Research On Credit Evaluation Of Internet Financial Enterprises Based On GA-BP Neural Network

Internet finance has filled the gap between traditional financial services and social investment and financing demand,many problems of whichhave been exposed.The most serious problem is that some internet finance companies are wandering on the “no threshold,no standard,no supervision” verge and free to enter and exit the internet financial market,which will damage the interest of investors and harm the order of the internet financial market if something trouble them.The purpose of the paper is to provide scientific and reasonable suggestion to the credit access standards for enterprises to carry out internet finance business,the selection standards for consumer internet financial products,the reference standards for enterprises to enhance their internet finance business capabilities and the regulatory standards of relevant regulatory agencies and departments by evaluating the credit of internet finance companies.From the perspective of credit of internet financial enterprises,this paper introduces internet financial capability indicators into the credit evaluation system of internet financial enterprises,which uses the SEM model to construct an evaluation index system reflecting the credit rating of Internet financial enterprises with 14 indicators.Based on this,the GA-BP neural network model was applied to the credit evaluation of Internet financial enterprises,and a predictive evaluation model based on BP neural network and GA-BP neural network was constructed.And then,this paper uses 171 sets of sample data from 57 listed Internet financial companies to carry out training and simulation,9 sets data of which were selected as test samples to analyze and predict enterprises credit.The experimentverification shows that the BP neural network can effectively evaluate the credit of internet financial enterprises;the GA-BP neural networkhas better prediction effect and training effect than the original BP neural network,which can more effectively evaluate the credit of Internet financial enterprises.