Credit Risk Analysis And Empirical Research On Capital-intensive Manufacturing Business

Financial crisis triggered by American subprime mortgage crisis gradually expandto the global, and uncertainty factors also increased, the global banking industry beginto pay more and more attention to credit risk management. In order to get more benefit,domestic commercial Banks need to increase the number of loan business in the rangeof risk control. The expansion of loans will also increase the risk of bank credit, themanagement cost and operation cost of Banks. As we all know, credit risk is the mainrisk faced by commercial banks, so the credit risk control has become the focus of bankrisk management.Manufacturing industry is not only the dominant part of China’s national economy,also the important support of the economic and social development, Because ofcentralized capital, most of manufacturing company are in times of financial strain.When money is scarce, large amounts of financing from Banks become inevitable.Nowadays the capitalization of capital-intensive manufacturing is an important share inthe commercial bank loans. The scale of manufacturing loan is larger, combined withthe global financial crisis expanding to real economy gradually (e.g., machinerymanufacturing, automobile manufacturing and other industries), the circumstance ofmanufacturing enterprise financing is becoming more serious.According to the operating characteristics and the financial characteristics ofmanufacturing, banks should set specific credit rating model in order to gain the largestprofit within risk control. At the same time, more manufacturing enterprises can alsoobtain financing opportunities to promote the development of the national economy.On the basis of theoretical knowledge of commercial bank credit business, weanalyze the operating and financial characteristics of manufacturing industry and selectdozens of manufacturing enterprises as samples and pick up theirs annual audit report tostudy. At first, financial indexs are roughly classified, and the relevant data arestandardized. Then we structure Logistic model using the main factors influencing thescore of the enterprise credit rating. At last, we associate use Logistic regression by thestatistical software SPSS to obtain the final model.