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The a priori risk classification with spatial autocorrelation in automobile insurance

Author

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  • Kamil Gala

    (Ubezpieczeniowy Fundusz Gwarancyjny)

Abstract

The subject of this paper is to describe a priori risk classification models in automobile insurance which take into consideration the address of the insured. The extension of the generalized linear model with the multi-level factor to account for the correlation between the levels is presented. The analysis of empirical data from the Polish insurance indicates both significant spatial heterogeneity and spatial autocorrelation. Moreover, the inclusion of spatial variables in the risk classification models can improve their accuracy and effectiveness.

Suggested Citation

  • Kamil Gala, 2018. "The a priori risk classification with spatial autocorrelation in automobile insurance," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 51, pages 147-168.
    • Handle: RePEc:sgh:annals:i:51:y:2018:p:147-168
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    References listed on IDEAS

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    1. Lemaire, Jean & Park, Sojung Carol & Wang, Kili C., 2016. "The Use Of Annual Mileage As A Rating Variable," ASTIN Bulletin, Cambridge University Press, vol. 46(1), pages 39-69, January.
    2. Boskov, M. & Verrall, R. J., 1994. "Premium Rating by Geographic Area Using Spatial Models," ASTIN Bulletin, Cambridge University Press, vol. 24(1), pages 131-143, May.
    3. Jean-Philippe Boucher & Michel Denuit & Montserrat Guillén, 2007. "Risk Classification for Claim Counts," North American Actuarial Journal, Taylor & Francis Journals, vol. 11(4), pages 110-131.
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