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

Maria Victoria Rivas-Lopez, Roman Minguez-Salido, Mariano Matilla-García and Alejandro Echeverria Rey
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Maria Victoria Rivas-Lopez: Escuela Politécnica Superior, Universidad Francisco de Vitoria, 28223 Madrid, Spain
Roman Minguez-Salido: Department of Public Economy, Statistics and Economic Policy, University of Castilla-La Mancha, Avenida Los Alfares 44, 16071 Cuenca, Spain
Alejandro Echeverria Rey: Escuela Politécnica Superior, Universidad Francisco de Vitoria, 28223 Madrid, Spain

Mathematics, 2021, vol. 9, issue 19, 1-12

Abstract: 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.

Keywords: spatial autorregresive model; claims; severity; actuarial models; water coverage; home insurance data (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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