Research on Risk Factors Identification of P2P Lending Platforms

Caimei  Lu; Lu  Zhang

doi:10.4236/ajibm.2018.85091

Caimei Lu¹, Lu Zhang²

Abstract: We take 2259 P2P Lending platforms as the sample, and integrate 14 variables from five dimensions to analyze the risk factors of P2P Lending problematic platforms by binary logistic model. The empirical results show that the 11 variables which are the type of company, platform background, operation time, the type of project, interest rate, fund custody, term of loan, day-bid, transfer of creditor’s rights, automatic bidding and information disclosure, have significant influences on the operating status of the platform, while the other variables such as registered capital, the number of employees and security mechanism have no obvious impact on the operating status of the platform. The results provide a reference for investors and regulators.

Keywords: Peer-to-Peer Lending, Problematic Platform, Risk Characteristics, Binary Logistic Regression

Cite this paper: Lu, C. and Zhang, L. (2018) Research on Risk Factors Identification of P2P Lending Platforms. American Journal of Industrial and Business Management, 8, 1344-1357. doi: 10.4236/ajibm.2018.85091.

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