Risk evaluation for C2C E-commerce via an improved credit counting method

Abstract

E-commerce has become a popular way for shopping, especially during the Covid-19 pandemic. The key of the E-commerce is the credit evaluation, for instance the client to client (C2C) mode E-commerce. In this paper, an improved credit scoring method is proposed. The improved credit scoring method uses the interval distribution of commodity prices to add points for successful transactions and deduct points for failed transactions by using credit grade deduction coefficients and credit level, which can solve credit hype and periodic deception. Through the analysis of credit risk, a risk calculation method for online transactions is designed by using the improved credit scoring model. The proposed risk calculation method can evaluate the risk of current transactions based on historical transaction conditions and current transaction prices. The simulated experiments show that the improved credit scoring method has better anti-credit speculation and periodic deception effects, and the risk assessment method is more accurate and effective for risk analysis and prediction in C2C E-commerce transactions.