Increase in probability of default

– High yield default rates: 5.1% (2000), 4.3% (1999, 1.9% (1998). Source: Fitch 3/19/01

– Historical Default Rates: 6.92% (3Q2001), 5.065% (2000), 4.147% (1999), 1998 (1.603%), 1997 (1.252%), 10.273% (1991), 10.14% (1990). Source: Altman

• Increase in Loss Given Default (LGD)– First half of 2001 defaulted telecom junk bonds recovered

average 12 cents per $1 ($0.25 in 1999-2000)

• Only 9 AAA Firms in US: Merck, Bristol-Myers, Squibb, GE, Exxon Mobil, Berkshire Hathaway, AIG, J&J, Pfizer, UPS. Late 70s: 58 firms. Early 90s: 22 firms.

3

Disintermediation

• Direct Access to Credit Markets– 20,000 US companies have access to US

commercial paper market.– Junk Bonds, Private Placements.

• “Winner’s Curse” – Banks make loans to borrowers without access to credit markets.

4

More Competitive Margins

• Worsening of the risk-return tradeoff– Interest Margins (Spreads) have declined

• Ex: Secondary Loan Market: Largest mutual funds investing in bank loans (Eaton Vance Prime Rate Reserves, Van Kampen Prime Rate Income, Franklin Floating Rate, MSDW Prime Income Trust): 5-year average returns 5.45% and 6/30/00-6/30/01 returns of only 2.67%

– Average Quality of Loans have deteriorated• The loan mutual funds have written down loan value

5

The Growth of Off-Balance Sheet Derivatives

• Total on-balance sheet assets for all US banks = $5 trillion (Dec. 2000) and for all Euro banks = $13 trillion.

• Value of non-government debt & bond markets worldwide = $12 trillion.

• Global Derivatives Markets > $84 trillion.• All derivatives have credit exposure.• Credit Derivatives.

6

Declining and Volatile Values of Collateral

• Worldwide deflation in real asset prices.– Ex: Japan and Switzerland– Lending based on intangibles – ex. Enron.

7

Technology

• Computer Information Technology– Models use Monte Carlo Simulations that are

computationally intensive

• Databases– Commercial Databases such as Loan Pricing

Corporation– ISDA/IIF Survey: internal databases exist to

measure credit risk on commercial, retail, mortgage loans. Not emerging market debt.

8

BIS Risk-Based Capital Requirements

• BIS I: Introduced risk-based capital using 8% “one size fits all” capital charge.

• Market Risk Amendment: Allowed internal models to measure VAR for tradable instruments & portfolio correlations – the “1 bad day in 100” standard.

• Proposed New Capital Accord BIS II – Links capital charges to external credit ratings or internal model of credit risk. To be implemented in 2005.

9

Appendix 1.1A Brief Overview of Key VAR Concepts

• Banks hold capital as a cushion against losses. What is the acceptable level of risk?

• Losses = change in the asset’s value over a fixed credit horizon period (1 year) due to credit events.

• Figure 1.1- normal loss distribution. Figure 1.2 – skewed loss distribution. Mean of distribution = expected losses (reserves).

• Unexpected Losses (UL) = %tile VAR. Losses exceed UL with probability = %.

• Definition of credit event:– Default Mode: only default– Mark-to-market: all credit upgrades, downgrades & default.

FIGURE 1.1

ExpectedLosses(EL)

EL EL

ConfidenceInterval

UnexpectedLosses, VAR

(UL)

Loss Distribution

Probability%

99.5th Percentile(Maximum) Value

0.5%

Figure 1.1 Normal loss distribution.

11

ExpectedLosses(EL)

UnexpectedLosses, VAR

(UL)

Loss Distribution

Probability%

Figure 1.2 Skewed loss distribution.