U.S. Representative Emanuel Cleaver II (D-MO) has published the initial findings of a probe into the alternative small business lending market in an effort to explore borrower protections, fairness and the possible need for greater regulatory oversight.
About a year after reports first surfaced that Cleaver would be examining the industry, the initial findings of the investigation have revealed several key concerns of the market. According to the report, published earlier this month, they include the common practice of forced arbitration — also widespread in the traditional lending space — as well as the use of consumer credit scores to assess the creditworthiness of a small business borrower. According to the report, the practice is “exploitative” and “largely unnecessary.”
Additional conclusions pointed to the use of alternative data in the underwriting process, including zip codes and social media profiles, which can also be used to discriminate against certain demographics of small business owners, including “lower-income borrowers and people of color,” the report stated.
But according to Cleaver’s investigation, the most widespread problem is an overall lack of transparency in alternative lenders’ algorithms and specific efforts to curb discrimination.
“One of the most concerning findings was how willfully vague some companies were being about the structure and nature of their algorithms,” the report continued. “While a few companies provided detailed information, others did not disclose whether they used race and gender information, or proxies for it, in their loan calculation. … If companies cannot volunteer even the most limited information, how can they be trusted to provide fair credit to small business owners?”
On the plus side, Cleaver’s report did find some alternative lending players are turning to proprietary credit scores, an alternative to personal credit scores that focus on the performance and historical data of the business, as well as the use of third parties in the underwriting process to prevent against bias.
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