Optimal Credit Scores Under Adverse Selection

33 Pages Posted: 20 May 2022

See all articles by Nicole Immorlica

Nicole Immorlica

Microsoft Research

Andre Sztutman

Massachusetts Institute of Technology (MIT)

Robert M. Townsend

Massachusetts Institute of Technology (MIT)

Date Written: May 18, 2022

Abstract

The increasing availability of data in credit markets may appear to make adverse selection concerns less relevant. However, when there is adverse selection, more information does not necessarily increase welfare. We provide tools for making better use of the data that is collected from potential borrowers, formulating and solving the optimal disclosure problem of an intermediary with commitment that seeks to maximize the probability of successful transactions, weighted by the size of the gains of these transactions. We show that any optimal disclosure policy needs to satisfy some simple conditions in terms of local sufficient statistics. These conditions relate prices to the price elasticities of the expected value of the loans for the investors. Empirically, we apply our method to the data from the Townsend Thai Project, which is a long panel dataset with rich information on credit histories, balance sheets, and income statements, to evaluate whether it can help develop the particularly thin formal rural credit markets in Thailand, finding economically meaningful gains from adopting limited information disclosure policies.

Keywords: information design, applied machine learning, credit scores, rural credit markets

JEL Classification: C58, D82, G21, Q14

Suggested Citation

Immorlica, Nicole and Sztutman, Andre and Townsend, Robert M., Optimal Credit Scores Under Adverse Selection (May 18, 2022). Available at SSRN: https://ssrn.com/abstract=4113505 or http://dx.doi.org/10.2139/ssrn.4113505

Nicole Immorlica

Microsoft Research ( email )

One Memorial Drive, 14th Floor
Cambridge, MA 02142
United States

Andre Sztutman (Contact Author)

Massachusetts Institute of Technology (MIT) ( email )

Cambridge, MA 02142
United States

Robert M. Townsend

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
193
Abstract Views
510
Rank
236,872
PlumX Metrics