An Empirical Study Of The Impact Of Borrowing Description On P2P Internet Loans

Despite the continuous expansion of domestic P2 P network lending market,information asymmetry is still a serious problem faced by both sides of lending activities in the absence of a sound credit system.In order to solve this problem,it is necessary to further improve the information disclosed by the borrower.The borrowing description,as a unique information disclosure method in the P2 P network lending,plays an important role in promoting the success of the transaction between the lender and the borrower on the platform.This article uses th e data of online loan platform to make an empirical research on the relationship between loan description and the success rate of P2 P network borrowing.It is found that the borrowing description can help ease the information asymmetry between the borrower and the borrower,and promote the transaction success.This paper uses the loan data from the "Yilong Loan" P2 P network lending platform to segment words,remove stopwords,and TF-IDF statistical word frequency,analyze the representative vocabulary of all borrowing descriptions,and infer the main contents of the loan description text.This paper also extracts the core keywords of personal character,family situation,guarantee situation and gratitude and request by manually reading the sample,and uses the word vector model to calculate multiple phrases with similar semantics and constructs each keyword.The library quantifies the borrowing description text.The main conclusions of this paper are as follows: The length of the borrowing description,the description of personal morality,family status,and mortgage guarantee in the borrowing description help to increase the probability of the borrower's borrowing success.The description of the gratitude and request will reduce the loan success rate,and the borrowing People can increase their own probability of obtaining loans by providing textual descriptions of borrowings.On this basis,the paper also studied the impact of borrower's own conditions on the effect of borrowing description.The results show that borrowers with fewer assets provide longer loan descriptions or more effective information in borrowing descriptions.,can more effectively improve the loan success rate;and the borrower provides a longer description of the borrowing,and in the bor rowing description to mention their own character,the increase in the loan success rate and income level has nothing to do,but the lower income borrower mentioned Their own family situation and guarantee information will help increase the success rate of borrowing,but expressing gratitude and request will reduce the success rate of borrowing.Compared with the borrower's description of its own profitability,the lender on the platform prefers to believe that borrowing People describe their own assets.Fi nally,this paper puts forward three suggestions for strengthening investor tips and education,strengthening information review and supervision,and using big data to optimize the credit rating model.