Bankruptcy prediction using case-based reasoning, neural networks, and discriminant analysis

摘要

Bankruptcy prediction is one of the major business classification problems. 1n this paper, we use three different techniques: (1) Multivariate discriminant analysis, (2) case-based forecasting, and (3) neural network to predict Korean bankrupt and nonbankrupt firms. The average hit ratios of three methods range from 81.5 to 83.8%. Neural network performs better than discriminant analysis and the case-based forecasting system.