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Statistical Analysis and Modeling for Fair Lending and Compliance: The OCC’s Perspective

In: Household Credit Usage

Author

Listed:
  • Mark Pocock
  • Irene Fang
  • Jason Dietrich

Abstract

In 1989, the Home Mortgage Disclosure Act (HMDA) was modified to require lenders to gather and report data on applicants’ race and gender. This data created opportunities for banking regulators to incorporate statistical techniques into analyses of disparate treatment during fair lending exams. Statistics provide an objective and efficient approach to identifying patterns in large volumes of data. Results from these analyses can be used to draw conclusions about disparate treatment as well as to identify areas of higher fair lending risk needing more thorough review. Overall, statistics have been an important complement to traditional manual file reviews during fair lending exams.

Suggested Citation

  • Mark Pocock & Irene Fang & Jason Dietrich, 2007. "Statistical Analysis and Modeling for Fair Lending and Compliance: The OCC’s Perspective," Palgrave Macmillan Books, in: Sumit Agarwal & Brent W. Ambrose (ed.), Household Credit Usage, chapter 0, pages 269-284, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-60891-7_16
    DOI: 10.1057/9780230608917_16
    as

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