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 . .

TY  - CONF
AU  - Lukić, Jelena
AU  - Misita, Mirjana
PY  - 2021
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4152
AB  - In this paper the fuzzy logic model is presented in order to determine if it is risky for the operation of an insurance company to extend the contract with existing insured persons on the basis of the cash flow and the number of their liquidated damage claims. The fuzzy logic process consists of two input variables (the amount and number of liquidated damage claims of one client) and one output variable, the risk. The risk assessment is determined by using fuzzy risk matrix. The main focus of this paper is the attempt to form a model to alarm possible critical operations of clients which would quantify the relative impact of possible risks which could endanger the insurance company operation.
PB  - Zaječar : Fakultet za menadžment
C3  - IV Međunarodna naučna konferencija Regionalni razvoj i prekogranična saradnja : zbornik radova
T1  - Fuzzy logic model as a predictor of potential critical operation of an insurance company
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4152
ER  - 

@conference{
author = "Lukić, Jelena and Misita, Mirjana",
year = "2021",
abstract = "In this paper the fuzzy logic model is presented in order to determine if it is risky for the operation of an insurance company to extend the contract with existing insured persons on the basis of the cash flow and the number of their liquidated damage claims. The fuzzy logic process consists of two input variables (the amount and number of liquidated damage claims of one client) and one output variable, the risk. The risk assessment is determined by using fuzzy risk matrix. The main focus of this paper is the attempt to form a model to alarm possible critical operations of clients which would quantify the relative impact of possible risks which could endanger the insurance company operation.",
publisher = "Zaječar : Fakultet za menadžment",
journal = "IV Međunarodna naučna konferencija Regionalni razvoj i prekogranična saradnja : zbornik radova",
title = "Fuzzy logic model as a predictor of potential critical operation of an insurance company",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4152"
}

Lukić, J.,& Misita, M.. (2021). Fuzzy logic model as a predictor of potential critical operation of an insurance company. in IV Međunarodna naučna konferencija Regionalni razvoj i prekogranična saradnja : zbornik radova
Zaječar : Fakultet za menadžment..
https://hdl.handle.net/21.15107/rcub_machinery_4152

Lukić J, Misita M. Fuzzy logic model as a predictor of potential critical operation of an insurance company. in IV Međunarodna naučna konferencija Regionalni razvoj i prekogranična saradnja : zbornik radova. 2021;.
https://hdl.handle.net/21.15107/rcub_machinery_4152 .

Lukić, Jelena, Misita, Mirjana, "Fuzzy logic model as a predictor of potential critical operation of an insurance company" in IV Međunarodna naučna konferencija Regionalni razvoj i prekogranična saradnja : zbornik radova (2021),
https://hdl.handle.net/21.15107/rcub_machinery_4152 .