What do a million observations have to say about loan defaults? Opening the black box of relationships

B-Tier
Journal: Journal of Financial Intermediation
Year: 2017
Volume: 31
Issue: C
Pages: 1-15

Authors (3)

Puri, Manju (Duke University) Rocholl, Jörg (not in RePEc) Steffen, Sascha (not in RePEc)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Using a unique dataset of more than 1 million loans made by 296 German banks, we evaluate the impact of many aspects of customer–bank relationships on loan default rates. Our research suggests a practical solution to reducing loan defaults for new customers: Have the customer open a simple transactions account – savings or checking account. Observe for some time and then decide whether to make a loan. Loans made under this model have lower default, as banks can use historical data about their borrowers to establish a baseline against which new client-related information can be evaluated. Banks assemble this historical information through relationships of different forms. We define relationships in many different ways to capture non-credit relationships, transaction accounts, as well as the depth and intensity of relationships, and find each of these can provide information that helps reduce default – even establishing a simple savings or checking account and observing the activity prior to loan granting can help reduce loan defaults. Our results show that banks with relationship-specific information act differently compared with banks that do not have this information both in screening and subsequent monitoring borrowers which helps reduce loan defaults.

Technical Details

RePEc Handle
repec:eee:jfinin:v:31:y:2017:i:c:p:1-15
Journal Field
Finance
Author Count
3
Added to Database
2026-01-29