Research On SMEs Credit Rating Evaluation Based On Hierarchical Prediction Correction Method

In China,SMEs play an important role in economic and social development and improving people's livelihood.However,as the key growth point of regional economic development,SMEs have long faced serious financing difficulties.Although Chinese government has introduced a series of favorable policies that help SMEs ease the financing pressure in the macro level.But the root of the problem has not been resolved.The essential reason is that the credit evaluation system currently adopted by commercial banks is not suitable for SMEs.Existing credit rating methods are mainly focused on serving the large enterprises,and lack of specificity for SMEs.In addition,these methods only consider the development status of enterprises on a certain time section,ignored the essence of corporate credit is a measure of enterprise's future repayment ability.The credit status of enterprises is affected by the dynamics of time and space.Therefore,this paper has conducted empirical research on SMEs manufacturing enterprises in Jiangsu and Zhejiang regions,and explored a set of credit evaluation system that matches the characteristics of SMEs in China.First,this paper determines the construction principles of the evaluation index system.Under the guidance of this principle,an evaluation index system consisting of 15 financial indicators and 10 non-financial indicators was determined.Second,this paper attempts to introduce temporal dynamic network into the objective weighting method,which simplifies the solution of time-series weights,and gives examples to verify the effectiveness of the improved SAM model.Third,in order to consider the stability of the subjective weighting method and the objectivity of the objective weighting method,this paper adopts the objectively modified subjective cross-weighting method and substitutes it into the enterprise static credit evaluation model with the fuzzy comprehensive evaluation method as the framework.Finally,the obtained enterprise static credit evaluation value is used to predict the enterprises status in the year of repayment,and using the hierarchical prediction revision method to modify the prediction result,thus the current credit rating of the enterprise is determined.In the empirical part,65 SMEs in Jiangsu and Zhejiang were selected,using their data from 2014 to 2018 to determine the current credit status,and using the ST status of the enterprise to judge the validity of the model.At last,the credit status of these companies are analyzed and explained,and suggestions for improvement are given.