Working Paper: NBER ID: w28021
Authors: Marco Di Maggio; Vincent Yao
Abstract: We study the personal credit market using unique individual-level data covering fintech and traditional lenders. We show that fintech lenders acquire market share by first lending to higher-risk borrowers and then to safer borrowers, and mainly rely on hard information to make credit decisions. Fintech borrowers are significantly more likely to default than neighbor individuals with the same characteristics borrowing from traditional financial institutions. Furthermore, they tend to experience only a short- lived reduction in the cost of credit, because their indebtedness increases more than non-fintech borrowers a few months after loan origination. However, fintech lenders' pricing strategies are likely to take this into account.
Keywords: Fintech; Borrowers; Credit Market
JEL Codes: G21; G23; G4
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| fintech loans (G21) | higher default rates (G33) |
| fintech loans (G21) | higher likelihood of default (G33) |
| higher default rates (G33) | fintech borrowers' increase in total indebtedness (G21) |
| fintech lenders' interest rates (G21) | better predictors of default (G33) |
| fintech borrowers (G21) | higher likelihood of default (G33) |