Credit risk management has been one of the most serious problems for banks and other financial institutions. With the continuous improvement of the economic system reform of our country, the establishment of market mechanism and perfect, the rapid development of capital markets and the banking sector, the existing credit evaluation system and method have been unable to keep up with the needs of the reform and development of economy in our country. In this paper, a model based on fuzzy integral support vector machine (SVM) is established, which takes into account the importance of the output of the sub support vector machine (SVM). Then the The empirical is analysis is carried out, and the results show that the method has higher classification accuracy, and verifies the feasibility and effectiveness of the method, and provides a theoretical basis for the bank to establish more reliable evaluation system.
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