Commercial Bank Credit Risk Assessment Method based on Improved SVM

摘要

Credit risk evaluation is the basic work of commercial bank's credit risk management, which goal is to analyze the credit risk of the bank. Support vector machines ensemble has been proposed to improve classification performance recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. A SVM ensemble method based on fuzzy integral is presented in this paper to deal with this problem. This method aggregates the outputs of separate component SVMs which is given different weights by means of fuzzy integral. The experiment results show that the result of fuzzy integral support vector machines is satisfactory.