Regulators in the United States have been tied up in a policy debate for the past few years about how much of customers’ financial data should be kept private. As banks and other lenders have doubled down on efforts to use data to assess customers’ creditworthiness, credit ratings have come under intense scrutiny because of questions about privacy and bias.
Historical data can shape future outcomes, helping to determine whether a prospective borrower has access to a home, car, or other opportunities, write University of Utah’s Mark Jansen, Chicago Booth PhD student Fabian Nagel, and Booth’s Constantine Yannelis and Anthony Lee Zhang. Removing key information such as a past bankruptcy from customers’ credit records can make a great deal of difference to individuals’ credit scores and their cost of borrowing, they find.
The analysis suggests that restricting access to such data has a small overall social-welfare cost for consumers but could be a boon for low-income consumers, effectively securing credit for those who need it most.
Experian and TransUnion are among the companies that provide lenders with a host of data about borrowers. They translate information about bankruptcies, mortgage repayments, student loans, educational backgrounds, and even unpaid parking fines into credit scores, which lenders use to calculate individual risk and interest rates.
In theory, this is good for social welfare, the idea among economists being that greater market efficiency increases well-being for society in general. Access to data improves efficiency and helps banks develop more precise pricing strategies. Higher-risk customers—who’ve previously declared bankruptcy, say—are designated high-cost borrowers because they’re statistically more likely to default. Customers with better credit scores pay lower prices or interest rates. The researchers’ model of household lending confirms this: having better access to data improves social welfare by enabling banks and lenders to differentiate between customers while allocating credit.
In an analysis of a sample of US borrowers from 2009 to 2018, researchers find that removing bankruptcy flags from borrowers’ records 7–10 years after filings led to a sharp increase in average credit scores and in the average size of new loans made at lower interest rates.
However, the researchers also find that these social-welfare gains are so small as to be almost negligible. They analyzed almost a decade of US car-loan data from the TransUnion Consumer Credit panel, housed at Booth’s Kilts Center for Marketing, to see what happened when lenders removed credit flags relating to borrowers’ past bankruptcies. Under the Fair Credit Reporting Act of 1970, lenders in the US are required to remove any information or flags relating to a bankruptcy from personal credit archives 7–10 years after the filing.
When bankruptcy flags were removed from people’s records, borrowers’ credit scores rose by an average of 17 points, reducing the interest rates on their loans by almost 23 basis points, and enabling them to borrow an additional $18 per person.
“Through the lens of our cost-benefit analysis model, we see that restricting data by removing these flags transfers approximately $19 million to previously bankrupt customers each year,” says Zhang. “But the concomitant annual loss in total social welfare is just $598,000.”
The researchers don’t make specific policy recommendations but note that restricting the availability of data after some length of time could be a useful tool for policy makers fighting poverty. It could increase and make more equitable access to credit, and could be more efficient than some other anti-poverty measures—such as a minimum wage and rent control—that distort markets. A minimum wage can increase costs to employers and lead to increased unemployment, while rent control can squeeze the supply of housing and in the long run push prices up.
Restricting banks’ access to customer data creates fewer such ripples in the economy, the researchers argue. The social-welfare loss is minimal, and there could be clear benefits in terms of wealth distribution.
Mark Jansen, Fabian Nagel, Constantine Yannelis, and Anthony Lee Zhang, “Data and Welfare in Credit Markets,” Working paper, July 2022.
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