TITLE:
Research on Risk Factors Identification of P2P Lending Platforms
AUTHORS:
Caimei Lu, Lu Zhang
KEYWORDS:
Peer-to-Peer Lending, Problematic Platform, Risk Characteristics, Binary Logistic Regression
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.8 No.5,
May
29,
2018
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.