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Managerial Applications of Neural Networks: The Case of Bank Failure Predictions

Authors Tam, Kar Yan View this author's profile
Kiang, Melody Y.
Issue Date 1992
Source Management Science , v. 38, (7), 1992, p. 926-947
Summary This Paper introduces a neural-net approach to perform discriminant analysis in business research. A neural net represents a nonlinear discriminant function as a pattern of connections between its processing units. Using bank default data, the neural-net approach is compared with linear classifier, logistic regression, kNN, and ID3. Empirical results show that neural nets is a promising method of evaluating bank conditions in terms of predictive accuracy, adaptability, and robustness. Limitations of using neural nets as a general modeling tool are also discussed.
ISSN 0025-1909
Language English
Format Article
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