Seminar

Department: Finance

Speaker:  Kumar Rishabh (HEC Lausanne)

Room: T020

Abstract

I investigate the informational value of interoperable payment data in lending, integral to
global open banking initiatives. I utilize a unique dataset that links borrowers’ electronic
payment histories with both traditional bank loans and fintech loans issued to the same
set of Indian small businesses. In analyzing traditional bank loans, I find that payment
history complements credit bureau data in predicting loan delinquency. Quantitatively,
the informational value of aggregate payment data equates to the value of lender’s
soft information. In a counterfactual scenario where traditional lenders incorporate
payment history alongside their existing hard and soft information, substantial benefits
are realized. However, while about 29% of the enhancement from adding payment history
can be attributed to the hardening of soft information, the predominant value stems from
its independent contribution. After loan disbursal, payment data markedly enhances
delinquency predictions, affirming its role in generating timely early warning signals for
monitoring loans. While there is a trade-off between accuracy and privacy in screening,
this is less pronounced in monitoring. In the fintech lending with sales-linked loans,
payment history emerges as a substitute for traditional credit bureau data, albeit with
pronounced moral hazard challenges.