Abstract #302291

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JSM 2003 Abstract #302291
Activity Number: 241
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Business & Economics Statistics Section
Abstract - #302291
Title: Multiple Testing in Fair Lending Monitoring
Author(s): Carla H. Inclan*+ and Anne Kerttula
Companies: Ernest & Young and Ernst & Young, LLP
Address: Quantitative Economics and Statistics, Washington, DC, 20036,
Keywords: fair lending ; multiple testing
Abstract:

Statistical methods can be used to test for patterns in loan underwriting or pricing that may raise fair lending concerns. Lenders may conduct testing by divisions, branches, or even by individual loan officers. Additionally, a critical element in fair lending testing is that comparisons be made across similarly situated applicants in order to yield meaningful comparisons. This can be achieved by segmentation of applicants into similar groups. Segmentation typically leads to multiple tests per unit of analysis, and requires adjustments when obtaining critical values for the tests. This paper explores alternative ways of addressing this issue. Using simulated data, we attempt to quantify the effect of correlation among multiple tests on the adjustments to the critical values, and on the test findings. An alternative way to compare similarly situated borrowers uses regression models to simultaneously control for the applicant and transaction characteristics that affect the underwriting or pricing outcomes, thus reducing the need for segmentation and mitigating issues arising from multiple testing.

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