University of Connecticut

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Geography Colloquium - Dipak Dey

Friday, April 19, 2019
12:20pm – 1:15pm

Storrs Campus
AUST 445

Spatial Risk Estimation for Individualized Auto Premiums based on Geographic Information System

Dipak K. Dey Department of Statistics University of Connecticut

This presentation is based on analyzing big auto insurance claim data to improve spatial risk estimation and classification. 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 graph Laplacian regularization. The estimated spatial effects are then used to generate risk rankings at the county/zip code 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 in US separately.

Contact:

Scott Stephenson [stephenson@uconn.edu

Geography Department (primary), UConn Master Calendar

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