Bank Creditworthiness Using Fuzzy Systems: A Comparison with a Classical Analysis Approach

Abstract

In the last decades, the problem of measuring credit risk has been the object of analysis by researchers. Financial organisations, banks, credit institutions, clients, suppliers, etc., need prediction of failure for firms in which they have any kind of interest. The most widely used methods are based on econometric analysis, which estimates the probability of clients’ insolvency (default). Often they do not show a satisfactory ability to discriminate between creditworthy and non-creditworthy clients. This situation is often due to the use of unrealistic assumptions of statistical hypotheses and to the complete lack of communication with the decision makers. The aim of this research is to overcome these limitations. In this paper a fuzzy logic approach, an alternative method, is used to provide a system able to evaluate bank creditworthiness. The financial data of 400 clients, offered by the Bank of Sardinia² and relating to small businesses are used to compare the econometric and fuzzy approaches³. The results are really interesting and show how the fuzzy system may offer better solutions to the problem of bank creditworthiness.

This research work is financed by Modena University (project “ Fuzzy logic prototype of a scoring for bank creditworthiness” 1999).