Neural network models and the prediction of bank bankruptcy

Ky Tam

Omega, 1991, vol. 19, issue 5, 429-445

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.

Keywords: neural; networks; discriminant; analysis; bank; failures; prediction (search for similar items in EconPapers)
Date: 1991
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Citations: View citations in EconPapers (74)

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