Predictive claim scores for dynamic multi-product risk classification in insurance

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<title>Predictive claim scores for dynamic multi-product risk classification in insurance</title>
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<dateIssued encoding="marc">2021</dateIssued>
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<abstract displayLabel="Summary">It has become standard practice in the non-life insurance industry to employ generalized linear models (GLMs) for insurance pricing. 
 However, these GLMs traditionally work only with a priori characteristics of policyholders, while nowadays we increasingly have a posteriori information of individual customers available across multiple product categories. In this paper, we therefore develop a framework to capture this a posteriori information over several product lines using a dynamic claim score. More specifically, we extend the bonus-malus-panel model of Boucher and Inoussa (2014) and Boucher and Pigeon (2018) to include claim scores from other product categories and to allow for nonlinear effects of these scores. The application of the proposed multi-product framework to a Dutch property and casualty insurance portfolio shows that customers' individual claims experience can have a significant impact on the risk classification. Moreover, it indicates that considerably more profits can be gained by accounting for their multi-product claims experience.</abstract>
<note type="statement of responsibility">Robert Matthijs Verschuren</note>
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<topic>Perfil de riesgo</topic>
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<topic>Bonus-malus</topic>
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<topic>Modelos actuariales</topic>
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<topic>Matemática del seguro</topic>
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<topic>Productos de seguros</topic>
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<topic>Reclamaciones</topic>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>01/01/2021 Volumen 51 Número 1 - enero 2021 , p. 1-25</text>
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