The impact of telematics on the insurability of risks

Abstract

Purpose The purpose of this paper is to analyze the use of telematics in insurance and its consequences for the insurability of risks. Empirical results on monitoring policyholders or insured objects and its consequences for asymmetric information, as well as claims frequency and severity are discussed. Furthermore, potential future research questions that arise from the use of telematics in risk management and insurance are outlined. Design/methodology/approach The paper systematically reviews existing studies and then investigates the consequences of telematics using Berliner’s insurability criteria. The results are based on 52 academic studies and industry papers published from 2000 to 2019. Findings The findings emphasize the effects of new information on information asymmetry and risk pooling, the implications of new technologies on loss frequency and severity, legal restrictions and ethical consequences of the use of telematics in the insurance field. Problems with the insurability impede the market development of innovations such as telematics tariffs. Originality/value Despite its increasing relevance for businesses at present, research on telematics in insurance is limited. Some papers can be found in the IT domain, but relatively little research has been done in the business and economics literature. The authors illustrate where the research stands currently and outline directions for future research.

Creating ethics guidelines for artificial intelligence and big data analytics customers: The case of the consumer European insurance market

“…If a young female driver manages to drive with care, this will be reflected in her premium, and she may not just be discriminated against on the basis of age. 99 Barry and Charpentier also make the case that the behavioral data gathered by telematics devices are more reliable than demographic data. 100 However, telematics and the associated data do bring with them more general fairness issues around surveillance, autonomy, and privacy.…”

Near‐miss telematics in motor insurance

“…Arumugam and Bhargavi (2019) describe a PHYD payment approach based on risk scores at a theoretical level, but they do not discuss any real case study examples. Eling and Kraft (2020) analyze the use of telematics in insurance and conclude that the reduction of information asymmetries, as well as the possibility of carrying out more accurate risk pooling, improves the insurability of risks; however, they stress the need for further research on loss frequency and severity in the context of telematics data. Geyer et al (2020) analyze a telematics data set with detailed information about driving behavior (speed, distance driven, and road type) in pay‐as‐you‐drive (PAYD) contracts that are based on distance driven and road type.…”

“…Hynes and Dickey (2008) found that even the rate of change of acceleration had an influence on rear‐impact vehicle collisions. We refer the reader to Eling and Kraft (2020; Table ) where they can find an updated, exhaustive and systematic summary of existing model approaches in telematics insurance.…”

An Acceptance Approach for Novel Technologies in Car Insurance

“…[3] described the partnership of a system integrator and auto insurers based on the use of telematic devices, which in turn created a profitable business venture. This has opened an avenue for a number of data mining [30] and risk modeling approaches [31] based on the close ties between system integrators and the risk and contract management departments of insurers.…”