Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis

Marian Reiff, Erik Šoltés, Silvia Komara, Tatiana Šoltésová and Silvia Zelinová
Additional contact information
Marian Reiff: University of Economics, Slovakia
Erik Šoltés: University of Economics, Slovakia
Silvia Komara: University of Economics, Slovakia
Tatiana Šoltésová: University of Economics, Slovakia
Silvia Zelinová: University of Economics, Slovakia

Equilibrium. Quarterly Journal of Economics and Economic Policy, 2022, vol. 17, issue 3, 803-842

Abstract: 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.

Keywords: general linear model; claim severity; motor third party liability insurance; least squares means; contrast analysis (search for similar items in EconPapers)
JEL-codes: C12 C21 G22 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.24136/eq.2022.028 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pes:ierequ:v:17:y:2022:i:3:p:803-842

Access Statistics for this article

Equilibrium. Quarterly Journal of Economics and Economic Policy is currently edited by Adam P. Balcerzak

More articles in Equilibrium. Quarterly Journal of Economics and Economic Policy from Institute of Economic Research Contact information at EDIRC.
Bibliographic data for series maintained by Adam P. Balcerzak ( this e-mail address is bad, please contact ).