MANAGERIAL APPLICATIONS OF NEURAL NETWORKS - THE CASE OF BANK FAILURE PREDICTIONS

• 成果类型: Article
• 署名作者: TAM, KY; KIANG, MY
• 署名单位: Arizona State University; Arizona State University-Tempe
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.38.7.926
• 发表日期: 1992
• 页码: 926-947
• 关键词: Neural networks; Artificial intelligence; discriminant analysis; BANK FAILURE PREDICTIONS

摘要

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.