Study On C2C E-commerce Credit Evaluation Model

In recent years, with the rapid development of economy in our country, the transaction scale of e-commerce also keeps increasing. Because of the virtuality and anonymity of e-commerce, the lack of network credit is increasingly serious and has seriously hindered the development of e-commerce in our country. Therefore, it is high time to actively explore and establish a suitable e-commerce credit evaluation model. In this context, this paper analyzes the existing problems of the current credit evaluation system and establishes a credit evaluation model.The main research work of this paper includes:(1) Taking "taobao" as the main research object, studies the C2C e-commerce credit evaluation system in our country. Makes improvements on the factors such as seller information, commodity information, buyers’evaluation, punishment and so on, and establishes a relatively comprehensive evaluation index system of credit.(2) Establishes the BP neural network with Matlab software, then according to the credit evaluation index system established above, collects reliable data and uses it as training samples and test samples of the BP neural network. Training the BP neural network, we can get the weight of each index, and an improved credit evaluation model is set up. At the end, simulates the new credit evaluation model, and tests its effectiveness.This e-commerce credit evaluation model established in this paper, considering the factors such as the deposit amount of the seller and the punishment, it can reflect the seller’s solvency and restrict some dishonest behaviors, and the BP neural network method can reduce the influence of subjective factors, so this model can predict the seller’s credit rating more comprehensively and reasonably.