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Using Neural Network Rule Extraction for Credit-Risk Evaluation


Maria Teresinha Arns Steiner, Pedro Jos? Steiner Neto, Nei Yoshihiro Soma, Tamio Shimizu, J?lio Cesar Nievola


Vol. 6  No. 5  pp. 6-16


Credit-risk evaluation is a very important management science problem in the financial analysis area. Neural Networks have received a lot of attention because of their universal approximation property. They have a high prediction accuracy rate, but it is not easy to understand how they reach their decisions. In this paper, we present a real-life credit-risk data set and analyze it by using the NeuroRule extraction technique and the WEKA software. The results were considered very satisfactory.


Neural Networks, NeuroRule extraction technique, Credit-risk.