Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector
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 lev...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/18/3268 |
| _version_ | 1797485225345810432 |
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| author | Jelena Lukić Mirjana Misita Dragan D. Milanović Ankica Borota-Tišma Aleksandra Janković |
| author_facet | Jelena Lukić Mirjana Misita Dragan D. Milanović Ankica Borota-Tišma Aleksandra Janković |
| author_sort | Jelena Lukić |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T23:15:42Z |
| format | Article |
| id | doaj.art-8c104ce2b3934643ae49c06110263e68 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T23:15:42Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-8c104ce2b3934643ae49c06110263e682023-11-23T17:35:39ZengMDPI AGMathematics2227-73902022-09-011018326810.3390/math10183268Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance SectorJelena Lukić0Mirjana Misita1Dragan D. Milanović2Ankica Borota-Tišma3Aleksandra Janković4Danube Insurance Company a.d.o, Makedonska 4, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11000 Belgrade, SerbiaBelgrade Business and Arts Academy of Applied Studies, Kraljice Marije 73, 11000 Belgrade, SerbiaThe Academy of Applied Technical Studies Belgrade, Katarine Ambrozić 3, 11000 Belgrade, SerbiaThe 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.https://www.mdpi.com/2227-7390/10/18/3268risk levelfuzzy dataFAHPfuzzy logicproduction rules |
| spellingShingle | Jelena Lukić Mirjana Misita Dragan D. Milanović Ankica Borota-Tišma Aleksandra Janković Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector Mathematics risk level fuzzy data FAHP fuzzy logic production rules |
| title | Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector |
| title_full | Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector |
| title_fullStr | Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector |
| title_full_unstemmed | Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector |
| title_short | Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector |
| title_sort | determining the risk level in client analysis by applying fuzzy logic in insurance sector |
| topic | risk level fuzzy data FAHP fuzzy logic production rules |
| url | https://www.mdpi.com/2227-7390/10/18/3268 |
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