Abstract
A commercial bank credit risk assessment model based on fuzzy neural network has been established using the credit assessment index system established for commercial banks. This network is a 6 layered structure with 4 factor inputs and one output measuring the credit risk of commercial banks. The fuzzy rule layer has the capability of making necessary adjustments in accordance with specific conditions of problems. The operation of this model is much better than the totally black-box operation of a neural system. A substantiation analysis has been made with 167 observations as sample data; training results indicate that the network prediction has less error.
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Yao, P., Wu, C., Yao, M. (2009). Credit Risk Assessment Model of Commercial Banks Based on Fuzzy Neural Network. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_110
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DOI: https://doi.org/10.1007/978-3-642-01507-6_110
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