Integration of traditional and telematics data for efficient insurance claims prediction

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<rdf:Description>
<dc:date>2024</dc:date>
<dc:description xml:lang="es">Sumario: While driver telematics has gained attention for risk classification in auto insurance, scarcity of observations with telematics features has been problematic, which could be owing to either privacy concerns or favorable selection compared to the data points with traditional features. To handle this issue, we apply a data integration technique based on calibration weights for usage-based insurance with multiple sources of data. It is shown that the proposed framework can efficiently integrate traditional data and telematics data and can also deal with possible favorable selection issues related to telematics data availability. Our findings are supported by a simulation study and empirical analysis in a synthetic telematics dataset</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/186144.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Mercado de seguros</dc:subject>
<dc:subject xml:lang="es">Siniestros</dc:subject>
<dc:subject xml:lang="es">Seguros</dc:subject>
<dc:subject xml:lang="es">Seguro de automóviles</dc:subject>
<dc:subject xml:lang="es">Telemática</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Integration of traditional and telematics data for efficient insurance claims prediction</dc:title>
<dc:relation xml:lang="es">En: Astin bulletin. - Belgium : ASTIN and AFIR Sections of the International Actuarial Association = ISSN 0515-0361. - 15/05/2024 Volumen 54 Número 2 - mayo 2024 , p.263-279</dc:relation>
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