Today there are over 448 individual makes of car that are licensed and on the road. There are over 45,387 basic model variants, and this is not including different trim levels and options. Taking one example, from just one large manufacturer the consumer will make a choice between: eight main model variants, six engine types, 18 finishes, four wheel types, 12 driver assistance packs, five lighting options (including safety lighting), four options for audio communications, plus 33 other options that may include specialised disability options.
It’s a name game
If it sounds complicated, it’s meant to. Choosing car options and comparing like-for-like when buying a car is a difficult business. For an individual automaker it makes sense to impress the consumer with a set of options and attractive features with names like Surround View Camera, Driver Monitoring, Rear Cross Traffic Warning or Forward Collision Warning.
But when it comes to making use of vehicle build data, and looking in context at an individual vehicle’s ADAS (Advanced Driver Assistance Technology) systems –with its risk and propensity to be involved in an insurance claim– it adds up to a market problem.
The new automotive-insurance relationship
«To keep on top of this complexity – the data normalization necessary for different ADAS hardware installations, VIN (Vehicle Identification Number) and trim data, the fast-moving nature of model types – any individual insurance company will need to recruit an army to trawl through each car manual»
If we consider the new automotive-insurance relationship that is going to be necessary, on the road to semi-autonomous and autonomous vehicles, there has to be a willingness from all parties to derive the necessary data insight coming from vehicle build information. On this journey, more and more information required for insurance underwriting is going to be coming from the vehicle data, and vehicle risk, not just the ‘person’ risk.
But looking at the established information silos that exist, the complexity and regionalised nature of the vehicle data, the resources needed to extract the necessary data just for insurance can be paralysing. To keep on top of this complexity – the data normalization necessary for different ADAS hardware installations, VIN (Vehicle Identification Number) and trim data, the fast-moving nature of model types – any individual insurance company will need to recruit an army to trawl through each car manual.
Looking to see a clearer pathway to the future
Quite rightly the stakeholders, the automotive OEMs and the insurers grappling with these issues want evidence, and they’re looking to see a clearer pathway to the future, before deciding to how to invest for vehicle on-board data solutions. Given what we know: advanced vehicle technology can reduce the insurance claims frequency, but it adds to the typical repair cost of a vehicle over and above the traditional bodywork cost, then we have to recognise some fresh thinking is required.
There are pockets of work going on. Since 2009 Euro NCAP has been rating vehicles that offer ADAS technologies in a test environment. But no macro trends have emerged that are really useful in determining how the feature performance really determines: how many collisions are being prevented? What is the cost-benefit ratio of specific ADAS features in terms of how they prevent insurance claims and bring other benefits to the driver? What are the trends? What are the appropriate strategies that insurers and the automotive OEMs should be following?
On the hunt for data
With our LexisNexis® Vehicle Build solution we are able to provide the evidence of how well ADAS systems work for a specific automotive brand, compared to other brands and other vehicle features. For us as data aggregation and data platform specialists it is all about deriving useful insight out of the mountains of data that exist, providing confidence to create new customer propositions.
«For the typical insurer, the limitations are around the huge resources needed to connect to the many different data sources, what we’ve been calling the ‘many-to-many challenge’»
On the one hand the vehicle manufacturers want the insurance industry to better price safety into the vehicle price, to help drive car sales and create a clearer consumer proposition of the benefits of ADAS systems. For the typical insurer, the limitations are around the huge resources needed to connect to the many different data sources, what we’ve been calling the ‘many-to-many challenge’.
Data normalization is required across vehicle marques, models and variants, to generate the required insight across systems that appear to perform differently. Changing individual systems to be able to ingest new data sources can be expensive and there’s only a small amount of data on the benefits. There’s a common desire for market insight.
A common desire for market insight
Telling a customer they have AEB, Lane Keeping Assist or ABS is not enough. In future connected car data and ADAS-derived data is going to be able to spell out clearer consumer benefits, such as lower insurance costs (and lower propensity to claim), and by how much.
LexisNexis® Vehicle Build helps insurance providers achieve their primary goals:
- Adequately assess and price risks, effectively creating new risk segments and quoting benefits
- Bringing a material impact to loss and expense ratios
- Helping to work across product functions, adding value to insurance products
- Maintain contract language that adheres to regulatory requirements
- Growing new business and providing consumer retention choices
- In summary, ADAS features, to varying degrees will become reflected in the insurance premium
LexisNexis® Vehicle Build helps automotive OEMs achieve their primary goals:
- Demonstrate clearer safety benefits and monetary benefits (usually insurance discounts) to the driver
- Demonstrate a clearer function of the machine-to-human interface, how the driver uses the ADAS features for the fullest benefit
- Helping to maintain their role in the vehicle ‘ecosystem’, as the system grows as an interdependent ‘network of networks’
- Providing a clearer roadmap for the future about the efficacy of ADAS features and their road safety or ‘risk’ impact
- Growing brand loyalty and preparing for the future interconnectivity challenges for insurance that are coming
For the driver and vehicle owner today, it is important to take a proactive approach and become familiar with the advanced driver assistance technologies and how they work, especially before getting behind the wheel of a new or rental vehicle with ADAS technologies. Being better informed –and by harnessing the power of vehicle build data– drivers will be able to get the most out of their vehicles while staying safe on the road.
