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Peter O. Davis Partner, Ernst & Young LLP Director of Credit Risk Services peter.davis@ey.com. Current State of Credit Risk Measurement . Symposium on Enterprise Wide Risk Management Chicago, April 26, 2004. Agenda. Continued Movement Toward Credit Quantification Regulatory Push

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peter o davis partner ernst young llp director of credit risk services peter davis@ey com
Peter O. Davis

Partner, Ernst & Young LLP

Director of Credit Risk Services

peter.davis@ey.com

Current State of Credit Risk Measurement

Symposium on Enterprise Wide Risk Management

Chicago, April 26, 2004

agenda
Agenda
  • Continued Movement Toward Credit Quantification
  • Regulatory Push
  • Avoiding Unintended Consequences
    • Incidence vs. Dollar Based Default Rates
continued movement towards credit quantification
Continued Movement Towards Credit Quantification
  • Extending credit inherently a judgment-based decision
  • Continued movement toward the reliance on credit models to support credit extension and portfolio management
  • Driven in part by continued advances in credit risk modeling
    • More mature models
    • Greater computing power
    • Development of credit loss databases
    • More credit products providing market information
  • Driven in part by demand for greater transparency
    • Large defaults by fallen angels triggered increased focus by investors
    • Demand for greater information by senior management, Board, shareholders, rating agencies, regulators
    • Demand for consistent measurement across products
regulatory push
Regulatory Push
  • For commercial banks, and (more recently) investment banks, regulators have created incentives for institutions to enhance their internal credit models
  • For those meeting advanced standards, by year-end 2006, under “Basel II” regulators will rely upon institutions’ internal credit models for setting regulatory capital
    • Probability of default models
    • Loss given default models
    • Exposure at default models
  • Will result in:
    • Standardization of credit risk measurement terminology and model classification
    • Heavy focus on model accuracy
    • Development of extensive credit performance databases, leading to ongoing innovations in model development
    • Greater transparency in credit risk-taking across institutions
    • Greater liquidity and continued innovation in credit products
avoiding unintended consequences
Avoiding Unintended Consequences
  • As credit models are used more broadly across institutions and more deeply within institutions, continued need to challenge whether:
    • models accuracy capture risks
    • model limitations are understood
    • application of individuals models and the integration of multiple models produce results that are consistent with the intended measurement purpose
  • Example of the application of default models
incidence based vs dollar based defaults illustration
Incidence-based vs. Dollar-based Defaults Illustration
  • Obligor default models measure the probability that an individual borrower will default over a given time horizon – an incidence measure of default risk
  • When measuring expected loss (EL), it is common to use the product of the probability of default (PD), loss given default (LGD) and exposure at default (EAD)
  • This approach implicitly assumes that incidence-based and dollar-based PDs are the same
illustration cont d
Illustration Cont’d
  • Illustration of the impact of dollar-based vs. incidence-based default rates:
  • Assumptions:
    • Three banks with loan portfolio of $100 million
    • Same 10 borrowers and 3 defaults
    • Obligors have same risk rating and incidence based default rates
    • LGD = 100% for defaulted loans
    • 100% closed-end loans
illustration cont d1
Illustration Cont’d
  • Bank A – Loan Size Does Not Differ
    • All the loans are the same size
    • The dollar loss implied by the incidence-based default rate is the same as historical loss
  • Bank B – Large Positions in Loans to Defaulting Obligors
    • The dollar loss implied by the incidence-based default rate is based on the number of defaults and average value of the loans
    • The size discrepancy of the loans are so large the average value hides more than it reveals
  • Bank C –Small Positions in Loans to Defaulting Obligors
    • The dollar loss is far lower than the incidence-based default rates imply
loss severity adjustment
Loss Severity Adjustment
  • Loss Severity Adjustment is defined as the ratio of the average value of defaults to the average current balance of the portfolio
  • For Bank B and C the use of incidence-based PD may not reflect the trends of the portfolio
    • For such instances a Loss Severity Adjustment may be applied to the losses implied by the incidence-based default rates
    • After the adjustment, the dollar losses reflect historical figures and the trend in the portfolio towards higher or lower dollar-based default probabilities
  • Loss Severity Adjustment restores information lost in the averages by reconciling the incidence-based default rates with the banks loss in dollars