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Lawrence Mielnicki, Ph.D. FleetBoston Financial Director, Retail Credit Risk Analysis

Challenges In Validation: Taking the Study Findings Forward A Retail Perspective. Lawrence Mielnicki, Ph.D. FleetBoston Financial Director, Retail Credit Risk Analysis. Risk Ratings May Be Less Problematic For Retail Lending Than For Commercial Lending.

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Lawrence Mielnicki, Ph.D. FleetBoston Financial Director, Retail Credit Risk Analysis

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  1. Challenges In Validation: Taking the Study Findings Forward A Retail Perspective Lawrence Mielnicki, Ph.D. FleetBoston Financial Director, Retail Credit Risk Analysis

  2. Risk Ratings May Be Less Problematic For Retail Lending Than For Commercial Lending • 23 of 26 respondents use statistical models in some aspect of their decisioning/account management process • Portfolios are large with sufficient defaults for validation purposes • Robust internal and external data is available • Default definition not consistent but this is not a roadblock

  3. Retail Model Validation Is Already a Best Practice Activity -- At least in the U.S. • OCC Bulletin 2000-16 sets standards for the development, use, and validation of statistical models • External vendor models can be validated on bank data, tracked, and re-validated at appropriate intervals • Internally developed models must pass certain tests that go beyond the use of statistical measures such as GINI and K-S • Data integrity may be an issue especially for external vendor supplied models

  4. From Scorecards to Risk Ratings • The preponderance of statistical risk measurement tools used in retail lending are in the form of “scorecards” • Scorecards are just a convenient way to implement statistical models • Underlying most scorecards is a probability something bad will either happen or not • The probability may be default but most likely something else like some state of delinquency • This prediction needs to be converted to a probability of default

  5. Do We Need A Common Risk Rating Scheme Across All Asset Classes? • Matter of personal preference • Pros • Places all credit risk on an equal footing for reporting • ….. • Cons • There are many more opportunities for risk segmentation in retail portfolios • ….. • Based on the QIS 3, this is not a requirement for Basle II AIRB

  6. Challenges Going Forward • Banks need to cleanse their processes of “black box” models • external vendors will need the message that “black box” models no longer sufficient for regulatory purposes • Scorecard development in the future should recognize the multiple uses of the underlying models • stoplight decisions (red, amber, green) are only one application of the tools • Stress testing of inputs • Guidance from the supervisors regarding the level of regulatory validation for Basle AIRB purposes would be helpful • is the OCC 2000-16 approach taken (validate the internal validation process) or • will the supervisors look to validate each model independently?

  7. Questions and Answers

  8. Challenges In Validation: Taking the Study Findings Forward A Retail Perspective Lawrence Mielnicki, Ph.D. FleetBoston Financial Director, Retail Credit Risk Analysis

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