Neuro-discriminate model for the forecasting of changes of companies financial standings on the basis of self-organizing maps

Abstract

This article presents the way how creditor can predict the trends of debtors financial standing. We propose the model for forecasting changes of financial standings. Model is based on the Self-organizing maps as a tool for prediction, grouping and visualization of large amount of data. Inputs for training of SOM are financial ratios calculated according any discriminate bankruptcy model. Supervised neural network lets automatically increase accuracy of performance via changing of weights of ratios. © Springer-Verlag Berlin Heidelberg 2007.