Abstract
Starting from the perspective of borrower credit risk in online peer-to-peer lending, the paper first collected the relevant borrowers’ data sample from Paipai Lending, a well-known online P2P (peer-to-peer) lending platform in China. By using Information Gain technique, the paper screened out the ultimate indicator variables from the original sample and then constructed a credit risk evaluation model of Chinese Online P2P Lending borrower based on Logistic Regression. Finally, the paper transferred the groups of testing sample set into the model to test the model accuracy. By comparing the model’s results with the relevant actual defaults, the model is proved to have good explanatory power for the credit risk of borrower.
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