Evaluating borrower’s default risk in peer-to-peer lending: evidence from a lending platform in China

ABSTRACT

Recent years have witnessed the popularity of online peer-to-peer lending, which allows individuals to borrow from and lend to each other on an Internet-based platform. Using data from a large P2P platform in China, this article explores the factors that determine the default risk based on the demographic characteristics of borrowers. Moreover, we propose a credit risk evaluation model, which can quantify the default risk of each P2P loan. Empirical results reveal that gender, age, marital status, educational level, working years, company size, monthly payment, loan amount, debt to income ratio and delinquency history play a significant role in loan defaults. Finally, we analyse the relationship between default risk and these contributory variables, and the possible causes are also discussed in this study.

KEYWORDS:

• Default risk
• credit risk assessment
• peer-to-peer lending
• demographic characteristic

JEL CLASSIFICATION:

• D12
• G20

Acknowledgements

This article was supported by Major Program of the National Social Science Foundation of China under Grant No. 15ZDB154.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ There are serious differences of social and economic development existing between inland and coastal cities in China. According to the different development level, China can be divided into three economic belt: Eastern China, Central China and Western China. The economic development of Eastern China is the best of these three regions, Central China is the medium region for economic development, and the economic development of Western China is relatively slow.

Additional information

Funding

This article was supported by Major Program of the National Social Science Foundation of China under Grant No. 15ZDB154.