A hybrid SOM-Altman model for bankruptcy prediction

Abstract

This article analyzes the problems of business bankruptcy, and the methods for bankruptcy prediction. This study proposed to join two models, one is the multi-discriminate Z-Score created by Altman, and the other is the Self-organizing maps. We proposed to generate self-organizing maps based on the financial data of public companies that are included in the NASDAQ list. These maps were used for bankruptcy prediction as well as creating classification of financial risk for Lithuanian companies. Comparing the weak results of prediction we accelerated by changing of ratios weights of the Altman Z-Score model. In this way, it can fit to conditions of the Lithuanian conjuncture. Based on the original ratio weights in Altman's Z-Score the results predicting Lithuanian bankruptcy were weak. The weights of Altman's Z-Score model were changed to fit the Lithuanian economic circumstance. © Springer-Verlag Berlin Heidelberg 2006.