Please use this identifier to cite or link to this item:
Title: Can automobile insurance telematics predict the risk of near-miss events?
Author: Guillén, Montserrat
Nielsen, Jens Perch
Pérez Marín, Ana María
Elpidorou, Valandis
Keywords: Risc (Assegurances)
Assegurances d'automòbils
Teoria de la predicció
Risk (Insurance)
Automobile insurance
Prediction theory
Issue Date: Mar-2020
Publisher: Taylor and Francis
Abstract: Telematics data from usage-based motor insurance provide valuable information - including vehicle usage, attitude towards speeding, time and proportion of urban/non-urban driving - that can be used for ratemaking. Additional information on acceleration, braking and cornering can likewise be usefully employed to identify near-miss events, a concept taken from aviation that denotes a situation that may have resulted in an accident. We analyze near-miss events from a sample of drivers in order to identify the risk factors associated with a higher risk of near-miss occurrence. Our empirical application with a pilot sample of real usage-based insurance data reveals that certain factors are associated with a higher expected number of near-miss events, but that the association differs depending on the type of near-miss. We conclude that nighttime driving is associated with a lower risk of cornering events, urban driving increases the risk of braking events and speeding is associated with acceleration events. These results are relevant for the insurance industry in order to implement dynamic risk monitoring through telematics, as well as preventive actions.
Note: Versió postprint del document publicat a:
It is part of: North American Actuarial Journal, 2020, vol. 24, num. 1, p. 141-152
Related resource:
ISSN: 1092-0277
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

Files in This Item:
File Description SizeFormat 
691701.pdf241 kBAdobe PDFView/Open    Request a copy

Embargat   Document embargat fins el 1-10-2021

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.