On the Rise of FinTechs: Credit Scoring Using Digital Footprints

TLDR

The paper investigates how digital footprints can predict consumer default and explores the implications for financial intermediaries, the unbanked, and regulatory behavior. The authors analyze the information content of users’ online activity—such as site access and registration—to forecast default risk. Digital footprint variables match the predictive power of credit bureau scores, complement them, and improve credit access while lowering default rates. JEL codes: G20, G21, G29.

Abstract

Abstract We analyze the information content of a digital footprint—that is, information that users leave online simply by accessing or registering on a Web site—for predicting consumer default. We show that even simple, easily accessible variables from a digital footprint match the information content of credit bureau scores. A digital footprint complements rather than substitutes for credit bureau information and affects access to credit and reduces default rates. We discuss the implications for financial intermediaries’ business models, access to credit for the unbanked, and the behavior of consumers, firms, and regulators in the digital sphere. (JEL G20, G21, G29)