Articles - Joining the dots between cars and drivers to assess risk


Over the last decade, we’ve seen technology impact most aspects of our lives. While the financial services sector may have been behind the curve in its pace of digital adoption, consumer expectations of simplicity, transparency, and ease have compelled insurance providers to accelerate digital offerings. As technology and data have changed how we buy and use our insurance policies, we should also expect data and technology to change how risk is determined.

 By Andrew Ballard, product principle, LexisNexis Risk Solutions, Insurance

 We must also acknowledge that insurance is an essential protection for consumers who want to know they will be covered should certain things happen and for that protection to be fairly priced and clearly understood.

 Connecting the dots to assess risk
 Traditional models were designed to predict risk and propensity to claim based on linear dimensions such as claiming history, value of the asset, and reported crime in a postcode area. More recently, motor insurance risk models have started ingesting data from connected vehicles and gaining a better understanding of driving behaviour through telematics devices. However, these differing data sets are usually managed in silos, lacking contextualisation.

 Moreover, technology is evolving in the vehicles we drive, many of which already have more advanced intelligent features known as ADAS (Advanced Driver Assistance Systems) such as automatic emergency braking or lane keep assist. Further levels of automation will be introduced as technology rapidly evolves, all the way to self-driving vehicles following the new Automated Vehicles Bill . While non-driving responsibilities will still remain with the vehicle owner, such as maintaining appropriate insurance and ensuring proper loading, when a vehicle is driving itself, a “commercial entity” rather than an individual will be responsible for the way it drives. The question remains however over how insurance providers will know the mode of the vehicle at the time of an accident.

 It’s not just the vehicles that are evolving. The proliferation of technology within our day-to-day lives has effectively turned people into an Internet of Things (IoT) sensor. Through the use of mobile phones and wearables, people can be fully connected, 24/7. We are generating data at 328.77 million terabytes a day. In comparison, a connected vehicle generates 30 .

 The data generated from a person shows a much more holistic picture of their mobility behaviour. Where and how they travel can feed into behaviour models. Does an individual drive an electric car? Do they tend to take a more climate-friendly route – i.e. one with fewer hills, narrow winding roads, less traffic and constant speeds? Do they participate in the ride-share community or make use of e-bike and scooter schemes?

 So what can the insurance sector gain from this evolution of driver and vehicle technology and data?

 Claims Prevention
 By accessing Vehicle Identification Number (VIN) level Advanced Driver Assistance Systems (ADAS) features for an individual vehicle – not one like it, but that actual car, insurers can understand the safety features available on that car and the risk that car poses when on the road. Overlaid with information of how the driver utilises those features (whether they disable them, ignore them or abide by them), will provide a view of a driver’s risk in combination with the vehicle’s.

 By adding in historic claims information from across the industry, an insurance provider can understand trends between loss type, vehicle, ADAS and location of loss. Finally, data collected through a connected car or a driving app will create a picture of how, when and where the vehicle is driven.

 This granular data will enable more accurate risk prediction and pricing but can also be used within a claims prevention model.

 In the same way energy companies, use smart meter data to provide tips to their customers on how to save on energy use, an insurance provider can share hints and tips to a customer on how to improve their safety. They can inform them of the ADAS features available in their vehicle and how to make the best use of them. This awareness is critical for the safe use of vehicle technology as capabilities become more advanced. Through crowd-sourcing of data (sometimes called “swarm data”) they can even enlighten them if they regularly use accident hotspots so they remain aware during their journeys.

 Hyper-personalisation
 A comedian once described a policyholder as a moody teenager; only reaching out when there’s a problem. Despite the funny, yet relatable analogy, insurance providers need to step up like responsible parents during the ‘moment that matters’ to their customer.

 They need to know their customer and provide the right type of service through the best channels. In motor claims this means understanding how a customer chooses to be mobile. By doing so, it will allow the insurance provider to be flexible in serving their policyholder’s mobility needs following an incident. For example, do all eligible claimants need to be supplied with a replacement car during the repair process? What if supply chain issues are causing delays to repair times and the customer is left without any mobility provision at all?

 Insurance providers could leverage data to better understand their customer and offer flexible alternatives to keep them mobile whilst their vehicle is immobile. They might want to offer a monetary incentive to use alternative mobility methods or understand if they have access to another vehicle through friends, family or even ride-share.

 In essence, great technology is an empty shell without relevant and accurate data. In order to gain real efficiencies and provide a personalised service at scale, insurance providers will need to see the whole story from quote to claim and that means accessing data on and from the vehicle and the driver. Joining the dots in driver and vehicle risk can help insurance providers know more in order to do more for their customers.

 
  

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