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Connected and autonomous vehicle injury loss events : potential risk and actuarial considerations for primary insurers

Recurso electrónico / Electronic resource
Colección: Artículos
Título: Connected and autonomous vehicle injury loss events : potential risk and actuarial considerations for primary insurers / Darren Shannon...[et.al.]
Notas: Sumario: The introduction of connected and autonomous vehicles (CAVs) to the road transport ecosystem will change the manner of collisions. CAVs are expected to optimize the safety of road users and the wider environment, while alleviating traffic congestion and maximizing occupant comfort. The net result is a reduction in the frequency of motor vehicle collisions, and a reduction in the number of injuries currently seen as preventable. A changing risk ecosystem will introduce new challenges and opportunities for primary insurers. Prior studies have highlighted the economic benefit provided by reductions in the frequency of hazardous events. This economic benefit, however, will be offset by the economic detriment incurred by emerging risks and the increased scrutiny placed on existing risks. We posit four plausible scenarios detailing how an introduction of these technologies could result in a larger relative rate of injury claims currently characterized as tail-risk events. In such a scenario, the culmination of these losses will present as a second hump in actuarial loss models. We discuss how CAV risk factors and traffic dynamics may combine to make a second hump a plausible reality, and discuss a number of opportunities that may arise for primary insurers from a changing road environment.Registros relacionados: En: Risk management & insurance review. - Malden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999- = ISSN 1098-1616. - 15/03/2021 Tomo 24 Número 1 - 2021 , p. 5-35Materia / lugar / evento: Seguro de automóviles Vehículos autónomos Conectividad Siniestralidad Indice de frecuencia Métodos actuariales Otros autores: Shannon, Darren
Otras clasificaciones: 322
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