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  5. FinTech and the Industrial Organization of the Financial Sector
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FinTech and the Industrial Organization of the Financial Sector

Paper Session

Friday, Jan. 5, 2024 2:30 PM - 4:30 PM (CST)

Marriott Rivercenter, Grand Ballroom Salon I
Hosted By: American Finance Association
  • Chair: Nadya Malenko, Boston College

Customer Data Access and Fintech Entry: Early Evidence from Open Banking

Tania Babina
,
Columbia University
Gregory Buchak
,
Stanford University
Will Gornall
,
University of British Columbia

Abstract

Open banking is the trend of empowering customers to share their banking data with fintechs and other banks. We compile a novel dataset documenting that governments in 49 countries have implemented open banking policies and 31 more are in active discussions. Following adoption, fintech venture capital investment increases by 50%, with more comprehensive policies showing larger effects. We examine the policy tradeoffs with a quantitative model of consumer data production and usage. Our calibrations show that customer-directed data sharing increases entry by improving entrant screening ability and product offerings, but harms some customers and can reduce ex-ante information production.

Market Concentration in Fintech

Kuan Liu
,
University of Arkansas
Dean Corbae
,
University of Wisconsin-Madison
Pablo D'Erasmo
,
Federal Reserve Bank of Philadelphia

Abstract

This paper discusses concentration in consumer credit markets with a focus on
fintech lenders and residential mortgages. We present evidence that show that concentration among fintech lenders is significantly higher than that for bank lenders and other nonbank lenders. The data also show that the overall concentration in mortgage lending has declined between 2011 and 2019, driven mostly by a reduction in concentration among bank lenders. We present a simple model to show that changes in regulatory pressure explains about a third of the change in market shares but have a modest impact on concentration. Changes in lender financial technology (interpreted as improvements in quality of loan services) explain more than 50 per cent of the increase in fintech market shares and 43 per cent of the increase in fintech concentration. This change in concentration in the fintech industry may have important implications for regulatory policy and financial stability.

Borrowing from a Bigtech Platform

Stefano Pegoraro
,
University of Notre Dame
Jian Li
,
Columbia University

Abstract

We model competition between banks and a bigtech platform that lend to a merchant with private information and subject to moral hazard. By controlling access to a valuable marketplace for the merchant, the platform enforces partial loan repayments, thus alleviating financing frictions, reducing the risk of strategic default, and contributing to welfare positively. Credit markets become partially segmented, with the platform targeting merchants of low and medium perceived credit quality. However, conditional on observables, the platform lends to better borrowers than banks because bad borrowers self-select into bank loans to avoid the platform's enforcement, causing negative welfare effects in equilibrium.

Cashless Payment and Financial Inclusion

Shumiao Ouyang
,
University of Oxford

Abstract

Can in-person cashless payment improve credit provision to the underprivileged? I study Alipay, a BigTech platform that acts as a one-stop-shop for financial services for more than 1 billion users. Using a representative sample of Alipay users with detailed information on their consumption, credit, and investment activities, I exploit a natural experiment to estimate the effects of cashless payment adoption. The use of cashless payment in a month increases the likelihood of gaining access to credit in the same month by 56.3%. Conditional on having credit access, a 1% increase in the cashless payment flow leads to a 0.41% increase in the credit line. These effects are mainly present for the less educated and the older. To quantify the value of cashless payment data to the lender and consumers, I build and estimate a simple model and run a counterfactual in which the lender does not observe these data. I find that credit lines rise by 57.7% on average, consumer surplus rises by 0.5% of median disposable income, and the increase in lender profit is about 41.3% of the increase in consumer surplus.

Discussant(s)
Paul Beaumont
,
McGill University
Erica Xuewei Jiang
,
University of Southern California
Deeksha Gupta
,
Johns Hopkins University
Emily Williams
,
Harvard University
JEL Classifications
  • G2 - Financial Institutions and Services