A Method for Dynamically Assessing Credit Risk of Internet Financial Service Platform

Abstract

This paper comprehensively uses the fuzzy cognitive graph method and entropy weight method to dynamically assess the credit risk of Internet financial service platforms. First, a platform credit risk indicator system was constructed. Secondly, the genetic algorithm is used to learn the fuzzy cognitive graph weight matrix. Then, the fuzzy cognitive graph inference mechanism is used to predict the dynamic changes of the credit risk index and the stable state finally achieved. Finally, combined with the index weights calculated by the entropy weight method, the credit risks of the three online lending platforms are dynamically assessed. This paper realizes the dynamic assessment and prediction of Internet financial service platforms, and provides theoretical support for the credit risk of government supervision platforms.