Fuzzy approach based model of interrelated factors for financial industry client risk assessment

Risk management process has an important role in the financial industry client relations. Due to the nature of risks, evaluation of qualitative and quantitative factors should be performed and combined for taking appropriate decisions. Fuzzy logic can be used for such purpose. The vagueness of the subject matter is based on the fact that most of the risk factors can be interpreted differently taking into account other circumstances directly or indirectly impacting the risk assessment. This paper introduces the methods for consolidation of risk factors by means of fuzzy scores and interval valued fuzzy sets. Interrelations between different risk factors are analysed. Aggregation of risk levels using t-conorms is proposed for obtaining the risk scores that serve as the basis for decisions in client servicing. These self-explanatory assessment and aggregation methods can be used in different stages of the risk management process.