Driving Risk Evaluation Based on Telematics Data
20 Pages Posted: 13 Dec 2018
Date Written: November 21, 2018
Telematics car driving data describes drivers' driving characteristics. This paper studies the predictive power of telematics data for claims frequency prediction. We first extract covariates from telematics car driving data using K-mediods clustering and principal components analysis. These telematics covariates are then used as explanatory variables for claims frequency modeling, in which we analyze their predictive power. Moreover, we use these telematics covariates to challenge the classical covariates usually used.
Keywords: Telematics data; Driving habit; Driving style; v-a heatmap; Acceleration pattern; K-mediods algorithm; Principal components analysis; Generalized additive model; Generalized linear model; Variable selection; Collinearity; Poisson regression; Deviance statistics; Claims frequency modeling; Car
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