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This research was funded by Universidad Francisco de Vitoria under the project titled Business analytics, geolocalizacion y modelizacion espacial en el sector financiero y asegurador (Research project funding 2021) and Mariano Matilla-Garcia was funded by the Ministerio de Ciencia e Innovacion under grant PID2019-107192GB-I00.

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Contributions from Spatial Models to Non-Life Insurance Pricing: An Empirical Application to Water Damage Risk

Publicado en:Mathematics. 9 (19): 2476-e2476 - 2021-10-01 9(19), DOI: 10.3390/math9192476

Autores: Victoria Rivas-Lopez, Maria; Minguez-Salido, Roman; Matilla Garcia, Mariano; Echeverria Rey, Alejandro

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This paper explores the application of spatial models to non-life insurance data focused on the multi-risk home insurance branch. In the pricing modelling and rating process, spatial information should be considered by actuaries and insurance managers because frequencies and claim sizes may vary by region and the premium should be different considering this rating variable. In addition, it is relevant to examine the spatial dependence due to the fact that the frequency of claims in neighbouring regions is often expected to be more closely related than those in regions far from each other. In this paper, a comparison between spatial models, such as spatial autoregressive models (SAR), the spatial error model (SEM), and the spatial Durbin model (SDM), and a non-spatial model has been developed. The data used for this analysis are for a home insurance portfolio located in Spain, from which we have selected peril of water coverage.

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