The paper introduces an approach to telematics devices data application in
automotive insurance. We conduct a comparative analysis of different types of
devices that collect information on vehicle utilization and driving style of
its driver, describe advantages and disadvantages of these devices and indicate
the most efficient from the insurer point of view. The possible formats of
telematics data are described and methods of their processing to a format
convenient for modelling are proposed. We also introduce an approach to
classify the accidents strength. Using all the available information, we
estimate accident probability models for different types of accidents and
identify an optimal set of factors for each of the models. We assess the
quality of resulting models using both in-sample and out-of-sample estimates.
Description
Usage-Based Vehicle Insurance: Driving Style Factors of Accident Probability and Severity
%0 Journal Article
%1 korishchenko2019usagebased
%A Korishchenko, Konstantin
%A Stankevich, Ivan
%A Pilnik, Nikolay
%A Petrova, Daria
%D 2019
%K Insurance, Probablity, Statistics, cars data,
%T Usage-Based Vehicle Insurance: Driving Style Factors of Accident
Probability and Severity
%U http://arxiv.org/abs/1910.00460
%X The paper introduces an approach to telematics devices data application in
automotive insurance. We conduct a comparative analysis of different types of
devices that collect information on vehicle utilization and driving style of
its driver, describe advantages and disadvantages of these devices and indicate
the most efficient from the insurer point of view. The possible formats of
telematics data are described and methods of their processing to a format
convenient for modelling are proposed. We also introduce an approach to
classify the accidents strength. Using all the available information, we
estimate accident probability models for different types of accidents and
identify an optimal set of factors for each of the models. We assess the
quality of resulting models using both in-sample and out-of-sample estimates.
@article{korishchenko2019usagebased,
abstract = {The paper introduces an approach to telematics devices data application in
automotive insurance. We conduct a comparative analysis of different types of
devices that collect information on vehicle utilization and driving style of
its driver, describe advantages and disadvantages of these devices and indicate
the most efficient from the insurer point of view. The possible formats of
telematics data are described and methods of their processing to a format
convenient for modelling are proposed. We also introduce an approach to
classify the accidents strength. Using all the available information, we
estimate accident probability models for different types of accidents and
identify an optimal set of factors for each of the models. We assess the
quality of resulting models using both in-sample and out-of-sample estimates.},
added-at = {2020-03-31T04:27:03.000+0200},
author = {Korishchenko, Konstantin and Stankevich, Ivan and Pilnik, Nikolay and Petrova, Daria},
biburl = {https://www.bibsonomy.org/bibtex/2e958c8300883d37184e3c3522e345713/alanagnew},
description = {Usage-Based Vehicle Insurance: Driving Style Factors of Accident Probability and Severity},
interhash = {0b31f47d760914c92a9f00b49295be7e},
intrahash = {e958c8300883d37184e3c3522e345713},
keywords = {Insurance, Probablity, Statistics, cars data,},
note = {cite arxiv:1910.00460},
timestamp = {2020-03-31T04:27:03.000+0200},
title = {Usage-Based Vehicle Insurance: Driving Style Factors of Accident
Probability and Severity},
url = {http://arxiv.org/abs/1910.00460},
year = 2019
}