Janković, Aleksandra

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  • Janković, Aleksandra (1)
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Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector

Lukić, Jelena; Misita, Mirjana; Milanović, Dragan; Borota-Tišma, Ankica; Janković, Aleksandra

(MDPI, 2022) 

TY  - JOUR
AU  - Lukić, Jelena
AU  - Misita, Mirjana
AU  - Milanović, Dragan
AU  - Borota-Tišma, Ankica
AU  - Janković, Aleksandra
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4062
AB  - 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.
PB  - MDPI
T2  - Mathematics
T1  - Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector
DO  - 10.3390/math10183268
ER  - 
@article{
author = "Lukić, Jelena and Misita, Mirjana and Milanović, Dragan and Borota-Tišma, Ankica and Janković, Aleksandra",
year = "2022",
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.",
publisher = "MDPI",
journal = "Mathematics",
title = "Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector",
doi = "10.3390/math10183268"
}
Lukić, J., Misita, M., Milanović, D., Borota-Tišma, A.,& Janković, A.. (2022). Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector. in Mathematics
MDPI..
https://doi.org/10.3390/math10183268
Lukić J, Misita M, Milanović D, Borota-Tišma A, Janković A. Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector. in Mathematics. 2022;.
doi:10.3390/math10183268 .
Lukić, Jelena, Misita, Mirjana, Milanović, Dragan, Borota-Tišma, Ankica, Janković, Aleksandra, "Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector" in Mathematics (2022),
https://doi.org/10.3390/math10183268 . .
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