The impact of credit scoring on consumer lending

Authors


  • We thank Luke Stein for excellent research assistance, Will Adams for his contributions to this project, and two anonymous referees, the editor, Chris Knittel, Ulrike Malmendier, Vikrant Vig, and seminar participants at IO Fest 2008 at Stanford, the 2009 AEA annual meeting in San Francisco, the 2011 AEA annual meeting in Denver, and the 2009 NBER IO summer meeting in Cambridge, Massachusetts, for helpful comments. We acknowledge support from the Stanford Institute for Economic Policy Research, the National Science Foundation (Einav and Levin), and the Center for Advanced Study in the Behavioral Sciences (Levin). Earlier drafts of this article were circulated with the title “The Impact of Information Technology on Consumer Lending.”

Abstract

We study the adoption of automated credit scoring at a large auto finance company and the changes it enabled in lending practices. Credit scoring appears to have increased profits by roughly a thousand dollars per loan. We identify two distinct benefits of risk classification: the ability to screen high-risk borrowers and the ability to target more generous loans to lower-risk borrowers. We show that these had effects of similar magnitude. We also document that credit scoring compressed profitability across dealerships, and provide evidence consistent with the view that credit scoring may have substituted for varying qualities of local information.

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