Analysis and prediction of P2P online lending platform - Based on binary logistic regression model

Abstract

This paper uses 17 indicators to analyze the critical factors that affect the P2P online lending platforms based on a binary logistic regression model. It shows that the problematic P2P online lending platforms are closely related to four indicators: the average interest rate, the top ten borrowers in terms of the repayment amount, the operating duration, and the top ten investors to receive the repayments. The accuracy of the regression model is up to 73% to predict whether the P2P network lending platform will be in a problem.