The Credit Assessment Model And Application For Middle And Small Business

Along with the establishment and development of socialist market economy system, the middle and small business in China has gradually become an important power to push the development of national economy and maintain social stability. But the middle and small business in China is still located in the "weak" status in Chinese economy system, and its development still faces many problems, among which, the financing difficulty is the universal and principal factor to constrain the development of middle and small business. Through analyzing the relevant problems concerning the financing of middle and small business, this paper regards credit assessment as the critical factor to solve the difficult in financing. Based on this, by the discuss on present situation of credit assessment both in and outside of our country, and by the analysis on existing credit assessment models, aiming at the defect of existing credit assessment models, utilizing analytic hierarchy process, principal component analysis, and BP neural network, the paper establishes credit assessment models for middle and small business within an industry and that among industries respectively.Firstly, through the comparison between the financing patterns of middle and small business in domestic and overseas, and via the economic analysis on the reasons to form the gap in the financing of middle and small business in our country, the paper demonstrates the crucial action of credit assessment on middle and small business to solve its difficulty in financing, and also addresses scientifically the significance of credit assessment on middle and small business.Secondly, based on the analysis on the characteristic of Chinese middle and small business, this paper sets up a credit assessment indicator system in three levels for middle and small business within an industry, and separately lists its financial standing indicator system. After investigating 20 middle and small businesses in agricultural industry in Anhui Province, the paper takes agricultural industry as an example, screens variables using principal component analysis to simplify the original indicator system, and amends the calculating formula of financial standing indicator system further utilizing the Logistic function. After then, it calculates the weight of indicators in each level by analytic hierarchy process, and sets up credit assessment model for middle and small business within an industry. At the same time, it carries out the further discussion on models according to the loaning goal of commercial bank. On the basis of confirming the critical probability for bank to loan, taking advantage of credit assessment model for middle and small business, the paper sets up decision-making model for bank to loan, and carries on a demonstrated analysis by inputting the data from Hefei Fengle Seed Co. LTD in first half year of 2005. Afterwards, aiming at the information construction of the credit of middle and small business, it puts forward some discussion and assumption to the development of credit assessment system of middle and small business based on the established mathematical models, analyzes the function of the system and divides it into some subsystems, thus designs the general structure and functional module for the system preliminarily.In view of the significance of the credit construction for middle and small business, after establishing individual credit assessment micro-model for middle and small business, it also should have macro knowledge to the credit standing of middle and small business. Therefore, this paper sets up credit assessment model for middle and small business among industries using BP neural network. It firstly knows about the difference between the industry and the individual enterprise, so as to build an assessment indicator system over again. Then utilizes the investigating data from 120 middle and small businesses in different industries in Anhui Province, divides them into training sample and testing sample, discusses the construction of BP neural network, decides the algorithm of BP neural network, so as to set up the credit assessment model among industries based on BP neural network. After carrying on a demonstrated analysis by inputting the data from some sub-industries in agricultural industry and industrial industry in the year of 2003, and analyzing the simulation result from the aspects of general credit standing in an industry and the credit difference between agricultural and industrial industry, it points out the reasons to result in the lowness of general credit level and the large gap between agricultural and industrial industry, and puts forward the policy to increase general credit level and the suggestion aiming at the credit construction in agricultural industry.