Evaluating Default Risk and Loan Performance in UK Peer-to-Peer Lending: Evidence from Funding Circle

被引：3
|
作者：
Xu, Boyu [1 ]
Su, Zhifang [1 ]
Celler, Jan [1 ]
机构：
[1] Huaqiao Univ, Sch Econ & Finance, 269 Chenghua,North Rd, Quanzhou 362021, Fujian, Peoples R China
来源：
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2021年 / 22卷 / 05期
关键词：
P2P lending; default risk; logistic regression; marginal effect; Cox Proportional Hazard regression; INFORMATION ASYMMETRY; SOFT INFORMATION; NETWORKS;
D O I：
10.20965/jaciii.2021.p0530
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The United Kingdom is the third-largest peer-to-peer (P2P) lending market in the world, which is surpassed only by the two dominant forces in P2P investing, China and the United States of America. As an innovative financial market in the UK, P2P lending brings not only many opportunities but also many risks, especially the loan default risk. In this context, this paper uses binary logistic regression and survival analysis to evaluate default risk and loan performance in UK P2P lending. The empirical results indicate that credit group, loan purpose for capital needs, sector type, loan amount, interest rate, loan term, and the age of the company all have a significant impact on the probability of loan default. Among them, the interest rate, loan term, and loan purpose for capital needs are the three most important determinants of the probability of loan defaults and survival time of loans.
引用
收藏
页码：530 / 538
页数：9
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