GAO Asked to Study Alternative Data Credit Decisions

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In a new letter last month, a group of Democratic lawmakers asked the Government Accountability Office (GAO) to take a closer look at the use of alternative data for credit decisions, particularly in the context of mortgage lending.

Alternative data can help lenders expand access to credit and make loans available to more consumers who may not have traditional measures of creditworthiness, but the legislators expressed concern about potential violations of fair lending laws.

What happened

According to the Consumer Financial Protection Bureau (CFPB), roughly 45 million individuals cannot be scored by the nationwide credit reporting agencies (CRAs) using traditional measures of creditworthiness, whether due to a lack of credit history or because of limited or outdated credit history.

To reach these consumers, some CRAs and lenders (both traditional and fintech) incorporate alternative data in their credit scoring algorithms. Information such as rental, utility and insurance payment history, as well as employment verification, educational history and even social media data, can help lenders identify creditworthy potential borrowers whom lenders might otherwise miss, explained Reps. Maxine Waters (D-Calif.), Al Green (D-Texas), Stephen F. Lynch (D-Mass.), Bill Foster (D-Ill.) and Josh Gottheimer (D-N.J.).

According to the letter, only one-third of people between the ages of 18 and 29 have a credit card, but the vast majority of those same millennials have a cellphone. Incorporating telecommunications payment history into the credit scoring process might allow CRAs to score previously unscorable consumers who lack a typical credit history.

However, concerns exist about whether the use of alternative data in lending decisions will affect compliance with fair lending laws, the legislators wrote, such as the Equal Credit Opportunity Act (ECOA) and the Fair Housing Act (FHA).

“[S]coring algorithms that utilize alternative data drawn from a consumer’s social media profile could allow CRAs and lenders to evaluate creditworthiness based on personal characteristics such as the consumer’s race, gender and religion,” the lawmakers said. “Furthermore, while some proponents claim that ‘full file’ reporting of utility payments, for example, would promote access to credit, some experts have expressed concerns that such an approach could unintentionally harm some consumers.”

To help answer some of these questions, the letter asked the GAO for more information about the benefits and drawbacks of alternative data in mortgage lending and the role of the federal government in overseeing the use of alternative data.

The letter presented specific questions for the GAO to study, such as “How have different entities within the credit industry used alternative data to expand access to mortgage credit?” and “What are the potential benefits and risks associated with using financial technology for access to mortgage credit?”

What other options exist for expanding access to mortgage credit, the lawmakers wondered, and how do the benefits and trade-offs of these options compare with the use of alternative data in credit scoring?

The legislators also asked the GAO to consider the potential risks alternative data poses to compliance with the ECOA and FHA, among other fair lending standards, as well as whether regulatory and enforcement agencies are equipped to manage and prepare for oversight of the use of alternative data in mortgage lending.

To read the letter to the GAO, click here.

Why it matters

The use of alternative data for lending decisions has been a hot topic in recent years, with the Federal Reserve Bank of Philadelphia conducting research on its benefits and the CFPB showing its support for alternative data as a means of underwriting consumer loans in a recent blog post.

DISCLAIMER: Because of the generality of this update, the information provided herein may not be applicable in all situations and should not be acted upon without specific legal advice based on particular situations.

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