The Impact of Automated Investment on Peer-to-Peer Lending

Cheng Chen, Guannan Li, Liangchen Fan, Jin Qin

OAI: oai:igi-global.com:276944 • DOI: 10.4018/JGIM.20211101.oa36

In the face of fierce competition, many peer-to-peer (P2P) lending platforms have introduced automated investment tools to serve customers better. Based on a large sample of data from PPdai.com, the authors studied the impact of automated investment on lenders’ investment behavior and platform performance. Using the propensity score matching (PSM) method, this article checks the differences of funding duration and loan performance with and without participation of automated investment tools in P2P lending. Our empirical results show that automated investment in P2P lending can significantly weaken investors’ herding behavior. The authors also found that automated investment prolongs the average funding duration of loans and undermines the platform efficiency. Furthermore, this study indicates that usage of automated investment does not affect the return on investment (ROI) in general.

Global Information Technology Computer Science and Information Technology IT Research and Theory