Data exchanges could work to change the UBI product, Siegfried Mortkowitz discovers.

It is widely assumed that the advent of connected cars will be a boon for usage-based insurance (UBI) because it will eliminate many of the issues that have impeded its market growth, such as cost for the insurer and the friction of installing the device or downloading the app. In addition, the insurance can then be made available by the carmaker at the point of sale.

However, this development will also greatly exacerbate a problem that is intrinsic to UBI: how to ‘translate’ the data from different data sources into one ‘language’ that can be understood by insurers and consumers.As David Lukens, director of Telematics at data, analytics and technology provider LexisNexis Risk Solutions, points out driving data can vary not only from source to source but also from carmaker to carmaker and even from model to model.

“There’s an irony in people thinking about the connected car,” he says. “People talk about it as if it were one thing but the connected car is actually a far more fragmented environment than smartphones and [telematics] devices, because every model year is different. Even within a model year different trim levels of a car have different data flows. So, even within one manufacturer, or one programme, you might have 20 different data types. And every model year it changes. And when you multiply that by 15 or 20 OEMs, it’s a very complicated problem.”

The solution is the use of data exchanges, which Lukens defines as “a forum in which different parties – it could be auto manufacturers, telecoms, insurance companies, or telematics service providers – submit their data to the service, and the service normalises and aggregates the data so it’s available to insurance companies in a common format, a single standard output.”

According to Geoff Werner, UBI global product leader at Willis Towers Watson. “These services are going to become very important, because insurance companies are going to struggle if they have to consume data from 20 different suppliers and all the data is different.”

Data exchanges such as LexisNexis and Willis Towers Watson have existed for many years but as Lukens and Werner suggest, they will become far more crucial players in the UBI ecosystem as more and more connected cars enter the global fleet. In Europe, that evolution will be hastened by the eCall mandate, which is due to come into effect in April of next year. In the US, it may take a bit longer. According to a 2016 study carried out by LexisNexis, using the national database of insured vehicles and manufacturer reports on how many connected cars they will produce in a model year: “We found that in ten years a little over 50% of the fleet will be connected in some way and 55% of those will be connected in a way that produces meaningful data for understanding driving risk.” Among other things, this means that data sources other than the connected car will still be used for UBI data for quite a while to come.

One important result of the growing importance of data exchanges will almost certainly be the creation of new partnerships and new ways of offering UBI to consumers. Lukens says one likely consequence of efficient data exchange platforms is the creation of close partnerships between carmakers and insurers. “There are already partnerships between insurers and carmakers,” he says. “BMW has a programme with Allianz, there are programmes with Audi, with Lexus. I think this allows those programmes to data-share, to really take it up a level. It’s going to be a great customer experience.”

Lukens goes on to say that this partnership is inevitable, since carmakers and insurers have a unique relationship. “They share a customer 100% of the time, everyone who has a car has insurance. The ability to team up and provide a sharing experience through the data is pretty powerful. If you’re BMW and you want to own and shape this customer’s ownership experience, you can enhance that by bringing in insurance partners.”

Sharing will bring in new players

Carmakers will want to make their data available to other insurance companies as well, through some kind of an exchange programme and that also applies to insurers, Lukens says. “From the insurance point of view, if I’m an insurer, you can’t only offer a programme to one carmaker. I have to have a programme that can take any vehicle owner, or in households that have different kinds of cars, to handle family policies, or to be able to handle the market in general.”

Werner of Willis Towers Watson predicts data exchange platforms will enable other players – some already active in the UBI market but in a different capacity, some who are newcomers – to exploit their data for UBI. “Some of these data suppliers are collecting data because they’re providing some other location-based service, such as Google Maps,” he explains. “Consumers allowed them to track them because they wanted that service. Now these companies may, with the right permissions in place, be able to use the same data to provide their customers with additional value and auto insurance would be a logical way to do that.”

These data suppliers could employ the data in one of three ways, he explains. They could offer auto own-branded insurance, either by themselves or with a single insurer; they could contribute the data to a data exchange and get revenue whenever an insurer purchases it from the data exchange host; or they could use their multiple partnerships with insurers to offer their customers a range of tailored motor insurance options to choose the best possible offer, what Werner calls a “lead generation model”.

He suggests that the increased numbers of connected cars on the road will reduce the impact of self-selection for UBI and create a dilemma for carmakers when most cars are connected and all drivers agree to let the carmakers contribute their data to a data exchange.

“Some of those drivers will get discounts, some will be unaffected and some will be surcharged,” Werner believes. “To the extent that the data can be used to improve their driving and settle claims better, it will minimise the number of people who are surcharged but there will be people who get surcharged and be very upset by that, which would be terrible for the data supplier.“

His solution is for the data supplier to know beforehand what types of offers each driver would get and provide them with full information, potentially only giving offers to drivers who are eligible for a discount. “The data supplier could analyse the data and then, before the data is shared with an insurance company, tell the customer, ‘We’ve seen your driving data and you could reduce your chances of having an accident and potentially reduce your insurance premiums if you would just drive a little better by not accelerating so violently.’ Or, ‘You’re a very good driver and we have insurance partners who will reward you with discounts of 21%, 25% or 23%.’ That would be using the data responsibly and bringing something of value to the customer.”

Werner believes this is a better model for the customer because it eliminates discount uncertainty, an important consumer complaint about UBI. “The consumer wants to know what he’s going to get,” he says, explaining that in three surveys carried out by his firm, the single biggest consumer complaint about UBI was the uncertainty of not knowing what the premium would be after the insurer had tracked them. “The data supplier already has of the actual driving data, and can tell the driver the exact discount he’s going to get before they have to agree to a UBI policy,” he says. “That’s why I think this is a far superior model to what we have today.”

Of course, data suppliers will have to be very meticulous about how they approach the customer to get permission to analyse the data. Werner suggests that in exchange they could offer the customer a substantial subscription fee discount, for example. “The consumer is always going to have to consent to their data being used this way,” Lukens cautions. “I don’t see a world in which I could pull your data without you knowing about it, use it to price your insurance and then present you with a quote. Ultimately, the consumer has to drive what the data can be used for.”

[Ins.Mortkowitz.2017.02.02]

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