Fintechs are increasing their lending activity to individuals with subprime credit scores, and regulators are starting to worry. Fintechs aren’t subject to the same regulations as big banks which makes their lending practices somewhat opaque.
Read the original article from GovTech magazine:
(TNS) — Financial technology (fintech) companies are increasingly lending to minorities and consumers with subprime credit scores, drawing attention from regulators who worry that the lack of oversight and transparency are allowing unfair or discriminatory practices to proliferate.
Rep. Emanuel Cleaver (D-Mo.) released a report Friday detailing the lending practices of some prominent fintech companies, finding that some companies could be discriminating against minorities and calling for more transparency from the fintech sector.
Fintech companies are somewhat controversial because many engage in traditional banking practices, and some consumers and regulators are calling for them to be regulated like traditional banks.
The top three findings from Cleaver’s investigation were that 1) fintech companies are more likely to lend to minority-owned businesses, 2) fintech companies need to be regulated to prevent discrimination and “unfair business practices,” and 3) some fintech companies have “implemented practices that should be widely adopted” to that end.
The fintech companies investigated for the report — which include Biz2Credit, Fora Financial, Kabbage, LendingClub, Lendup and OnDeck Capital, Inc. — may be serving subprime consumers that might not otherwiseget a loan, but that doesn’t mean they’re treating those consumers fairly, Cleaver argues.
“For example, almost every company that disclosed a reasonable amount of information admitted to using forced arbitration clauses in their contracts,” Cleaver wrote in the report. “These clauses require individuals to resolve all disputes out of court in a situation that is more favorable to the lenders, both from a monetary and public relations perspective.”
Cleaver also pushed back against fintech companies’ practice of using personal credit scores to determine small business loans.
“This is a common practice at traditional banks, but can be exploitative and is largely unnecessary,” Cleaver wrote. “A personal credit score has little bearing on a business model or the owner’s business acumen, and using it unfairly punishes minority business owners who may not have had the same opportunities to build credit.”
But Cleaver’s biggest concern is the lack of transparency. Fintech companies use data-driven algorithms to make loans to individuals and small businesses, but regulators don’t know what kind of data fintech companies are collecting or how it’s being used, which could allow a host of bad practices to fly under the radar.
Many of the companies he investigated were “willfully vague about the structure and nature of their algorithms,” Cleaver said. “This lack of volunteered information is concerning given the limited oversight our government currently has over the use and compiling of these algorithms.”
Some of these fintech companies are drawing data from social media profiles (like Twitter and Facebook), Cleaver found, but aren’t disclosing how that data plays into loan-making decisions.
Scott Astrada, the federal advocacy director for the Center for Responsible Lending (CRL), told InsideSources that while fintech innovates the “delivery channel” for loans, the “model is the same.”
“This deserves broader scrutiny because fintech companies will fly under this banner to say we can predict risk better, but they’re not transparent, so the proprietary algorithms are not subject to any scrutiny from the public or researchers or even regulators, and you can easily see how they could violate lending laws depending on what data points they use,” Astrada said. “The innovation of using different data points to measure risk isn’t new. They’re black boxes of risk assessment and there’s a whole host of red flags that could be going through there.”
Besides discrimination concerns, fintech companies could be making increasingly risky, reckless loans to subprime borrowers who are very unlikely to pay back the loan. Given that’s what happened in the mortgage market just 10 years ago and eventually crashed the market, there’s a fear something similar will happen with fintech companies.
But Lawrence White, professor of economics at New York University’s Leonard N. Stern School of Business, thinks another subprime lending catastrophe of that size and scope is unlikely.
“The widespread financial crisis was due to the fact that we had nine very large financial companies, like Goldman Sachs, like Morgan Stanley, Fannie Mae and Freddie Mac and Merrill Lynch, who did not have enough capital to be able to absorb the losses that were going to happen when those subprime borrowers couldn’t repay their loans,” White told InsideSources. “It’s quite likely we’ll see the same kind of crisis we saw ten years ago because we have the same kinds of financial companies but they have more capital, and we have regulators that are more attuned to the potential problems.”
Furthermore, there isn’t a handful of companies dominating the fintech market. The boom in fintech innovation has resulted in thousands of new, smaller companies focusing on different aspects of traditional banking, although a 2017 report from Deloitte found that the fintech sector is starting to consolidate, which could result in fewer fintech conglomerates dominating the market.
To avoid discriminating against minorities or conducting unfair business practices, Cleaver recommends fintech companies adopt disclosures per the Truth in Lending Act, similar to traditional banks, to clearly state why an individual or small business may be receiving a loan at a particular interest rate (i.e., explain how their algorithm affects the lending process).
He also said, “Fintech lenders should register with the Consumer Financial Protection Bureau’s complaint system to receive and respond to complaints” and “conduct — make publicly available — third-party fair lending audits that analyze loan origination data to determine whether there are statistically significant discriminatory markups.”