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The burning questions around the changes in motor risk as we move towards full vehicle automation

Swiss Re and Waymo announce partnership to foster the safe deployment of new technologies on the roads
Maria-Eleni Mageira
Digital Marketing & Communications Manager

Swiss Re and Waymo recently announced their research collaboration partnership as we fasten our seatbelts for this new journey of remarkable technological advances and plentiful insight into the future of autonomous vehicles. Ensuring safety on the roads is becoming more pressing than ever before, while assessing the risk from new technologies is becoming even more complex. Luigi Di Lillo and Margherita Atzei from Swiss Re specialise in automation and its emerging risks. We called them seeking answers to some of our burning questions.

Hello both. Being part of an ecosystem is key for supporting the fast-evolving industry. What exactly are the obstacles that Swiss Re and Waymo are aiming to tackle?

We will set out the differences in performance between human-driven vehicles and autonomous vehicles in a formal way. The main obstacles are data, understanding the technology and contextualising its performance.  

This rapid advance in self-driving technology is already being reflected in motor insurance. What is changing in motor risk?

The motor insurance market is evolving fast. The emergence of new technologies and business models will lead to the creation of new risk assessment methodologies and insurance products. Currently, the insurance industry does not possess the knowledge and means to assess the risk and underwrite autonomous vehicles. Through our partnership with Waymo, we want to fill this gap and foster the safe deployment of this technology on the roads.

What does it mean for insurance portfolios?

The roll-out of autonomous vehicles, even long before their mass deployment, will lead to important changes to insurance portfolios. We might see a shift towards commercial liability as ride-sharing business models take over. Product liability will also increase in importance as the driver of the vehicle shifts from being a human to AI.

Is 100% safety an achievable vision?

In plain terms, it is achievable as much as it is for a vehicle driven by a super-attentive, highly skilled and reactive human, minus the human common sense. Absolute certainty of full (ie under any driving conditions, in any design domain) prevention or mitigation cannot be guaranteed but it is a goal to aspire to and strive for.

How does Swiss Re's Automotive & Mobility Solutions Unit – together with Movingdots – plan to support clients, insurers and mobility providers in the transition towards vehicle autonomy?

At Swiss Re, we develop solutions that can support our clients in better understanding and quantifying emerging risks in the mobility space. Some examples are our Vehicle Risk scores (eg ADAS Risk Score, EV Risk Score) that translate our risk and engineering knowledge into something that can be used by insurers to better assess and predict the risk. Working with Movingdots will make these scores richer and more dynamic, allowing for driver behaviour and vehicle feature usage to be unified with the pure vehicle dimension for a holistic risk-scoring solution of unmatched predictive power.

Luigi Di Lillo
Lead Products and Partnerships at Swiss Re

Luigi Di Lillo is an applied physicist who leads the Products and Partnerships team at Swiss Re – Business Unit Reinsurance Solutions. He is an Affiliated Researcher of the Ethical Intelligence Lab at Harvard University and a Research Collaborator in the Department of Logic and Philosophy also at Harvard University. He sits on the Board of Directors of PAVE Europe (Partners for Automated Vehicle Education).

Margherita Atzei
Product Manager at Swiss Re

Margherita Atzei is a Product Manager at Swiss Re, leading the development of insurance solutions for autonomous vehicles. Margherita holds a bachelor's degree in economics from the University of Bristol and a master's degree in economics from the University of St. Gallen.

Related work

The future of motor risk: Driver today, passenger next

From driverless dilemmas to more practical commonsense tests for automated vehicles

Formal Estimation of Collision Risks for Autonomous Vehicles: A Compositional Data-Driven Approach

On the emerging risks of automation: the case for Autonomous Vehicles

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