Neural Networks and Expert Systems: New Horizons in Business Finance Applications

Abstract

Neural networks and expert systems are two major branches of artificial intelligence (AI). Their emergence has created the potential for a new generation of computer‐based applications in the area of financial decision making. Both systems are used by financial institutions and corporations for a variety of new applications from credit scoring to bond rating to detection of credit card fraud. While both systems belong to the applied field of artificial intelligence, there are many differences between them which differentiate their potential capabilities in the field of business. Presents an analysis of both neural networks and expert systems applications in terms of their capabilities and weaknesses. Uses examples of financial applications of expert systems and neural networks to provide a unified context for the comparison.

Neuro-Based Artificial Intelligence Model for Loan Decisions

“…The result will be compared to a cutoff point. If the score exceeds the cutoff point, the application is approved; if not, the application is rejected (Tafti and Nikbakht, 1993). However, the credit scoring cannot totally remove the human factor.…”

“…Traditional judgmental methods and conventional statistical techniques are used in the approval of loan worthiness (Tafti and Nikbakht, 1993). Traditional statistical models such as discriminant analysis and logistic regression usually assume multivariate normality and homoscedastic and these assumptions are often violated in the real world banking data (Giang, 2005;Huang et al, 2004).…”

“…The application software is self-adjustable for any user and it only requires a representative training set against a standard reference. Then, the ANNs self-adaptive nature will take over (Pollard, 1990) • Most financial decisions have incomplete information, so neural networks have more applications for such data than do expert systems and advanced statistical methods (Tafti and Nikbakht, 1993) The advantages of using ANN are as follows:…”

Decision support through knowledge management: the role of the artificial intelligence

“…Of particular interest within the framework of technology's role in KM is the role of AI in its various forms. AI has received considerable attention during the last two decades and has been widely applied in many business areas (Mentzer and Gandhi, 1993;Tafti and Nikbakht, 1993;Liebowitz, 1997; Zhang et al, …”

Operational Tools in the Management of Financial Risks

“…Despite these advantages and the initial enthusiasm on the expert systems technology, their implementation revealed several limitations. The major drawbacks in the implementation of expert systems in the study of financial decision problems concern the significant amount of time which is needed to elicit precise knowledge from experts, the accuracy needed during the modeling of the decision variables, and their inflexibility to the changes of the decision environment (Tafti and Nikbakht, 1993;Klein and Methlie, 1995).…”