Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector

Jelena Lukić (), Mirjana Misita, Dragan D. Milanović, Ankica Borota-Tišma and Aleksandra Janković
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Jelena Lukić: Danube Insurance Company a.d.o, Makedonska 4, 11000 Belgrade, Serbia
Mirjana Misita: Faculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11000 Belgrade, Serbia
Dragan D. Milanović: Faculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11000 Belgrade, Serbia
Ankica Borota-Tišma: Belgrade Business and Arts Academy of Applied Studies, Kraljice Marije 73, 11000 Belgrade, Serbia
Aleksandra Janković: The Academy of Applied Technical Studies Belgrade, Katarine Ambrozić 3, 11000 Belgrade, Serbia

Mathematics, 2022, vol. 10, issue 18, 1-17

Abstract: The aim of the paper is to determine the risk level of a contract extension with the existing policyholders, which is further propagated to the business effectiveness and long-term sustainability of the company. The uncertainties in the relative importance of risk factors, their values, and risk levels are described by the linguistic forms, which are modeled by using the fuzzy sets theory. The evaluations of the relative importance of risk factors are stated as a fuzzy group decision-making problem. The weights of risk factors are obtained by using a fuzzy analytic hierarchy process. The determination of production rules for the assessment of the risk level is based on fuzzy IF-THAN rules. The verification of the model is performed by using real-life data originating from the insurance company which operates in the Republic of Serbia.

Keywords: risk level; fuzzy data; FAHP; fuzzy logic; production rules (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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