Press kit

The world of insurance is rapidly evolving, moving away from one-size-fits-all policies toward smarter, data-driven models.  Risk no longer has to be shared amongst the insured individuals, but can be tailored to your own use-age or behaviour over time.

One such innovation is Distance Based Adaptive Insurance, a dynamic approach that aligns premiums more closely with how much your fleet is actually on the road. As technology, mobility patterns, and risk assessment methods change, this model is becoming increasingly relevant for operators.

What Is Distance Based Adaptive Insurance?

Distance-Based Insurance is a type of adaptive insurance where premiums are calculated on the basis of how many kilometres your drivers are on the road. Or, in the case of shared mobility assets, how many minutes of trips your assets rack up through their usage in a month. Unlike traditional insurance, which relies heavily on static factors, this model adjusts pricing based on periodically recorded data.

Distance-based insurance operates on a basic principle — your premiums should reflect your real world behaviour. 

How Does Distance Based Adaptive Insurance Work?

Distance-based adaptive insurance usually operates through one of these methods:

1. Telematics Devices – A small device installed in the vehicle records mileage and driving behaviour. Transmitting in real time.
2. Mobile App Tracking – A driver’s smartphone that tracks distance via GPS.
3. Reported Vehicle Data – Some modern cars can share data directly with insurers.

Based on the collected data, insurers calculate premiums using a combination of:

• Base insurance cost, which is the minimum coverage fee
• Per-kilometre coverage rate

For example, a person who drives 5,000 km per year may pay significantly less than someone who drives 20,000 km annually.

Why Is Distance Based Insurance Becoming Popular?

Several factors are driving the adoption of this model for mobility operators:

1. Fairer Pricing

Traditional insurance penalises low-mileage drivers by charging them rates similar to those charged to high-mileage drivers. Distance-based insurance corrects this imbalance, making pricing more equitable.

2. Supports Sustainability

By financially rewarding less kilometre travelled and better route optimisation, this model indirectly promotes reduced fuel consumption and lower carbon emissions, thus aligning with global sustainability goals.

3. Ideal for Car-Sharing Model 

For car sharing operators, distance based insurance enables their operations to scale better. By dynamically associating coverage to on-road assets. Not locking them into paying for de-fleeted or under-used heretical. Trip based pricing ensures a fairer set of premiums that  align to their unit economics. 

4. Adapted to Seasonality

With dynamic pricing based on kilometres, distance based insurance supports your operations during a low activity period. If you observe less activity during winter, the dynamic pricing model can ensure your operations margin stays high to support your company’s sustainability.

Challenges and Concerns of Distance Based Adaptive Insurance

While promising, this model does come with some concerns:

1. Privacy Issues

Many platforms worry about insurers tracking their movements. Transparency between insurer and companies on data ensures GDPR respect and compliance. 

2. Technology Reliability

GPS glitches, app malfunctions, or device failures could lead to inaccurate mileage recording.

3. Not Suitable for All Operators

Companies with a fleet on the road all day may end up paying more than they do with traditional insurance.

Traditional Insurance vs. Distance Based Adaptive Insurance

Unlike traditional insurance, which relies on a fixed annual premium based on generalised risk factors, distance-based adaptive insurance uses a variable pricing model that changes according to how much your drivers are on the road.. 

Traditional insurance assesses risk broadly using factors such as age, location, and past claims history, whereas distance-based insurance offers a more personalised assessment based on real driving data. 

While conventional policies give operators limited control over their premiums, the distance-based model allows policyholders to influence their costs by optimising around trip volume. 

Traditional insurance requires little to no technology, whereas distance-based insurance depends heavily on accurate usage data. As a result, traditional insurance is better suited for regular or high-mileage fleets, while distance-based adaptive insurance is more beneficial for low-mileage fleets or platforms that have peak seasons followed by months with reduced trip volume.

FAQs

1. What exactly is distance based adaptive insurance?

Distance-based adaptive insurance is a usage-based insurance model where your premium depends largely on how many kilometres you drive. Instead of paying a fixed annual amount, you pay a base rate plus a variable cost based on your actual driving distance.

2. How is my driving distance tracked?

Insurers typically track mileage through a telematics device installed in your car, a mobile app using GPS, or built-in vehicle data systems. The technology records only the necessary data required to calculate your premium.

3. Is my company data safe with distance based insurance?

Insurers use encryption, secure servers, and strict access controls to ensure GDPR compliance and guarantee your fleet data safety. 

4. Does distance based insurance monitor my driving behaviour, too?

Some policies only track distance, while others may also monitor speed, braking patterns, and time of travel. Behaviour-based tracking can sometimes lower your premium further if you demonstrate safe driving habits.

How Autonomous Vehicles Are Shifting From Sci-Fi to Reality

In the United States, more and more autonomous vehicles are hitting the streets. East-coast to West-coast, billions of investment has been directed into start-ups across the value chain. From software providers, battery developers and full-stack car manufacturers. It is a relentless rise  of a new model of mobility, and with it a new set of risks that need controlling for.

Why Self Driving Cars Arrive First In The U.S 

Several factors have made the U.S an excellent proving ground for autonomous vehicles over recent years. These include the pre-existence of tech giants, with big budgets to back innovation bets,and urban hubs organised around cars.

However, the pressing need to control risk and prevent loss relating to human error on the road was also a factor that has accelerated innovation in driverless mobility in the U.S.

It has been said that 94% of car accidents occur due to human mistakes behind the wheel. The belief powering these innovations in driverless mobility is that if you remove the driver from the equation, risk of loss will be reduced.

So far, the data seems to suggest that the benefit to risk control is real.  In the U.S, data from  riverless mobility pioneer Waymo, demonstrate that autonomous vehicles have reduced crash rates. With 80–90% fewer injury-causing crashes, as they avoid human distractions, intoxication, and fatigue on the same routes driven by regular vehicles. 

When Driverless Mobility Will Arrive In Europe 

Ten years on from the first step on from the first-step in the U.S market,  Europe is set for its own on-road revolution. But it is a revolution  from below as much as above. With Europe’s own start-ups implementing autonomous vehicles, rather than U.S players wholesale importing their model to Europe. 

From local actors to cross continent partnership, start-ups in Europe are also developing their own driverless solutions. Mobility super-app Bolt has announced partnerships NVIDA, with self-driving firm Pony AI and automaker Stellantis all within a few months. Signalling the shared mobility giant’s intent to play a serious role in the autonomous vehicle race.

However, for Europe, driverless mobility is a bigger challenge due to urban design. Cities have been designed for pedestrians, urban ecosystems are organised for public transport, for autonomous vehicles the challenge is to adapt the model to a unique environment. 

A Challenging Ecosystem for Driverless Mobility

Europe is not a unified environment. The creation of PAVE Europe (Partners for Automated Vehicle Education), shows how this forces mobility players to act. Directing efforts to public and policymaker education. Its members include Waymo, Deloitte, Holon, Ruter and PwC. In Europe there is more of a focus needed on first securing top-down policy change that brings similar rules across borders, to enable autonomous mobility to flourish.

When it comes to risk control, autonomous fleets, optimised through AI and integrated into shared mobility models, can meaningfully contribute to great on-road safety. But, also to reduce urban emissions and rethink how space is used in cities. By decreasing reliance on personal vehicles, these fleets accelerate Europe’s transition toward a more sustainable and intelligent mobility ecosystem.

Driverless Mobility Solutions at Scale

In Europe, the future of driverless mobility will be based on a common shared goal, built by an entire ecosystem moving in the same direction. Major automotive groups, technology investors, and public institutions are increasingly aligned around a shared conviction: autonomous vehicles are becoming the new reality.

Billions in investment are accelerating that shift, and the partnerships forming between established players and innovative start-ups are giving it real operational depth. What will ultimately determine success is the supporting infrastructure that makes deployment viable at scale. 

Adaptive insurance models that evolve with the risk profile of autonomous fleets, data platforms, smart infrastructure, and regulatory frameworks that move with the industry, every layer of the ecosystem has a role to play. Europe has the ambition, the partners, the investment, and the tools are aligning. Be part of the new mobility world.