Developing a multicriteria decision support system for financial classification problems: The FINCLAS system

Several techniques and methods have been proposed in the past for the study of financial classification problems, including statistical analysis techniques, mathematical programming, multicriteria decision aid and artificial intelligence. The application of these methods in real world problems, where the decisions have to be taken in real time, calls upon a powerful and efficient tool for supporting practitioners financial analysts in applying these techniques. This paper presents the FINCLAS (FINancial CLASsification) decision support system for financial classification problems. The classification is achieved through the use of the UTADIS (UTilites Additives DIScriminantes) multicriteria decision aid method. The main parts of the FINCLAS system and the UTADIS method are discussed, and an application of the system is presented.