WASHINGTON—Should borrowers be denied new loans because they haven’t finished school?
This kind of question annoys policymakers as they seek to encourage lenders to use new types of data and computer models to enable more borrowers to qualify for loans and at lower prices.
These efforts aim to address growing criticism of an existing credit reporting system that relies on past loan repayment history but also raises questions about fairness and credit accessibility.
Several bills have been introduced in the House of Representatives this year by lawmakers from both parties to improve the credit scoring system. Last month, a bipartisan fintech task force held a hearing on the use of alternative data.
Rep. French Hill (R., Ark.), the task force’s lead Republican, said alternative credit criteria have “the potential to expand the universe of borrowers and provide greater access to affordable credit.” “. Citing a report from credit reporting firm TransUnion,
Mr Hill said two out of three lenders were able to lend to more borrowers through the use of alternative data.
Democratic presidential candidate Sen. Kamala Harris (D., Calif.) has offered to include on-time rent payments and cellphone bills in credit scores as part of her campaign promise to boost black home ownership.
Some fintech companies are already using these techniques. At Upstart Network Inc., an online lender founded by former Google Inc. employees, loan seekers are asked to provide the highest degree earned, the name of the university or college attended, and the fields of study. education, as well as work history.
“Using work history and education history generates a much more accurate credit model,” says Dave Girouard, Head of Upstart. He adds that the company’s model approves 27% more loan applicants for its personal loans than the traditional credit-scoring model and results in 16% lower average interest rates for approved loans.
Other lenders also use educational history or employment status to screen borrowers, with similar results, as well as more widely accepted data such as rent and utility payments and cash flow from bank statements. borrowers.
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Despite the growing adoption of these measures, some consumer advocates say the trend will hurt low-income or minority borrowers. “It entrenches and perpetuates inequality in such an obvious and brutal way,” says National Consumer Law Center attorney Chi Chi Wu, who adds that the existing system already makes it harder for low-income people and less assets to qualify for cheaper loans.
The ratio of people with at least a bachelor’s degree is 33% among whites and 54% among Asians, compared to 23% among African Americans and 16% among Hispanics, according to census data.
Policymakers hope, however, that alternative data will allow lenders to reach some of the 45 million Americans, or 19.3% of the adult population, who currently do not have access to credit, according to the Consumer Financial Protection Bureau.
Given their reliance on loan repayment history, traditional scoring models handicap young people who have little or no credit history, as well as those who may have had previous financial difficulties.
But determining what types of data should be allowed in credit scoring is a complex and controversial task. The Equal Credit Opportunity Act of 1974, the main law used to guarantee access to credit and prevent discrimination, prohibits lenders from using information such as race, sex, national origin and age as factors to determine the availability of credit. The use of other types of information, such as income and assets, is permitted.
Whether the use of education and occupation related data is appropriate is debatable. While serving as a strong indicator of people’s creditworthiness, the data shows a similar correlation with prohibited factors. A 2015 study by Federal Reserve economists showed that the average student loan delinquency rate among those who did not complete college was 44%, compared to 11% for those with a bachelor’s degree.
“US anti-discrimination law from the 1970s is not well suited to deal with today’s big data reality,” says Aaron Klein, policy director of the Center for Regulation and Markets at the Brookings Institution. He added that change must start with an honest conversation about which borrowers deserve special protection and how to compensate lenders to serve riskier consumers.
Uncertainty has largely prevented traditional banks from using alternative data. Even fintech lenders in the United States generally stick to non-controversial information such as bank account data and avoid information gleaned from social media.
“There is still a framework that makes it perfectly safe [use such information] without facing an existential threat,” said David Klein, chief executive of CommonBond, an online student loan provider.
The Government Accountability Office, the independent watchdog of Congress, recommended in December that financial regulators provide clearer guidance to lenders on how to use alternative data in the underwriting process, which has not happened. not yet produced.
While most lenders closely monitor their lending models, Upstart’s experience is telling. The company has developed and operated its lending model under CFPB oversight for nearly two years. It is the only company that has been approved for its innovation program. On Monday, the CFPB unveiled detailed data on how Upstart’s model has expanded access to credit and encouraged other lenders to explore ways to lend to more people with no or limited credit histories. .
Mr. Girouard, of Upstart, says the company’s model offers higher approval rates and lower interest rates for “all traditionally underserved demographics.”
It first tried using test scores and weighted borrower averages, but abandoned it four years ago because “the effort to collect and verify information was not worth the predictability it provided. “, did he declare.
Write to Yuka Hayashi at [email protected]
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