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.

In Germany, every year 66,000 road crashes lead to death or injury of young novice drivers. This makes them twice as likely to be involved in, or cause, vehicle crashes compared to their older and more experienced counterparts. This study aims to address this societal issue by developing a better understanding of the German young driver problem. For this purpose, we created an updated, 55-item strong version of the Behaviour of Young Novice Drivers Scale (BYNDS), originally developed by Scott-Parker et al. in 2010. To make the new version of the BYNDS understandable for German young novice drivers, this research used a new method of translation in combination with extensive pre-testing. As a result, we identified possible threats for response errors such as retrospective formulated questions or double negations. Due the adjustment of the possible sources of error the presented version of the BYNDS is semantically and conceptually different from the original. However, due to the application of the updated version of the BYNDS in a robust sample of 700 participants, this paper presents the first reliable and validated tool to measure novices risky driving behaviour in Germany. Moreover, it offers an updated and extended version of the BYNDS that allows practitioners but also researchers to broaden their understanding of young driver risk.

From February 2020, both urban and rural Ireland witnessed the rapid proliferation of the COVID-19 disease throughout its counties. During this period, the national COVID-19 responses included stay-at-home directives issued by the state, subject to varying levels of enforcement. In this paper, we present a new method to assess and rank the causes of Ireland COVID-19 deaths as it relates to mobility activities within each county provided by Google while taking into consideration the epidemiological confirmed positive cases reported per county. We used a network structure and rank propagation modelling approach using Personalised PageRank to reveal the importance of each mobility category linked to cases and deaths. Then a novel feature-selection method using relative prominent factors finds important features related to each county's death. Finally, we clustered the counties based on features selected with the network results using a customised network clustering algorithm for the research problem. Our analysis reveals that the most important mobility trend categories that exhibit the strongest association to COVID-19 cases and deaths include retail and recreation and workplaces. This is the first time a network structure and rank propagation modelling approach has been used to link COVID-19 data to mobility patterns. The infection determinants landscape illustrated by the network results aligns soundly with county socio-economic and demographic features. The novel feature selection and clustering method presented clusters useful to policymakers, managers of the health sector, politicians and even sociologists. Finally, each county has a different impact on the national total.

Zusammenfassung: Sicherheit ist eine zentrale Grundlage für Freiheit, Lebensqualität und Wohlstand in einer modernen Gesellschaft. Als vielschichtiges Alltagsphänomen erfährt der Sicherheitsbegriff eine kontinuierliche Erweiterung, die durch soziale, wirtschaftliche und politische Veränderungen angetrieben wird. Daraus ergeben sich sowohl neue Herausforderungen als auch Potenziale für die deutsche Versicherungswirtschaft, deren zentrale gesellschaftliche Funktion aus der hoch entwickelten Kernkompetenz in der Risikoidentifikation, -bewertung und -übernahme resultiert.Bislang verspricht das immaterielle Kernprodukt von Versicherungen eine in die Zukunft gerichtete Leistung, die erst im Anschluss an ein Schadenereignis fällig wird – was obendrein nur von einem Bruchteil der Versicherten erlebt wird. Durch den zielgerichteten Einsatz neuer Technologien bietet sich für die Assekuranz jedoch die Chance, ihre Rolle von „Verstehen und Schützen“ hin zu „Vorhersagen und Verhindern“ weiterzuentwickeln. Diese Entwicklung wird als Anlass genommen, das traditionelle Leistungsversprechen am Beispiel der Sicherheit junger Fahrer kritisch zu hinterfragen. In aktuellen Studien der WHO zählen junge Autofahrer weltweit zu den am meisten gefährdeten Verkehrsteilnehmern. Dies führt neben Produktivitätsverlusten und hohen medizinischen Kosten vor allem zu weitreichenden Belastungen im privaten Umfeld. In diesem Zusammenhang wird diskutiert, ob die Telematik-Versicherung als verhaltensbasiertes Produkt ein geeignetes Werkzeug für den antizipativen Umgang mit Risiken ist. Dadurch wird ein Beitrag zur Debatte rund um das Thema Sicherheit geleistet.