Who can get money? Evidence from the Chinese peer-to-peer lending platform

This paper explores how borrowers’ financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher...

Full description

Saved in:
Bibliographic Details
Published inInformation systems frontiers Vol. 19; no. 3; pp. 425 - 441
Main Authors Tao, Qizhi, Dong, Yizhe, Lin, Ziming
Format Journal Article
LanguageEnglish
Published New York Springer US 01.06.2017
Springer Nature B.V
Subjects
Bank holding companies
Big Data
Business and Management
Control
Data management
Decision making
Electronic banking
Information systems
Interest rates
IT in Business
Lending institutions
Management of Computing and Information Systems
Online banking
Operations Research/Decision Theory
Peer to peer computing
Peer to peer lending
Systems Theory
China
Listing outcomes
Peer-to-peer (P2P) lending
Fintech, offline authentication
Information asymmetry
China
Online AccessGet full text

Cover

More Information
Summary:This paper explores how borrowers’ financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher income or who own a car are more likely to receive a loan, pay lower interest rates, and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. We also find that the unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision. We discuss the implications of our results for the design of big data-based lending markets.
ISSN:1387-3326
1572-9419
DOI:10.1007/s10796-017-9751-5