Study: Racial Bias Skewed Small Business Relief Lending

By Tadi Abedje Published: October 13, 2021

Study: Racial Bias Skewed Small Business Relief Lending

A notice of closure is posted at The Great Frame Up in Grosse Pointe Woods, Mich. The government is closing in on the $349 billion lending limit on its Paycheck Protection Program that is sending relief money to the nation’s small businesses. The Small Business Administration says that it has approved more than 1.6 million loans worth more than $339 billion. The program will likely reach its ceiling Thursday, April 16. (AP Photo/Paul Sancya, File)

In Summary

There is new research which states Black business owners were more likely to receive Paycheck Protection Program loans from online lenders than banks.

There is new research occurring in smaller banks that highlighted human bias.

According to a research paper which looked into the $806 billion Paycheck Protection Program released on Oct. 11, Black-owned businesses were more likely to receive their PPP loan from a fintech lender than a regular bank. Additionally, it highlighted the borrowing rate from fintechs among Black business owners was higher than any other group.

It is no secret minority entrepreneurs, like Black business owners, have struggled more than white borrowers when it comes to finding a lender.

According to the U.S. Small Business Administration, the Paycheck Protection Program is “an SBA-backed loan that helps businesses keep their workforce employed during the COVID-19 crisis.”

Sabrina T. Howell, who is an assistant professor of finance at the New York University Stern School of Business and was the main author of the paper, said to The New York Times, “I was taken aback by the striking disparity—it was a surprising and unexpected fact, and we wanted to figure out why.”

These results come at a time when there is scrutiny about how algorithmic systems can unintentionally eternalize biases. Regulators, such as the Consumer Financial Protection Bureau, are evaluating whether or not lenders use these systems improperly, according to The New York Times.

There is an opportunity for technology to level the playing field, according to Dr. Howell.

“The human brain is a much scarier black box than any machine-learning algorithm,” she said to The New York Times. “You can constrain an algorithm to meet fair-lending standards, and you can ensure the data it trains on isn’t biased. That may be hard to do, but it’s a clear and objective possibility.”