Supervising and Regulating the Use of Credit Repository Data Raphael W. Bostic Federal Reserve Board June 18, 2001.

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Presentation transcript:

Supervising and Regulating the Use of Credit Repository Data Raphael W. Bostic Federal Reserve Board June 18, 2001

Introduction Federal Reserve oversees activities of institutions that use data at credit repositories Our concerns: –Data are accurate –Data are complete

Regulatory Structure What data can be kept –Prohibitions against collecting certain data –Examples: gender, race, marital status

Regulatory Structure What data can be kept How long data can be kept –Allows for opportunity to recover

Regulatory Structure What data can be kept How long data can be kept Who can access the data –Grounds for obtaining personal information –Legitimate business purpose required

Regulatory Structure What data can be kept How long data can be kept Who can access the data How are disputes handled –Critical for addressing accuracy concerns

Institutional Structure Repositories have an incentive to make their data complete –Profit motive: lenders want models that work best

Institutional Structure No regulatory requirement to report credit information A self-enforcement mechanism –Lenders do not have to report –Repositories do not have to provide access

Introduction to Regulation and Supervision Credit scoring and safety and soundness Credit scoring and fair lending enforcement

Credit Scoring and Safety and Soundness Credit scoring uses –Rank applicants according to credit quality –Estimate probability of default for individual applicants at portfolio level

Credit Scoring and Safety and Soundness If the scoring model does not work, an institution can face significant, and unforeseen, risks Could potentially results in institutional stress

Credit Scoring and Safety and Soundness Supervisors must monitor the performance of scoring models - “Model validation” In the US, model validation is done by specialists at the banking regulatory agencies

Credit Scoring and Safety and Soundness Validation objectives –Evaluate model stability, reliability, and accuracy –Conduct benchmark analysis/back-testing

Credit Scoring and Safety and Soundness Validation process –Evaluate sample design –Evaluate model design –Assess internal validation procedures

Credit Scoring and Fair Lending Ensure that discrimination against protected classes does not occur –Overt discrimination –Disparate treatment –Disparate impact

Credit Scoring and Fair Lending In the US, fair lending oversight is conducted by examiners of the banking regulatory agencies

Credit Scoring and Fair Lending Model validation –Was the model developed in accordance with fair lending laws?

Credit Scoring and Supervision and Regulation Final point –“I don’t know” is not an acceptable answer!