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Functions of the bonus-malus system in the motor third party liability insurance of motor vehicle owners

100%
Szymańska A.
Economic and Environmental Studies
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2018
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vol. 18
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issue 2
925-942
EN
The bonus-malus system is one of the stages of the ratemaking process in motor liability insurance. The purpose of the work is to discuss the role of the bonus-malus systems in the ratemaking and to present their functions. The article reviews the measures for assessment of the ratemaking function of the bonus-malus systems and attempts to investigate the impact of preventive and marketing functions. These functions fulfil their role under the condition that the insured party is aware of the functioning of the bonus-malus system. It has been hypothesized that the policyholders choosing the insurer do not know the bonus-malus system offered to them and that increasing the knowledge about the functioning of the system intensifies the impact of its preventive function. The study was conducted on the basis of an analysis of the insurance conditions offered by the insurers on the Polish market (GIT) and a questionnaire survey. Mathematical statistics methods have been used for the analysis. The results of the research confirm the hypothesis that the insured do not know the bonus-malus system while choosing an insurer. This is the effect of not passing enough information to the client. The results allow claiming that even offering brief information about the rules of the functioning of the bonus-malus system improves the awareness of policyholders and increases the impact of the preventive function, which makes it possible to positively verify the second research hypothesis.
PL
System bonus-malus jest jednym z etapów procesu taryfikacji w ubezpieczeniach komunikacyjnych OC. Celem pracy jest omówienie roli systemów bonus-malus w taryfikacji oraz przedstawienie ich funkcji. W artykule dokonano przeglądu miar oceny funkcji taryfikacyjnej systemów bonus-malus oraz podjęto próbę zbadania oddziaływania funkcji prewencyjnej i marketingowej. Funkcje te spełniają swoją rolę pod warunkiem, że ubezpieczający ma świadomość funkcjonowania systemu bonus-malus. Postawiono hipotezy, że ubezpieczający wybierając ubezpieczyciela nie znają oferowanego im systemu bonus-malus oraz, że zwiększenie wiedzy na temat funkcjonowania systemu potęguje oddziaływanie funkcji prewencyjnej. Badanie przeprowadzono na podstawie analizy ogólnych warunków ubezpieczenia (OWU) ubezpieczycieli na polskim rynku oraz badania kwestionariuszowego. Do analiz wykorzystano metody statystyki matematycznej. Wyniki badań potwierdzają postawioną hipotezę, że ubezpieczeni nie znają systemu bonus-malus wybierając ubezpieczyciela. Jest to efekt niedoinformowania klienta. Wyniki pozwalają twierdzić, że nawet krótka informacja o zasadach funkcjonowania systemów bonus-malus poprawia świadomość ubezpieczających oraz zwiększa oddziaływanie funkcji prewencyjnej, co pozwala pozytywnie zweryfikować drugą postawioną hipotezę badawczą.
2
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General linear model – an effective tool for analysis of claim severity in motor third party liability insurance

100%
Šoltés E., Zelinová S., Bilíková M.
Statistics in Transition new series
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2019
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vol. 20
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issue 4
13-31
EN
The paper focuses on the analysis of claim severity in motor third party liability insurance under the general linear model. The general linear model combines the analyses of variance and regression and makes it possible to measure the influence of categorical factors as well as the numerical explanatory variables on the target variable. In the paper, simple, main and interaction effects of relevant factors have been quantified using estimated regression coefficients and least squares means. Statistical inferences about least-squares means are essential in creating tariff classes and uncovering the impact of categorical factors, so the authors used the LSMEANS, CONTRAST and ESTIMATE statements in the GLM procedure of the Statistical Analysis Software (SAS). The study was based on a set of anonymised data of an insurance company operating in Slovakia; however, because each insurance company has its own portfolio subject to changes over time, the results of this research will not apply to all insurance companies. In this context, the authors feel that what is most valuable in their work, is the demonstration of practical applications that could be used by actuaries to estimate both the claim severity and the claim frequency, and, consequently, to determine net premiums for motor insurance (regardless of whether for motor third party liability insurance or casco insurance.
3
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Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis

88%
Reiff M., Šoltés E., Komara S., Šoltésová T., Zelinová S.
Equilibrium. Quarterly Journal of Economics and Economic Policy
|
2022
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vol. 17
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issue 3
803-842
EN
Research background: Using the marginal means and contrast analysis of the target variable, e.g., claim severity (CS), the actuary can perform an in-depth analysis of the portfolio and fully use the general linear models potential. These analyses are mainly used in natural sciences, medicine, and psychology, but so far, it has not been given adequate attention in the actuarial field. Purpose of the article: The article's primary purpose is to point out the possibilities of contrast analysis for the segmentation of policyholders and estimation of CS in motor third-party liability insurance. The article focuses on using contrast analysis to redefine individual relevant factors to ensure the segmentation of policyholders in terms of actuarial fairness and statistical correctness. The aim of the article is also to reveal the possibilities of using contrast analysis for adequate segmentation in case of interaction of factors and the subsequent estimation of CS. Methods: The article uses the general linear model and associated least squares means. Contrast analysis is being implemented through testing and estimating linear combinations of model parameters. Equations of estimable functions reveal how to interpret the results correctly. Findings & value added: The article shows that contrast analysis is a valuable tool for segmenting policyholders in motor insurance. The segmentation's validity is statistically verifiable and is well applicable to the main effects. Suppose the significance of cross effects is proved during segmentation. In that case, the actuary must take into account the risk that even if the partial segmentation factors are set adequately, statistically proven, this may not apply to the interaction of these factors. The article also provides a procedure for segmentation in case of interaction of factors and the procedure for estimation of the segment's CS. Empirical research has shown that CS is significantly influenced by weight, engine power, age and brand of the car, policyholder's age, and district. The pattern of age's influence on CS differs in different categories of car brands. The significantly highest CS was revealed in the youngest age category and the category of luxury car brands.
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