Research On P2P Loan Pricing Based On Data Mining And Simulation

As the hottest financial form of Internet finance,P2 P loans have been facing rapid growth in the past few years and are also faced with problems such as difficulty in profitability and high cost of obtaining customers.The current status of the P2 P platform led by Lending Club is rather bleak,and its profitability has been questioned.P2 P,as a supplement to traditional bank credit,can help meet the growing demand for private lending when the current domestic credit mechanism is not yet fully mature.It plays an important role in promoting economic development.This article discusses how to solve the problem of improving the profitability of P2 P platforms.The improvement of profitability of P2 P loans can be achieved through the following methods: 1.Larger operating income can be divided into two subdividing goals: expanding transaction volume and increasing fee rate.Second,control of risk,that is,overdue rate,bad debt rate.Firstly,this paper discusses how to improve the return on investment of platform investors,and innovatively proposes to use IRR internal rate of return as the basis for making loans.An IRR-CHAID decision tree model was constructed to identify the variables that have the greatest impact on the profitability of each loan loan investment,and to prove that IRR can be used as the investor's investment basis to obtain a higher income than the current Lending Club credit rating.Regarding how to control overdue rates and bad debt ratios,this paper comprehensively considers the highly unbalanced and erroneous cost gaps of sample data,and abandons traditional traditional iso-performance Linebased loan cutting point selection methods to utilize True Rate and Cost.-sensitive unweighted line At the same time,Monte Carlo simulation was introduced.This chapter guides the lending club loan data with precision by minimizing overall misclassification costs.Finally,based on the determination of the precise cutting point selection method,this article uses Monte Carlo simulation to weaken the influence of the uncertainty of the ROC curve on the loan pricing,and evaluates the pricing level of each credit rating at the current stage of Lending Club.At present,Lending Club has a high price for users with excellent credit,and a low price for users with poor credit,and puts forward reasonable pricing advice.