Digital Verification and Inclusive Access to Credit: An Empirical Investigation

44 Pages Posted: 14 Apr 2020

See all articles by Tat Chan

Tat Chan

Washington University in St. Louis - John M. Olin Business School

Naser Hamdi

Equifax, Inc.

Xiang Hui

Washington University in St. Louis - John M. Olin Business School

Zhenling Jiang

University of Pennsylvania - The Wharton School

Date Written: March 18, 2020

Abstract

To mitigate asymmetric information in the consumer lending market, lenders typically rely on credit information to grant loans. In this paper, we study how the digitization of employment and income verification promotes inclusive access to credit by further reducing asymmetric information over and beyond the use of credit scores. Using a data set covering all employment verification inquiries to Equifax associated with auto loan applications, we empirically investigate how loan outcomes change after the employers of auto loan applicants join the digitization system of Equifax. We find an increase in both the loan origination rate and delinquency rate, mainly ascribable to deep subprime and subprime consumers. Interest rates have also become slightly higher. Finally, the digital verification increases lenders’ profit, because the negative impact of the increased delinquency rate is more than offset by the growth in loan origination. These findings are consistent with a model where instant access to verified data helps reduce the time and effort required to gather information, allowing for expanded access to finance for marginal consumers. Our results help inform managers and public policy makers on ways of improving economic efficiency and lenders’ profit in the consumer lending market, while promoting inclusive access to credit.

Keywords: Inclusive Access to Credit; Digitization; Verification Cost; Information Asymmetry

Suggested Citation

Chan, Tat and Hamdi, Naser and Hui, Xiang and Jiang, Zhenling, Digital Verification and Inclusive Access to Credit: An Empirical Investigation (March 18, 2020). Available at SSRN: https://ssrn.com/abstract=3556554 or http://dx.doi.org/10.2139/ssrn.3556554

Tat Chan

Washington University in St. Louis - John M. Olin Business School ( email )

One Brookings Drive
Campus Box 1133
St. Louis, MO 63130-4899
United States

Naser Hamdi

Equifax, Inc. ( email )

Atlanta, GA
United States

Xiang Hui

Washington University in St. Louis - John M. Olin Business School ( email )

One Brookings Drive
Campus Box 1133
St. Louis, MO 63130-4899
United States

Zhenling Jiang (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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