Keywords

FinTech, personal loans, credit score, nonprime borrowers, market segmentation

Abstract

FinTech lending—known for using big data and advanced technologies—promised to break away from the traditional credit scoring and pricing models. Using a comprehensive dataset of FinTech personal loans, our study shows that loan rates continue to rely heavily on conventional credit scores, including 45% higher rates for nonprime borrowers. Other known default predictors are often neglected. Within each segment (prime/nonprime) loan rates are not very responsive to default risk, resulting in realized loan-level returns decreasing with risk. The pricing distortions result in substantial transfers from nonprime to prime borrowers and from low- to high-risk borrowers within segment.

Original Publication Citation

FinTech Lending with LowTech Pricing (with Itzhak Ben-David, Jason Lee, and Vincent Yao)

Document Type

Working Paper

Publication Date

2023

Publisher

Fisher College of Business Working Paper Series

Language

English

College

Marriott School of Business

Department

Finance

University Standing at Time of Publication

Assistant Professor

Share

COinS