Study On The Credit Risk Measurement Of Small And Medium-Sized Enterprises In China

The booming development of Small and Medium-Sized Enterprises(SME) has the stronger economic externality, it not only is the important power of furthering the economic growth, but also functions at many aspects, such as adjusting the economic structure, extending the society employment…etc. However, the financing of SME in China has been facing "Macmillan Gap". Whether the financing trend of domestic SME, or the financing structure of foreign SME indicates: Under the restriction of the actual environment, there is only one direction to solve thefinancing puzzledom of SME——extending the indirect financing system, increasingthe debt financing derived from the bank. So it becomes the key part of solving this puzzledom to strengthen the credit risk evaluation of SME. Along with the undeveloped excellent and big corporation gradual decreasing and the credit market subdividing, it must be a problem more attention should be paid to by domestic banks to study the credit risk measurement of SME in the future.The paper's topic is how to build up the credit risk measurement model whichfits for China, and its study object is the special group——SME. Firstly, basing onthe review and comparison to the correlative methods and models of credit risk measurement, the paper pointed out that the most feasible method of domestic SME's credit risk measurement is the Multivariate Statistical Analysis at present. Secondly, according to the finance data and non- finance data of 113 SME samples in 2002 and 2003, the paper carried on the "Independent-samples T Test" and "Principal Components Analysis" to the first 20 indexes, and get an simplified index system only including 10 indexes. Thirdly, the paper inputted the index data, and empirical research into the Multivariate Linear Discriminant Model (MLDM) and Logit Model (LM). The Conclusions showed: the MLDM is apt to make all the 10 indexes enter the final discriminant function, and the total classification accuracy rate attains 76.1% in the last two year before default, 81.4% in the last one year; the LM inclined to select the "Backward: Conditional" method and the model when Logit analysiscarried on the 4th step, the total classification accuracy rate attains 78.8% in the last two year before default, 85.8% in the last one year; although the total forecasting accuracy rate of LM is higher than the MLDM, it is worse than the MLDM on the pivotal second misclassification rate, easily judges a default enterprise to be normal, neglecting its potential credit risk. Finally, on the foundation of the model results, the paper analyzed the credit risk characteristics of domestic SME, and compared with the results of Moody's RiskCalc? default model at the same time. Using this default model Moody Company studied the private companies' credit risk of some more developed countries, such as the United States, Australia etc. The comparative conclusion revealed that, removing the non-finance factor, the capital structure and the profitability are the first two factors in turn, which are remarkable, steady, and able to embody the credit risk characteristics of domestic SME. To sum up, this result is basically similar to the average result of the contrastive countries.