Copyright @ IFAC Modeling and Control of Economic Systems. Klagenfurt. Austria. 2001 ELSEVIER IFAC PUBLICATIONS www.elsevier.com/locatelifac COMPARA TIVE ANALYSIS OF RESULTS OBTAINED BY UTILIZING EXPERT SYSTEMS AND NEURAL NETWORKS IN FINANCIAL ANALYSIS Adrian Kapczynski, Tomasz Zurek Silesian University of Technology, Faculty of Organization and Management Abstract: In the context of examining the financial situation of chosen companies using Du Pont analysis in presented paper a comparative analysis of results obtained while applying solutions based on Artificial Intelligence is provided. Both main tools, neural networks and expert systems, are used to examine financial aspects of the given companies. The results obtained from both tools make it possible to provide advantages and disadvantages of both tools and finally recommendations of using them under specified conditions. Copyright © 200} }FAC Keywords: Expert system, neural network, finance 1. INTRODUCTION Economic development occurring in the contemporary world causes many changes in the organization and management of an enterprise. Nowadays a key factor of competitive advantage is information - identification of its source, acquisition. storage, processing and interpretation. In order to exist in a tough, highly competitive environment the company is obliged to perfectly identify and understand its strengths and weaknesses while having information concerning the weak points of its competitors and their behaviour. Based on that the role of a financial expert in a company is still growing (Michalski, 1999). Now, the basic goal of an enterprise may be another financial goal. The attention of the management is focused primarily on maximizing the value of a company. Achieving the mentioned goal guarantees profits for the owners of capital, the survival of the company in a highly competitive environment and also provides advantages connected with satisfying demand generated by customers. 389 Having existing restrictions (political, economical, lawful) in mind, maximizing the value of an enterprise is possible only by practising a policy of steady development of all aspects of running the business, leading to an optimization of all key financial coefficients, not only the return on sales. As stated above, financial analysis becomes a matter of utmost importance and remunerativeness a part of it (Czekaj and Dresler, 1997). One of the most effective is Du Pont analysis, which shows the influence of a company's total assets structure, assets turnover on return referring to sale, total assets and equity (Sierpinska and Jachna, 1997). Present-day advanced Information Technology creates tools which can to a certain degree replace the human expert (Michalski, 2000). Among these tools the wo main groups are expert systems and neural networks. Both of them function in a different way; each of them has its own advantages and drawbacks. Expert systems require providing detailed knowledge (in the form of rules and facts), which is then used by the inference engine to draw conclusions. On the other hand, neural networks learn through examples, so they usually require big amounts of data to learn in order to be properly trained (Tadeusiewicz, 1993). Expert systems have small capabilities for dealing with