Abstract
Modelling of Large Insurance Claims and Occurrence Data
by
Dipak K Dey
This presentation features the partnership between Travelers Insurance and the Department of Statistics, University of Connecticut, on analyzing big auto insurance claim data to improve spatial risk classification. In this talk, we explore a spatial variant of the double generalized linear model (DGLM), in which Tweedie distribution, as a special case, is used to model the pure premium, and the spatial correlation is incorporated via Laplacian regularization. The estimated spatial effects are then used to generate risk rankings at the county level. Simulation results and real data analysis showcase the efficacy of the new methods. Besides our recent progress, the challenges we face in large-scale predictive modeling and our future directions will also be discussed. In particular, we focus on collision data and build models for each state of USA separately.
Committee
Workshop
Key Dates
Communication
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