How telematics is driving success

Rutger van der Wall examines how telematics can be used to understand the risks of driverless cars

How telematics is driving success

Whether it’s motorists’ fears or fantasies about driverless cars, barely a day goes by without fresh opinion appearing in the media on the whys and wherefores of autonomous vehicles. This has recently been brought into sharper focus as the UK government has confirmed it is looking to amend the Road Traffic Act 1988 motor insurance provisions to extend mandatory motor insurance to include product liability. In a speech to insurers earlier this year, the road transport minister warned that traditional data sources for rating insurance will become obsolete with the emergence of the connected car.

If there was ever a sharp elbow prod to the insurance sector to prepare, this was it. That is not to suggest insurers have been slow to the party, far from it.
They have been acutely conscious of the liability questions and involved in discussions from the outset. However, there is an urgent need to get down to the nitty-gritty and start appreciating the value that driving behaviour data, such as speeding, braking and road familiarity, will bring in understanding liability and risk and enabling cover to be provided for driverless cars.

We know that fully autonomous vehicles are not going to appear overnight – it is more realistic to consider this as a staged process. IHS Automotive, a provider of global market, industry and technical expertise, predicts that almost 76 million vehicles with some level of autonomy will be sold globally between now and 2035. This means we will see vehicles with a range of autonomous capabilities on our roads and a hybrid of liabilities for insurers and manufacturers to consider.

For example, personal liability will need to be accounted for in the case of humans driving vehicles with limited automation. However, manufacturers involved in testing autonomous vehicle technology have clearly indicated they will carry liability for their vehicles when they are in fully autonomous mode. The challenge for insurers is that they have no historical data to refer to when it comes to these
types of risk.

So how can insurers calculate risk and develop products that support the use and adoption of driver assistance technology? Ultimately, they need to know how consumers are using this.


“We have a window of opportunity to use telematics during this testing period to better understand the risks involved”


The answer is in telematics technology. We have a window of opportunity to use telematics during this testing period to gain the necessary insights and better understand the risks involved. By working with the original equipment manufacturers (OEMs), insurers can use the mass of data being collected from vehicles to understand the effectiveness of autonomous cars and how drivers interact with the capabilities of the vehicle. The data collected through telematics will be invaluable for underwriters and actuaries to determine their claims loss ratios, and also how the risk changes across the different levels of autonomy.

It will also enable insurers and manufacturers to identify, in the case of an accident, whether the technology installed worked in the way expected, and also the role that human intervention played, if any. These results can then be delivered back to the insurer for them to make a judgment on the fault of the claim and who is responsible.

Fundamentally, driving data, regardless of how it is collected – whether hard wired black box, a 12V plug-in device into the cigarette lighter in the car or a driverless car – needs filtering, normalising and enriching to bring value. This is where insurers need to be focusing their time right now, to fully understand the processes and possibilities. Ultimately, this will help them meet the new legal requirements by the time fully autonomous vehicles reach UK roads.

In order to accelerate the learnings during this period, the industry needs to consider how it can work together for the benefit of all parties. For example, a data hub could be created, which would enable all insurers and OEMs to share data and learnings. Insurers could then pitch for the data sets they require. This exchange of data would provide actuaries and underwriters with access to a large amount of quality data in order to calculate risks accurately and identify emerging trends.

Insurers are already effective at sharing data with central government databases, controlling personal data to eliminate fraud, and using contributory services. So this is a good model to use in the case of driverless cars. Therefore, by working together as an industry, propositions and solutions can be created to improve the success of driverless cars with all the societal benefits this mode of transport will offer.

Rutger van der Wall is Vice president business development, auto insurance – LexisNexis

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