Independent consultant Christopher Wilson on why usage-based insurance will be the commercial driver for connected vehicle deployment models for the near future
Christopher Wilson is a connected-car pioneer. In the early 1990s, while working with TRW Automotive, he saw how connected devices could unsnarl traffic jams and speed emergency responses. His history includes stints as VP of strategy and IT for Daimler/Chrysler and director of product management for ADAS with TeleAtlas/TomTom. He managed connected vehicle programs at the Crash Avoidance Metrics Partnership (CAMP) and was founding director of the Vehicle Infrastructure Integration Consortium (VIIC).
Now, as an independent consultant and one of the leading advocates for connected vehicles, he continues to explore the best business models and deployment strategies to make use of the data generated by connected vehicles. TU asked Chris whether it's time for vehicle data to begin to pay off…
When it comes to understanding consumer behavior, it seems like the UBI industry is trying to reinvent the wheel. Can't we employ the same analytics technologies used by Amazon, for example?
The same software that enables Visa to detect aberrant behavior on a credit card will let an insurance company detect the aberrant behavior of a driver—given enough data. Visa has been watching your buying patterns for a long time; insurance companies have been getting driving data for two or three years, and it's pretty coarse data. We are still lacking in data, both quantity and quality, about how people really drive. We have data coming in now, but it's just a small fraction of what we will have in a few years. Same with Amazon: They have a lot of data; when we catch up, we will be able to recommend driving styles.
How can this coming flood of data be managed and analyzed to provide information for insurers, fleet managers and other businesses?
Most of today's UBI models are based on very simplistic driving parameters, such as time of day or simple acceleration metrics. For example, the fleet management systems out there typically sample every 30 seconds or, more likely, every few minutes. That doesn't give rich detail of how someone accelerates into and out of a curve, whether they stop for stop signs or roll through them.
The next step is to be able to put some better algorithms in the cars to identify certain critical events; that's being done. Given a trigger event, we can download a lot of data for short period of time, but we have limited ability to identify or characterize safety events and find those triggers. The ‘big data’ movement here in Silicon Valley is developing techniques to deal with the size of data sets we will have and developing the tools to find the key events. We're at a really good time for the whole UBI world, because we are now capable of getting all this data as well as having adequate tools for analysis and processing. (For more on UBI and data, see Telematics and UBI: The data challenges, Telematics and the value of data, and Telematics and probe data: The revenue opportunities.)
Will we need a bigger data pipe from the vehicle?
Yes. Pipes are getting bigger all the time, and there are a lot of people working to make even bigger pipes for connected vehicles. The exercise we're in right now is figuring out how big a pipe we want to pay for. I predict we will find that that pipe is a lot bigger than most people think right now.
What about data from smartphones? The brought-in device remains very important in many of the current connected car offerings.
Short-term, the smartphone is a great source of high-quality data. But there are some significant problems that mean that, long-term, it will go away once insurance companies and OEMs learn to work together to get good data. For example, imagine what happens when you put your phone on the dash and enter a curve. The phone starts to slide across the car, hits the side of the car and then falls to the floor. What does an insurance company make of that? At best, they lost the data on the curve; at worst, they think you flipped the car. Installation is a big issue as well as access to richer sensors. In the long term, even better data will be obtained from OEMs. (For more on UBI and smartphones, see Smartphones as an incentive for insurance telematics and Consumers and UBI: The power of value-added services.)
Will OEMs install sensors just for insurance companies?
There will be a lot of resistance on the part of OEMs to putting in a new ‘insurance sensor.’ Right now, there is a lot of low-level exploration of cooperation. This is stepping up with applications like Ford’s Crew Chief. If fleet managers, who make the vehicle buying decision and also pay for insurance, see they can get insurance rates reduced by having good accelerometer data, they will call up Ford and say they’ll buy the vehicle if they can get access to the data. OEMs will be incentivized to open existing sensors. It's just a software change to make that data available. That’s a long way from an ‘insurance sensor,’ but we still have many, many more opportunities with existing vehicle architectures and sensors, especially as we consider the new sensors appearing in vehicles.
If using telematics data to personalize insurance rates is the obvious solution, are there other, not so obvious uses for that data?
There are many, many uses. On the infrastructure side, we currently have traffic. But we can use data to better utilize, design and operate infrastructure, signal timing, where to build roads, how to manage lanes on a bridge, what speeds are being driven. On the vehicle side, this data can be used to identify bad behaviors in real time, then to provide the driver feedback or use vehicle systems to ameliorate the outcome of bad driving. For autonomous and semi-autonomous systems, we can use connected vehicle data to learn how vehicles should behave and make them feel ‘natural.’ Many uses outside the transportation space as well.
The technical problems, for the most part, are not that hard to solve. The main challenges are around the business model. (For more on UBI business models, see Telematics and the business case for UBI, and Telematics and customized UBI business models, and Telematics, IP litigation and the UBI market.) That's another reason I'm working with insurance companies: I believe insurance can put a high value on collecting data from vehicles, and that data can then be used for so many other beneficial purposes. UBI will be the commercial driver for connected vehicle deployment models for the near future.
Susan Kuchinskas is a regular contributor to TU.
For more on insurance telematics, see Special report: Insurance telematics.
For exclusive insurance telematics business analysis and insight, read TU’s Smart Vehicle Technology: The Future of Insurance Telematics report.
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