An Empirical Study On The Dynamics Of Enterprise Social Credit Ratina

Building a credit society is an important part of China’s socialist construction.It has been 22 years since the concept was put forward in 1999.Over the years,the government has promulgated many policies to promote the construction of a credit society.Enterprise credit information has been publicized year by year,and enterprise social credit infrastructure has been relatively complete.With the gradual rise of big data and artificial intelligence,it has become possible to provide enterprises with social credit ratings through them,and this method can reduce the possibility of human intervention in the rating process and the economic burden of enterprises,improve the rating efficiency and promote the construction of a credit society.This paper compares the existing rating standards and select the evaluation dimensions that can reflect the enterprise social credit status.Then combine the available data and the data that can be standardized to form a rating standard that can be used to evaluate the credit status of the enterprise.The analytic hierarchy process is used to empower the evaluation criteria,and the expert interview method is used to determine the degree of membership of the evaluation dimension.Design a rating reporting system and form a program that can be automated to run the rating standards.Grab the data required for rating through the Internet and combine the data reported by the enterprise to evaluate the enterprise’s credit,and finally verify the completeness and feasibility of the automated credit rating.Through the real-time update of big data,the enterprise’s data is continuously calculated and analyzed,and the latest rating results of the enterprise can be obtained,and then the rating results can be dynamically updated,which greatly improves the accuracy of the rating results and reduces the shortage of manual attention monitoring.Thereby verifying the completeness and feasibility of automated credit rating,and solving the problems of fairness in the process of enterprise social credit rating and fairness and accuracy of results.