Empirical Analysis of Credit Risk Measure Using Fuzzy Adaptive Neural-Networks: For Small and Medium-Sized Enterprises

Abstract

Measuring credit risks of small and medium-sized enterprises should take a series of unique characteristics into consideration. Firstly, non-financial conditions should be combined to produce more accurate evaluation results. Secondly, to overcome the vague of non-financial and sharp boundaries of financial conditions,fuzzy approaches and a nonlinear classifier based on fuzzy adaptive neuralnetwork(hereinafter referred to as “FAN”) were introduced. A sample family of 65 firms was collected to test the performance of the above classifier, among which 29 firms were default and 36 firms were good. The result was shown as ROC curves. To compare the performance of the model, the empirical results of another 4 classifiers were shown at the same figures and tables. The results showed that FAN has the best performance and can effectively distinguish the good and default firms.