Credit Risk Measurement Of P2P Network Loan Based On Logistic Regression

With the development of online lending, Alipay invents the new thing of Yu’e bao and the technology of third-party payment is developing in2013which is called the year of the internet finance. A variety of banks begin to pay constant attention to online services. Until Nov,2013, the number of P2P online lending financial firm is more than500and the number is still growing in general. However, risk of management becomes a new problem which is one of the most important issues.There is an example of P2P online lending as the research of internet finance. P2P online lending gives an introduction in detail and tries the ways in credit risk measure that take measure of credit risk of P2P online lending. This paper introduces the way of credit risk management and then gives the results of logistic regression that adapts to P2P online lending platform.Owing to the short development of P2P online lending and insufficiency of statistics, the research makes use of the lending statistics of Prosper firm in USA. P2P online lending’s credit risk analysis estimates by the individual and makes great connection to the individual credit. The way is different from estimating by financial index analysis. Credit score, debt to income rate, borrower rate, term etc. are used to estimate credit risk and luckily, they all pass the significance testing to get the restively accuracy in the prediction.Empirical analysis is based on statistics in foreign countries, but the methods can be used in many different aspects. It is possible that logistic regression can be applied to the credit risk measure in P2P online lending in theory. And we can benefit from it. It is the first search of credit risk measure in internet finance, and maybe we will choose different variable in China. However, it still gives us positive effects.