Department of Mathematics

Special Actuarial Research Seminar

  •  Himchan Jeong, Department of Statistics and Actuarial Science at Simon Fraser University in Canada
  •  Integration of Traditional and Telematics Data for Efficient Insurance Claims Predictions
  •  02/21/2023
  •  4:00 PM - 5:00 PM
  •  C304 Wells Hall
  •  Amanda Nickols (

Linked Abstract

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 concern or adverse selection compared to the data points with traditional features. To handle this issue, we propose a data integration technique based on calibration weights. It is shown that the proposed technique can efficiently integrate the so-called traditional data and telematics data and also cope with possible adverse selection issues on the availability of telematics data. Our findings are supported by a simulation study and empirical analysis on a synthetic telematics dataset.



Department of Mathematics
Michigan State University
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C212 Wells Hall
East Lansing, MI 48824

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