|CV: Curriculum Vitae from Carlos Serrano Cinca, professor in Accounting and Finance at the University of Zaragoza (Spain)|
Serrano Cinca, C. (1996): "Self Organizing Neural Networks for Financial Diagnosis", Decision Support Systems, 1996, Vol 17, julio, pp. 227-238, Elsevier Science
A complete Decision Support System (DSS) for financial diagnosis based on Self Organizing Feature Maps (SOFM) is described. This is a neural network model which, on the basis of the information contained in a multidimensional space in the case exposed, financial ratios generates a space of lesser dimensions. In this way, similar input patterns in the case exposed, companies are represented close to one another on a map. The neural network has been complemented and compared with multivariate statistical models such as Linear Discriminant Analysis (LDA), as well as with neural models such as the Multilayer Perceptron (MLP). As the principal advantage, this DSS provides a complete analysis which goes beyond that of the traditional models based on the construction of a solvency indicator also known as Z score, without renouncing simplicity for the final decision maker.
Self organizing feature maps; Neural networks; Kohonen maps; Financial diagnosis; Bankruptcy prediction