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Detecting Discrimination in Fair Lending Analysis Using Proxies

The use of proxy methods in fair lending analysis – and in particular fair lending enforcement actions – has drawn much attention. In an article entitled “BISG Methodology and Its Impact on Regression Analysis,” we studied the use of proxy methodologies as applied in regression analysis designed to test for potential discriminatory practices.

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BISG Matching and Its Impact on Regression Analysis for Fair Lending

In determining whether discrimination occurs based on race or ethnicity, particularly with regard to fair lending, it is obviously important to know the race or ethnicity of the applicant(s). However, for some non-mortgage products lenders are not allowed to collect these data. Therefore, one must use proxies for race and ethnicity.

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Essential Elements of Profitable Loan Pricing

  In a previous article, we discussed the fair lending benefits of having a profitable and risk-based loan pricing strategy. In this post, we dissect the specific components that comprise an effective approach. 

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FDIC Provides Highlights from April 2016 Community Banking Conference

From the FDIC:

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Statistics of Z Tests Versus T Tests in Fair Lending Analysis

Understanding the difference between Z statistics and T statistics for fair lending analysis can be frustrating, even more so when it comes to determining which test to use. Let’s take a more detailed look into this world of statistics.

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Proper Loan Pricing Structure is Profitable & Fair Lending Friendly

The first rule of policy analysis is that policies have both intended and unintended consequences. This is no more true than in the commercial banking space, as good intentions can sometimes produce negative results. In this article, we examine the importance of lenders having a well-designed and profitable loan pricing strategy as part of fair […]

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Z Statistics Versus T Statistics in Fair Lending Analysis

Regression analysis for fair lending with respect to underwriting analyses generally use what are known as “discrete choice” models.  Such functional forms are used in which the measurement (dependent) variable is categorical or a limited outcome.  In an underwriting evaluation for fair lending analysis, for example, what is measured is either approval or denial.  A common […]

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Understanding Fair Lending Regression Tables in One Easy Lesson

In studying your bank’s loan data, how can you determine the relationships among various factors in your lending policies, customer base, pricing, and more? Through the use of regression modeling, an important tool in statistical analysis.

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A Simple Explanation of Using “Proxies” In a Fair Lending Review

  Ever wonder how one can conduct a fair lending review of your bank’s consumer lending products without having government monitoring information like race, gender, and ethnicity available? Enter the proxy.

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Fair Lending Risk in Consumer Lending for Community Banks

Consumer loans pose a great deal of risk for financial institutions. In this post, we’ll examine that risk to lenders.

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