Automation Helped Black Borrowers Get the Most Out of PPP in Fintechs and Big Banks: Study


Dive brief:

  • According to an economic working paper by New York University researchers released Monday.
  • The study found that after controlling for a company’s zip code, industry, loan size, PPP approval date, and other characteristics, black-owned businesses were 12.1 points percentage more likely to get their PPP loan from a fintech lender than a traditional bank. “Among conventional lenders, small banks were much less likely to lend to black-owned businesses, while the top four banks showed little or no disparity after including checks,” the researchers wrote.
  • Automated loan verification, commonly used by fintechs and big banks, has improved approval rates for black borrowers who applied for loans from both nonbanks and the country’s largest institutions, concluded. Researchers.

Dive overview:

Researchers said they found evidence that when small banks automate their lending processes and reduce human involvement in the loan origination process, their black-owned business PPP lending rate increases, with larger effects. in places with more racial animosity.

“Fintech lenders almost completely automate their underwriting processes, leaving little room for preference-based discrimination to affect the approval decision,” the researchers wrote. “In contrast, conventional lenders have traditionally relied more on human involvement and personal relationships between loan officers and clients.”

The researchers said they found significant variation in the degree of automation among traditional lenders, “with the big banks – those where we see little difference in the conditional likelihood of lending to black-owned businesses – being more automated than the larger banks. small banks “.

Sabrina T. Howell, Assistant Professor of Finance at the Stern School of Business at New York University and lead author of the article, told the New York Times research illustrates how technology can help level the playing field for borrowers.

“The human brain is a much scarier black box than any machine learning algorithm,” Howell said. “You can force an algorithm to meet fair lending standards, and you can make sure that the data it trains on is unbiased. It may be difficult to do, but it is a clear and objective possibility. Whereas when you have a human loan officer standing in front of someone and making a decision, you can never do that. “

The Independent Community Bankers of America (ICBA), however, rebuffed the study’s findings, saying the Times community banks had “outperformed the rest of the banking industry in serving minority, women and corporate owned businesses. veterans “.

The group took issue with some of the methods used by researchers to determine a candidate’s race.

The researchers used Census Bureau data on the locations and last names of business owners to project what race they were likely to be, since collecting data on the ethnicity of borrowers was optional for those who owned the business. lenders.

The ICBA said these steps turned the research into “an unreliable guessing game.”

The NYU study is the latest research report to analyze the $ 806 billion loan program, which was designed to provide forgivable loans to struggling small businesses amid pandemic lockdowns.

A study published by the Federal Reserve Bank of New York in May also found that black-owned businesses were more likely to turn to non-banks and fintechs for P3 loans than business owners of other races or ethnicities.

One in four black business owners who applied for a P3 loan used a fintech rather than a traditional bank – more than twice the rate for businesses owned by whites, Asians and Hispanics, researchers from the Fed.

Another study conducted by researchers at the McCombs School of Business at the University of Texas at Austin paints a much less rosy picture of the involvement of fintechs in the economic aid program.

The report, published in August, found that fintech lenders were nearly five times more likely to be linked with suspicious PPP loans.

The study examined over 10 million PPP loans for potential red flags such as unregistered businesses, multiple businesses with a residential address, unusually high implied compensation per employee, and large inconsistencies in reported jobs with a another government program, and found that nine of the 10 lenders with the highest rates of suspicious PPP loans were fintechs.

“While FinTech lenders are likely to expand access to P3s, this may have the effect of facilitating fraudulent credit,” they wrote.

Previous United Arab Emirates: EmSAT exam to help low-grade students enter university - News
Next The contribution of the Nyundo School of Arts and Music to Rwanda's music industry | New times

No Comment

Leave a reply

Your email address will not be published. Required fields are marked *