New vehicles fitted with eCall, smartphones with their sensors leveraged by technology partners like Cambridge Mobile Telematics and The Floow, the original black boxes installed in vehicles by insurers; all promise many benefits from improving driver behaviour to reducing premiums to enabling UBI insurance products and powering mobility services. Tesla's Elon Musk promised to make the nightmare of claims into a dream leveraging the data from its EVs.
At the heart of this is data and data management. It should be easier for Tesla to manage the output from its own vehicle sensors and AutoPilot but how will it fare with other makes of vehicles which it insures? Most households have multiple makes of cars in the drive, some have motorbikes as well and most truck fleets have more than one make.
Ryan McMahon vice president of strategy at Cambridge Mobile Telematics, makes a strong point.
"There is no standardization among automakers, so the data that is collected varies by manufacturer, by car model and by year. So, “connected car data” can mean anything from simply an odometer reading to live video from a camera. ..... “It means something very different to different manufacturers, and it’s changed over time and will continue to change because it’s driven by whatever the needs are of the manufacturer.”
Insurance companies by gathering data from many different devices — including smartphones, Internet of Things (IoT) devices, cameras, dashcams, and connected cars- need to be able to connect and standardise data and will look to the data aggregators for that vital output. Gaps left by one data source may be filled by data from another.
"For example, one of the leading predictors of crashes is hard braking. However, it can be difficult to standardize the reporting of hard braking because different manufacturers sample the relevant data at different intervals. A hard braking event may last only a fraction of a second, so if an automaker samples the data only once a second, it may miss that event. This can be solved by adding an IoT device with a sample rate that’s higher.
“When you put these two elements together, we’re fusing data across these devices, and then we fuse data across phones, and now we can fuse data across connected car,” McMahon said. “So, we can fill in the gaps of any information that doesn’t exist in one sensor platform with another.”
This normalisation of data is vital if the driver is to be given the means to improve driving standards. Even more to deliver the data to underwrite risk better and manage claims when vehicles are involved in road traffic accidents. Other solution providers like CCC, Mitchell and Verisk serve up vehicle data including ADAS features and vehicle specs to help feed the algorithms of underwriting. and claims
Add in the vehicle damage damage and repair cost/time estimating, Tractable and Solera to name just two, and you add to the mountains of data each in different formats and coverage.
McMahon compared usage-based insurance for automobiles to an electricity bill or a water bill. By reflecting the individual’s actual consumption, these tools can help them understand the elements that make up what they pay as well as the ways they can reduce that cost.
“If the incentives are aligned, and if the data is available, and if there’s a mechanism to try to communicate it, then the consumer can actually get in a position where they reduce the likelihood of getting into a crash,” McMahon said.
In those unfortunate cases where consumers and commercial drivers to get in to a crash the claims platforms like RightIndem can triage the data and feed in real-time to the various software and platforms deployed by insurers.
This is evolving and insurers around the world seeking the optimal mix of technology partners to fully leverage the multiple and disparate data sources.
Not just for cars; there is a market for motorbikes as well. Private owners may be resistant to tracking ( I imagine free souls roaming highways and byways free of oversight and not wanting surveillance) but couriers and delivery drivers will surely benefit.
And truck fleets are already monitored so it is a natural shoe-in. As long as the data is standardised, fed to all the software and technology stacks involved and is 'AI-Ready'.
Data-driven is the mantra for insurtechs, innovative insurers and mobility services but in practice this is complex as McMahon describes. Easy enough to connect an odometer to a UBI auto insurance product. Quite another to add context to hard braking, aggressive cornering and sudden deceleration.
Specialist insurers will find it easier than generalists but that is relatively so and does not make it absolutely easy to deploy telematics effectively. ZEGO and pay-as-you-go insurance for food delivery drivers working for Uber Eats, Just Eats and others is one thing. Progressive or Admiral offering insurance for a wide range customers quite another.
All require telematics to be part of the systems architecture and technology stacks of the insurer. The insurer will have a range of traditional, UBI and mobility-as-a-service products requiring custom integrations.
Core systems of record, underwriting and claims platforms must be able to facilitate integration and data flows between platforms, applications and deliver optimal results to consumers, business customers, insurers and their brokers.
This is a matter of serious strategic and tactical capabilities that will sort out the digitally mature from the digitally immature.
McMahon compared usage-based insurance for automobiles to an electricity bill or a water bill. By reflecting the individual’s actual consumption, these tools can help them understand the elements that make up what they pay as well as the ways they can reduce that cost. “If the incentives are aligned, and if the data is available, and if there’s a mechanism to try to communicate it, then the consumer can actually get in a position where they reduce the likelihood of getting into a crash,” McMahon said.