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Integration of traditional and telematics data for efficient insurance claims prediction

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008  240830e2024 bel|||p |0|||b|eng d
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24510‎$a‎Integration of traditional and telematics data for efficient insurance claims prediction‎$c‎Hashan Peiris [et al]
520  ‎$a‎While 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
650 4‎$0‎MAPA20080586294‎$a‎Mercado de seguros
650 4‎$0‎MAPA20080556495‎$a‎Siniestros
650 4‎$0‎MAPA20080545338‎$a‎Seguros
650 4‎$0‎MAPA20080603779‎$a‎Seguro de automóviles
650 4‎$0‎MAPA20080556730‎$a‎Telemática
7730 ‎$w‎MAP20077000420‎$g‎15/05/2024 Volumen 54 Número 2 - mayo 2024 , p.263-279‎$x‎0515-0361‎$t‎Astin bulletin‎$d‎Belgium : ASTIN and AFIR Sections of the International Actuarial Association
856  ‎$u‎https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/integration-of-traditional-and-telematics-data-for-efficient-insurance-claims-prediction/2D72787C1DE75B6DF0FECC90E6414B40