Forward looking vs backward looking: An empirical study on the effectiveness of credit evaluation system in China’s online P2P lending market

Yanyan Gao (The Department of Finance, Southeast University, Nanjing, China)
Jun Sun (Huaihai Institute of Technology, Lianyungang, China)
Qin Zhou (School of Economics and Management, Southeast University, Nanjing, China)

China Finance Review International

ISSN: 2044-1398

Publication date: 15 May 2017

Abstract

Purpose

The purpose of this paper is to estimate the effectiveness of the credit evaluation system using the borrowing data from China’s leading P2P lending platform, Renrendai.com.

Design/methodology/approach

The current credit valuation systems are classified into the forward-looking mechanism, which judges the borrowers’ credit levels based on their uploaded information, and the backward-looking mechanism, which judges the borrowers’ credit levels based on their historical repayment performance. Probit models and Tobit models are used to examine the effectiveness of credit evaluation mechanisms.

Findings

The results show that only the “hard” information reflecting borrowers’ credit ability can explain the default risk on the platform under the forward-looking credit evaluation mechanism. The backward-looking credit evaluation mechanism (BCEM) based on the repeated borrowings produces both promise-enhancing and “fishing” incentives and thus fails to explain the default risk, and weakens the effectiveness of forward-looking credit indicators in explaining the default risk because it encourages borrowers to invest in forging forward-looking credit indicators. Additional information such as the interest rate and the repayment periods reveals borrowers’ credit and thus can also be used as a predictor of borrowers’ default risk.

Practical implications

The findings suggest that current ex ante screening based on the information collected from the borrowers or repeated borrowings is inadequate to control the default risk in P2P lending markets and thus needs be improved. Ex post monitoring and sharing on defaulter’s information should be strengthened to increase the default cost and thus to deter potential bad borrowers.

Originality/value

To the authors’ knowledge, this is the first paper classifying the credit evaluation system in online P2P lending market into the forward-looking type and the backward-looking type, which is important since they provide different incentives to borrowers. The paper also investigates and provides evidence on the promise-enhancing and “fishing” incentives of BCEMs.

Keywords

Acknowledgements

The authors thank for helpful comments from three anonymous referees, the participants at Advanced Forums on Internet Finance (2015) in Nanjing University, the 2nd Financial Management Forums (2015) in the University of International Business and Economics and 2016 AFAANZ Conference in Gold Coast, Australia. All errors remain to the authors. The authors also thank for the fund supports by the Key Project of China Social Science Foundation (Grant No. 15AJL004), the Youth Project of MOE Social Science Foundation (Grant No. 14YJC790107), the General Project of Jiangsu Social Science Foundation (Grant No. 15GLB013) and the Fundamental Research Funds for the Central Universities (Grant No. 2242016S20013).

Citation

Gao, Y., Sun, J. and Zhou, Q. (2017), "Forward looking vs backward looking: An empirical study on the effectiveness of credit evaluation system in China’s online P2P lending market", China Finance Review International, Vol. 7 No. 2, pp. 228-248. https://doi.org/10.1108/CFRI-07-2016-0089

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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