Borrowing from a Bigtech Platform

93 Pages Posted: 21 Sep 2022 Last revised: 30 Nov 2023

See all articles by Jian Li

Jian Li

Columbia University - Columbia Business School, Finance

Stefano Pegoraro

University of Notre Dame - Department of Finance

Date Written: August 31, 2022

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.

Keywords: Bigtech, platform, enforcement, adverse selection, moral hazard, advantageous screening, welfare, credit rationing

JEL Classification: G21, G23, C72, D82

Suggested Citation

Li, Jian and Pegoraro, Stefano, Borrowing from a Bigtech Platform (August 31, 2022). Available at SSRN: https://ssrn.com/abstract=4206016 or http://dx.doi.org/10.2139/ssrn.4206016

Jian Li

Columbia University - Columbia Business School, Finance ( email )

3022 Broadway
New York, NY 10027
United States

Stefano Pegoraro (Contact Author)

University of Notre Dame - Department of Finance ( email )

P.O. Box 399
Notre Dame, IN 46556-0399
United States
5746312240 (Phone)
46556 (Fax)

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