Authors
Rajkamal Iyer, Asim Ijaz Khwaja, Erzo FP Luttmer, Kelly Shue
Publication date
2016/6
Journal
Management Science
Volume
62
Issue
6
Pages
1554-1577
Publisher
INFORMS
Description
This paper examines the performance of new online lending markets that rely on nonexpert individuals to screen their peers’ creditworthiness. We find that these peer lenders predict an individual’s likelihood of defaulting on a loan with 45% greater accuracy than the borrower’s exact credit score (unobserved by the lenders, who only see a credit category). Moreover, peer lenders achieve 87% of the predictive power of an econometrician who observes all standard financial information about borrowers. Screening through soft or nonstandard information is relatively more important when evaluating lower-quality borrowers. Our results highlight how aggregating over the views of peers and leveraging nonstandard information can enhance lending efficiency.
This paper was accepted by Amit Seru, finance.
Total citations
Scholar articles
R Iyer, AI Khwaja, EFP Luttmer, K Shue - Management Science, 2016
R Iyer, AI Khwaja, EFP Luttmer, K Shue - AFA 2011 Denver meetings paper, 2009
RIAIK Erzo, FPLK Shue - 2010
A Khwaja, R Iyer, EFP Luttmer, K Shue - CID Working Paper Series, 2013
AI Khwaja, R Iyer, EFP Luttmer, K Shue - 2009
RIAIK Erzo, FPLK Shue - Retrieved on 20th January, 2014
AI Khwaja, R Iyer, EFP Luttmer, K Shue - 2013