Sherezad Rehmann, Senior Director of Global Product Management, and Martyn Mathews, Senior Director of Personal Lines Insurance, U.K. and Ireland, LexisNexis Risk Solutions
As nations globally instigated lockdown measures to control the spread of COVID-19, private cars largely went unused for weeks on end. The annual motor insurance premium calculated on a range of factors such as where the policyholder lives, their age, occupation and engine size could not factor for this sudden and prolonged change in risk. Insurance providers offering telematics or usage-based insurance products had insight the rest of the market could only guess at with reports of traffic volumes falling between 70%-85%[i].
The pandemic has highlighted the value of static and dynamic vehicle data in understanding risk, delivering a fair and accurate premium and giving motorists more flexibility and control over their insurance costs. Rather than rely on estimations and proxies for risk, it could tell an insurer the car’s mileage (valuable insight during and post-pandemic), the car’s position, how it is driven and the Advanced Driver Assistance Systems (ADAS) features on-board and activated to enable the development of more personalised, more engaging insurance cover.
This isn’t visionary, the insurance and car manufacturing markets were coming together to make this concept a reality, well before the emergence of COVID-19.
By 2030[ii], all new vehicles are expected to have connectivity feeding a wide range of data to car manufacturers. Carmakers have invested significantly in connectivity as part of their drive to provide a greater choice of mobility solutions to help improve the customer experience. Data from the car can help them understand exactly how their vehicles are used and how they can cut the cost of ownership as they invest in developing increasingly autonomous vehicles as part of their zero emissions and zero fatalities objectives. C.A.S.E., or Connectivity, Autonomous, Sharing/Subscription and Electrification, is being used as the guiding principal for the future of the auto industry.
In parallel with the development and increasing market penetration of the connected car there is a recognition amongst insurance providers that they will need access to vehicle centric data to support the provision of usage based insurance.
It is as much in insurers’ interests to understand more about the car as it is manufacturers. Consumer expectations were already changing prior to the pandemic, but the demand for more personalised products looks set to increase. Vehicle centric data has the potential to help price insurance more fairly, cut claims costs and deliver new services such as Pay As You Drive products.
The big question has been how to bring these two major industries together so that insurance providers can access connected car data in a way that adheres to data privacy and security regulations as well as making sure that the data is useable and meaningful for insurance. How do you ensure Mrs Smith driving her Fiat 500 is given the option to share her driving data for insurance and this will be understood in the same way as her neighbour driving a completely different car? When you think about the volume of car makes and models, the number of motor insurance providers, the quantity of motorists buying insurance it becomes a big ‘many to many’ problem.
The solution lies in a data platform strategy that takes all the strands of vehicle centric data – so telematics data from any device or app, data from the connected car and vehicle build data and putting it into an environment where it can be standardized, contextualized, normalized and scored in a fully compliant manner for use across a variety of vehicle makes or models. This is one big data project that could have a profound impact on the future of mobility.
The starting point goes back to the investment car makers are putting in vehicle autonomy with ADAS (Advanced Driver Assistance Systems) increasingly available in vehicles and constantly being enhanced. SMMT research shows 8 in 10[iii] new cars in the UK have driver assistance systems and over half have adaptive cruise control. In the US, LexisNexis internal analysis shows 76% of
2019 models had at least one core ADAS feature, which is up significantly compared to 18% in 2014[iv].
To date, it has been a challenge for insurers to identify exactly what ADAS features a specific vehicle is equipped with when writing a motor insurance policy. This is because each car manufacturer has created their own unique terminology, definitions and naming structures – sometimes releasing multiple features within the same model year. In addition, many items are chosen as optional extras when a vehicle is purchased from new.
To address this challenge, data scientists at LexisNexis Risk Solutions have developed an ADAS classification system using machine learning to scan millions of lines of car manufacturer vehicle data to logically sequence and classify vehicle safety features and component’s intended operation or purpose.
This classification system provides the foundation for LexisNexis Vehicle Build. Access to vehicle safety data will help insurance providers factor for their presence throughout the customer journey – in pricing, mid- term adjustments and renewals – and establish the differences in risk profile associated with the vehicles that have these safety features.
Access to vehicle safety data will help insurance providers factor for their presence throughout the customer journey. It will also enable them to understand how specific safety features behave, for example if a feature will provide an alert or warning to the vehicle’s driver when a potential danger or hazard is detected. It will also allow insurers to understand the purpose of features.
At the same time, car manufacturers will be able to see what ADAS features have the most impact on their customer’s safety to help drive further enhancements.
As carmakers and insurers get a better understanding of the vehicle, how it’s driven, its performance and how semi-autonomous features work in the real world, consumers will also learn how data from and about the car can work for them. This will support market adoption, drive innovation and help create more benefits in terms of safety and total cost of ownership.
Safer cars, safer roads, lives saved, fairer more flexible insurance cover – the value of vehicle centric cannot be overstated and we’re already well on the journey to enable motorists to truly benefit.
