The following is an article written by Trellance’s Vice President of Lending & Regulatory Analytics, Dan Price. It originally appeared on CUInsight.com.
Fair lending is the new boogey man of the credit union world—not because we don’t want to practice it, but because we’ve now seen what can happen when an institution is accused of not following industry practices. And now with auditors asking more questions than ever about fair lending practices, your credit union better be ready to show that all lending determinations are made fairly. In this article, we’re going to review the basics of fair lending practices and how your credit union can prepare to answer any audit questions.
What Is Fair Lending?
Fair lending is how we ensure borrowers aren’t being denied a loan based on their race, gender, age or other protected aspects. The majority of people want to make their decisions based on approved lending practices—credit history, income—but unfortunately biases, both implicit and explicit, still exist, and can affect how lending decisions are made. Being aware of how these biases can affect lending practices can help your credit union to practice fair lending, as can audits of your lending data. Let’s look at some of the things that you’ll want to avoid while practicing fair lending.
Disparate treatment
Disparate treatment is the first thing people think of when they think of biased lending practices. It is treating potential borrowers differently based on protected class features, such as rejecting a Black borrower or giving a person over the age of 60 a higher interest rate. In a fair lending audit, this may be determined either by establishing a paper trail of statements that show preference to a non-protected class borrower, or by identifying areas of different treatment that cannot be explained by non-discriminatory practices.
Disparate impact
Disparate impact is harder to define, and harder to prevent. It is when a credit union implements a policy that seems neutral but has a disparate impact on persons of a protected class. An example of this would be in requiring higher interest rates on older vehicle makes. In theory, this makes sense and wouldn’t be viewed as negatively effecting a protected class. But when we look at the data, persons of protected class are more likely to have older vehicle makes, and therefore bear the brunt of the higher interest rates. Your credit union should keep an eye on the data to see if any of its policies are having this sort of disparate impact on members.
Redlining
Redlining is a type of disparate treatment when unequal access to credit or terms is provided to a specific area based on the prohibited characteristics (age, race, etc.) that make up the primary population of an area. You might think this is easy to avoid, but your credit union may already be accidentally participating in this, just by prioritizing areas with higher incomes or by having physical branches concentrated in a specific area of the region you serve. Your credit union can identify and begin to rectify these issues by analyzing the zip codes of members and identify any areas that are underrepresented.
Preparing for the auditors
Once you’ve identified any instances of the above conditions, you can begin to prepare for your audit. This might involve rectifying any instances of disparate treatment—such as adjusting interest rates, reaching out to previously rejected borrowers or holding trainings for employees. More than likely, however, it will involve creating documentation for why certain decisions were made, allowing your credit union to show auditors that though something might look like disparate treatment, the decision was actually made based on nonprohibited factors.
Technology can be incredibly beneficial in this process. If your credit union does not currently have the means to analyze borrower data for any potential violations of fair lending practices, now would be a good time to start looking for a technology partner to aid in the process. These providers can utilize your credit union’s data alongside publicly available third-party data to identify any areas of concern, allowing your credit union to quickly rectify any issues or document the reasons for a decision.
At the end of the day, we all want to treat our members fairly. Analyzing your data for discrepancies in treatment can allow your credit union to better serve members in the future while also preparing for audits. Consider partnering with a technology provider to ensure your credit union is doing as much as possible to provide a fair lending environment for all members.
Dan Price is the Vice President of Lending & Regulatory Analytics at Trellance.
