Formalizing Financial Decision-Making Process: Classical or Fuzzy Approach?

The importance and the complexity of financial decision-making process are the reasons why so much work has been invested over the years in formulating methods that would realistically treat this issue. The requirement for adequate and effective methods and procedures is justified by very high complexity of the real situation, making it more difficult to fit into restrictive hypotheses on which mathematical models are often based. Financial decision-making represents a field where decision support systems can be successfully implemented, especially knowledge based decision support systems and intelligent decision support systems. This paper presents the most important features of two decision support systems, a classical system and a system based on fuzzy logics. The performances of these two models are compared and the advantages achieved through the introduction of fuzzy concepts into the classical decision support systems determined.