Title: Peer to peer personal credit risk assessment based on survival model
Authors: Rui Liang - University of Chinese Academy of Sciences (China) [presenting]
Abstract: The credit risk problem of peer to peer online lending is increasingly prominent, and the default rate is a key parameter for quantifying credit risk. Therefore, it is particularly important to effectively calculate the methods and models for default events. Taking a large amount of transaction data as a sample, through survival analysis to determine the key factors affecting default and construct a loan default model, and use Cox regression to analyze when the borrower defaults and draw a loan survival curve. The empirical results show that education, credit rating, credit limit, number of loans, academic qualifications, real estate certification and default rate are negatively correlated, and positively correlated with loan survival time.