An Artificial Neural Network Approach for Credit Risk Management

Vincenzo Pacelli, Michele Azzollini

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DOI: 10.4236/jilsa.2011.32012                

Abstract

The objective of the research is to analyze the ability of the artificial neural network model developed to forecast the credit risk of a panel of Italian manufacturing companies. In a theoretical point of view, this paper introduces a litera-ture review on the application of artificial intelligence systems for credit risk management. In an empirical point of view, this research compares the architecture of the artificial neural network model developed in this research to an-other one, built for a research conducted in 2004 with a similar panel of companies, showing the differences between the two neural network models.

Keywords

Credit Risk, Forecasting, Artificial Neural Networks

Conflicts of Interest

The authors declare no conflicts of interest.

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