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Annals of Data Science

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10-03-2017

Influencing Factors of Online P2P Lending Success Rate in China

Authors: Zhuopei Yang, Yanmei Zhang, Hengyue Jia

Published in: Annals of Data Science | Issue 2/2017

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Abstract

The low success rate of lending is the main drawback of development of online P2P lending platforms in China. Based on the theory of social capital, this study analysed the influence factors of success rate of P2P lending platform in China, using social network method and multiple linear regression model. Soft information, such as bidding record, has been creatively employed to study the corresponding topics. Data used in this study comes from the largest online P2P lending platform in China. The results show that: compared with other influence factors, the bidding record has a more significant effect on the success rate, and the users depend more on the social capital; the bidding records reduce the asymmetry of information, and help increasing the success rate of lending and decreasing the cost of online P2P lending.

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Title: Influencing Factors of Online P2P Lending Success Rate in China
Authors: Zhuopei Yang
Yanmei Zhang
Hengyue Jia
Publication date: 10-03-2017
Publisher: Springer Berlin Heidelberg
Published in: Annals of Data Science / Issue 2/2017
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-017-0103-6

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