Using a fuzzy approach to support financial analysis in the corporate acquisition process

In the global market place, many companies have had to adapt their strategies to meet significant challenges. A strategy adopted by some companies has been international expansion via acquisitions. The need for expert knowledge to determine an appropriate company to acquire has been complicated by the sheer size of the global market place. The costs associated with this in relation to time and personnel have created the need for a computerised expert system to be developed. This paper endeavours to show how a proposed fuzzy based system can assist in the identification of a company for acquisition. The authors discuss the manipulation of the magnitude of fuzzy membership functions to communicate priorities within the system. The fuzzy system is designed to assist financial experts in identifying a suitable company for acquisition in the corporate acquisition process. This includes the deliberate weighting of certain inputs and results above others in the decision-making process. The system attempts to learn and simulate the human precedence given to particular financial statistics in company analysis. The system uses the magnitude of the fuzzy membership functions to reflect the human precedence given to each financial ratio. This enables a particular company’s strengths and weakness to be considered while concurrently considering their significance and relevance to the acquiring organisation. The system will enable a larger number of companies to be analysed in a more time and cost-effective manner. The development of this system is intended to illustrate that a fuzzy system can aid the financial experts of an acquiring organisation in the global acquisition process. q 2004 Elsevier Ltd. All rights reserved.