From Financial Information to Strategic Groups: A Self- Organizing Neural Network Approach

Abstract

This paper sets out to determine what is the strategic positioning of the Spanish Savings Banks, on the basis of published financial information. Its starting point is the concept of the strategic group, regularly employed in Business Management to explain the relationships between firms within the same sector, but with peculiarity that the strategic group is identified using financial information. In this way, we obtain groups of firms that have similar cost structures, levels of profitability, borrowing, etc. and, in general, that follow a similar financial strategy. As the exploratory data analysis technique to obtain these strategic groups, we propose combining a non-supervised neural network, the Self-Organizing Feature Maps (SOFM) with Cluster Analysis (CA). This methodology allows us to visualize the similarities between firms in an intuitive manner. The application of the proposed methodology to the financial information published by the totality of the Spanish Savings Bank allows us to identify the existence of profound regional differences in this important sector of the Spanish financial system. Thereafter, a bivariate study of the financial ratios has allowed us to specify what are the aspects that distinguish the Savings Banks which operate in the different Spanish regions.

JEL Classification: G21