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Neural network models and the prediction of bank bankruptcy

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  • Tam, KY

Abstract

The number of failed banks has reached a high unparalleled since the great Depression. Research in developing predictive models for bank failures is therefore warranted and desirable in this turbulent period. In this paper, we present a neural network approach to bank failures prediction and compare its performance with existing models. Empirical results show that among alternative models, neural networks is a competitive instrument for evaluating the financial condition of a bank. The study concludes with a discussion on the potential and limitations of neural networks as a general modelling tool for financial applications.

Suggested Citation

  • Tam, KY, 1991. "Neural network models and the prediction of bank bankruptcy," Omega, Elsevier, vol. 19(5), pages 429-445.
    • Handle: RePEc:eee:jomega:v:19:y:1991:i:5:p:429-445
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