What autonomous vehicles do to insurance systems and how the community will adapt

Last month, the Swiss Association for Autonomous Mobility (SAAM) organised a panel discussion with the Swiss InsurTech Hub on how to price a risk when the “driver” is no longer human. Set up within the framework of the SAAM Insurance Day in Zürich, this panel demonstrated how data, simulation, and collaboration are crucial to building trust and accelerating the safe rollout of autonomous vehicles (AVs). Indeed, since insurance coverage is a legal prerequisite for any vehicle registration in Switzerland, it is a gateway to scalability for autonomous mobility. Without it, fleets cannot expand beyond pilot projects. But what are the steps to take?

Shifting mindsets

For decades, insurance models have relied on human behaviour. Premiums were determined by age, experience, location, and driving history, a simple equation that assumed human error was at the heart of most accidents. With autonomous vehicles, that logic collapses. There is no driver’s record, no reaction time, no distraction. Instead, decisions are made by complex systems of sensors, software, and artificial intelligence. Responsibility and risk shift from the individual to the technology itself, as well as to the ecosystem that supports it: manufacturers, operators, data providers, and infrastructure managers.

This evolution forces insurers to rethink their core business. It’s no longer about predicting how humans behave, but about understanding how algorithms perform under specific conditions. Risk is no longer universal; it is contextual. The same vehicle might be low-risk in a controlled industrial park but high-risk in a dense urban environment. Therefore, measuring risk becomes a synonym to assessing the environment of operation of AVs.

New tools enabling adapted insurance

Without a human driver, insurers need new indicators of performance and safety. This is where the concept of the Operational Design Domain (ODD) becomes essential. An ODD defines where and how an autonomous vehicle can operate safely, including factors like geography, road type, traffic density, weather, and time of day.

Simulytic has developed an innovative model called the AV Deployment Risk Score (AVDRS). It uses digital twins and AI to simulate thousands of driving scenarios in a virtual version of the real world. This allows insurers to evaluate how an autonomous system behaves within its specific ODD, before it ever hits the road. This tool, as well as other similar ones currently entering the insurance market, is more than just a technical innovation; it represents a new way of managing trust. Creating hyper-local, evidence-based risk assessments allows insurers to move from reactive pricing (based on past claims) to predictive and preventive models.

The role of data in that ecosystem transformation is key. But using synthetic telematics data generated from digital twins protects manufacturers and drivers from intrusive access to proprietary vehicle software. The result is a win-win situation: insurers can price risk accurately, and manufacturers can prove the safety of their systems without revealing trade secrets.

Consequences for the automotive and insurance ecosystems

A progressive transformation can lead to a different approach to coverage, making it not just a financial product, but a service integrated into the mobility ecosystem itself.

Starting from existing models’ adaptation with additional risk factors to bridge from human-driven vehicles to autonomous ones, a new single, unified Autonomous Vehicle Liability Policy could then be developed, covering all aspects of AV operations instead of keeping separate policies for general liability, auto, cyber, and product risks. In parallel, the insured parties and distribution model could change: instead of each company in the AV ecosystem buying its own insurance, a comprehensive AV Wrap Policy could cover all stakeholders, manufacturers, software developers, fleet operators, and service providers, under one umbrella. Besides, in the future, AV software providers might embed insurance directly into their platforms, so coverage becomes a built-in feature of autonomous mobility.

These innovations in vehicle technology and the cooperation of stakeholders involved are expected to result in a positive scalability framework for autonomous mobility, based on conditions for scalable, insurable AV deployments. Accurate risk scoring helps insurers offer fairer premiums. It also encourages manufacturers to improve their systems based on measurable safety indicators. Over time, this cycle of data, feedback, and confidence will be essential to making autonomy mainstream. This makes insurance a potential catalyst for progress in the age of autonomy. The next generation of insurance products may be dynamic, usage-based, and embedded, reflecting real-time conditions rather than static assumptions.

This transformation will not happen overnight. It requires cooperation between insurers, technology providers, policymakers, and associations like SAAM, which bring these stakeholders together to share knowledge and shape a common framework.

Autonomous vehicles are teaching us that safety, trust, and innovation go hand in hand. The insurance industry has a unique role to play, not just in managing risk, but in enabling the future of mobility.

Source: The original article was published HERE.