Consumer Lending Discrimination in the FinTech Era

43 Pages Posted: 6 Nov 2017 Last revised: 11 Sep 2019

See all articles by Robert P. Bartlett

Robert P. Bartlett

University of California, Berkeley - School of Law; University of California, Berkeley - Berkeley Center for Law, Business and the Economy

Adair Morse

University of California, Berkeley - Haas School of Business; National Bureau of Economic Research (NBER)

Richard Stanton

University of California, Berkeley - Haas School of Business

Nancy Wallace

University of California, Berkeley - Real Estate Group

Multiple version iconThere are 3 versions of this paper

Date Written: December 7, 2017

Abstract

Discrimination in lending can occur either in face-to-face decisions or in algorithmic scoring. We provide a workable interpretation of the courts’ legitimate-business-necessity defense of statistical discrimination. We then estimate the extent of racial/ethnic discrimination in the largest consumer-lending market using an identification afforded by the pricing of mortgage credit risk by Fannie Mae and Freddie Mac. We find that lenders charge Latinx/African-American borrowers 7.9 and 3.6 basis points more for purchase and refinance mortgages respectively, costing them $765M in aggregate per year in extra interest. FinTech algorithms also discriminate, but 40% less than face-to-face lenders. These results are consistent with both FinTech and non-FinTech lenders extracting monopoly rents in weaker competitive environments or profiling borrowers on low-shopping behavior. Such strategic pricing is not illegal per se, but under the law, it cannot result in discrimination. The lower levels of price discrimination by algorithms suggests that removing face-to-face interactions can reduce discrimination. Further silver linings emerge in the FinTech era: (1) Discrimination is declining; algorithmic lending may have increased competition or encouraged more shopping with the ease of platform applications. (2) We find that 0.74-1.3 million minority applications were rejected between 2009 and 2015 due to discrimination; however, FinTechs do not discriminate in loan approval.

Keywords: Discrimination, FinTech, Mortgages, Credit Scoring, Algorithmic Underwriting, Big Data Lending, Platform Loans, Disparate Impact, Legitimate Business Necessity

JEL Classification: G21, G28, G23, J14, K22, K23, R30

Suggested Citation

Bartlett, Robert P. and Morse, Adair and Stanton, Richard H. and Wallace, Nancy E., Consumer Lending Discrimination in the FinTech Era (December 7, 2017). UC Berkeley Public Law Research Paper, Available at SSRN: https://ssrn.com/abstract=3063448 or http://dx.doi.org/10.2139/ssrn.3063448

Robert P. Bartlett

University of California, Berkeley - School of Law ( email )

215 Boalt Hall
Berkeley, CA 94720-7200
United States
510-642-6646 (Phone)

University of California, Berkeley - Berkeley Center for Law, Business and the Economy

UC Berkeley School of Law
Berkeley, CA 94720

Adair Morse (Contact Author)

University of California, Berkeley - Haas School of Business ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Richard H. Stanton

University of California, Berkeley - Haas School of Business ( email )

Haas School of Business
545 Student Services Building #1900
Berkeley, CA 94720-1900
United States
(510) 642-7382 (Phone)
(510) 643-1412 (Fax)

Nancy E. Wallace

University of California, Berkeley - Real Estate Group ( email )

Berkeley, CA 94720-1900
United States

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