A Data Mining Approach for Risk Assessment in Car Insurance: Evidence from Montenegro

Ljiljana Kašćelan, Vladimir Kašćelan and Milijana Novović-Burić
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Ljiljana Kašćelan: Faculty of Economics, University of Montenegro, Podgorica, Montenegro
Vladimir Kašćelan: Faculty of Economics, University of Montenegro, Podgorica, Montenegro
Milijana Novović-Burić: Faculty of Economics, University of Montenegro, Podgorica, Montenegro

International Journal of Business Intelligence Research (IJBIR), 2014, vol. 5, issue 3, 11-28

Abstract: This paper has proposed a data mining approach for risk assessment in car insurance. Standard methods imply classification of policies to great number of tariff classes and assessment of risk on basis of them. With application of data mining techniques, it is possible to get functional dependencies between the level of risk and risk factors as well as better results in predictions. On the case study data it has been proved that data mining techniques can, with better accuracy than the standard methods, predict claim sizes and occurrence of claims, and this represents the basis for calculation of net risk premium and risk classification. This paper, also, discusses advantages of data mining methods compared to standard methods for risk assessment in car insurance, as well as the specificities of the obtained results due to small insurance market, such is the one in Montenegro.

Date: 2014
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