Regression analysis is a powerful tool for assessing fair lending risk and performance. As is the case with any tool, however, it must be understood and used correctly. This includes understanding the limitations which in turn defines what conclusions can be drawn from an analysis.
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When preparing to conduct a fair lending regression analysis, the first step is to determine the loan sample to be analyzed. This is usually accomplished by first selecting a particular loan product on which to focus and a time period.
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As we have discussed in previous posts, fair lending regression analysis has become widely used for evaluation of lender practices. While a comprehensive discussion on the subject is unnecessary certainly beyond a blog post, it is important to understand limitations when such analyses are applied to such a critical issue as fair lending.
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A tension exists between a bank meeting its CRA obligations and compliance with other fair lending laws and regulations. This can sometimes present a bank with conflicting priorities.
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In the second installment of this two-part post, we provide some guidance concerning data for fair lending underwriting analysis in the community bank space.
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In Part 1 of this two-part post, we discuss some issues with conducting fair lending underwriting analysis for community banks: challenges which are becoming more acute with the regulatory emphasis on quantification.
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For decades, banks and those of us who have been involved with regulatory compliance have objected to subjectivity that makes managing compliance matters difficult.
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The CFPB recently released its report on fair lending for 2016. The report covered a number of topics related to fair lending, including a summary of their supervisory and enforcement activities. One area addressed was the use of “testers” which involves sending persons of protected and non-protected class status into branch locations to inquire about […]
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In Part 1 of this post I raised the issue of the new HMDA to be reported March 1, 2018, and how this has the potential to alter the fair lending landscape by increasing the level of risk. Below I detail some of the reasons why I believe this is the case. In a future […]
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The update to HMDA reporting is just around the corner, and while most institutions are probably prepared for the data reporting changes, this does not mean those institutions are actually ready. In this series of articles on HMDA 2018, we’ll discuss the fair lending risk implications of the new data that will be made available […]
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