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Opening the black box on premiums: three ways that big data is changing car insurance models

Opening the black box on premiums: three ways that big data is changing car insurance models | Insurance Business

Opening the black box on premiums: three ways that big data is changing car insurance models

The following is an opinion piece written by Patrick Quinn, chief executive officer, MyPolicy Group. The views expressed within the article are not necessarily reflective of those of Insurance Business.

Big data harnessed through telematics technology is reconfiguring risk-pricing in car insurance, enhancing insights for insurers and lowering premiums for responsible drivers.

September is traditionally the busiest month for car insurance renewals and as households across the UK went back to work this month, many will have faced the unenviable task of renewing their cover. While UK drivers have profited from falling premiums over the past 18 months, as insurers priced in the benefits of government legislation designed to cut the cost of personal injury claims and curb fraudulent whiplash claims, car insurance remains a significant financial burden for many drivers.

The cost of annual renewal is particularly prohibitive for younger drivers, a group often heavily penalised by the processes underpinning insurers’ risk pricing. Historically, insurers have used demographic profiling to price risk, grouping drivers into different risk buckets by age, gender or postcode, before allocating an average annual premium to each bucket. This approach aims to ensure that enough capital is allocated to each bucket to pay for any claims and expenses that arise, maintaining profitability in motor lines, but fails to provide a substantive assessment of the risk posed by individual drivers. Younger drivers are typically categorised together, meaning that even the most careful, safety-conscious young drivers often face hefty premiums due to the high incidence of accidents among this age-group. Ultimately, these broad-brush assumptions fail to provide an accurate picture of the risk posed by individual driving behaviours, to the detriment of both insurers and their customers.

Pricing risk
Over time, the scope of demographic profiling has been expanded to incorporate a much broader range of customer data, including previous convictions, type of car and historic claims, but the integration of big data into risk pricing, as powered by Minerva’s Rating Engine, has ushered in a new era of innovation for the motor insurance industry.

The development of telematics and usage-based car insurance began in the early 2000s, driven by the rise of mobile data, smartphones and, increasingly, connected vehicles. Young drivers have been well-represented among early adopters of telematics-based insurance, with many opting to install a small black box within their vehicle in a bid to reduce their insurance premium. While older drivers might regard the installation of the ‘black box’ as a sinister, big-brother presence, young drivers, well-versed in data sharing, have been quick to engage with a more connected and collaborative driving experience. At MyPolicy Group, we have observed this trend in the take up of our own telematics offering.

Harnessing insights
Data aggregated through telematics provides a 360-degree picture of a drivers’ behaviour, from the way they accelerate out of their driveway, to the speed at which they exit a motorway junction. By effectively harnessing data around when, where and how a person is driving, insurers can derive a much more granular assessment of individual driving behaviours and, by extension, the likelihood of that person making a claim. A more individualised approach to drivers’ risk enables insurers to risk-adjust for every mile driven, rather than a rough annual average, bringing clarity and customisation to both insurers and drivers.

Rewarding safer drivers
By connecting the dots between premium pricing and driving behaviour, telematics providers have opened up the ‘black box’ on premium pricing, inverting the long-held narrative in car insurance, namely, that loyalty does not pay. For too long, drivers have been penalised on the basis of arbitrary risk factors and historic claims. Most drivers who have a traditional insurance product and automatically renew their cover pay more each year, due to the loss-leading business model of motor insurance, which relies on acquiring new customers through discounts and steadily ratcheting the cost of cover up year after year to make that customer profitable. Customers who take out traditional insurance are seldom, if ever, rewarded for safer driving.

More recently, the development of software and mobile apps have enhanced feedback for drivers on their driving performance, providing insurers with new opportunities to engage with their customers. Encouraging motorists to access, share and adjust their driving behaviour in response to data feedback enables them to take a more active role in determining the price of their car insurance. By enhancing transparency around premiums, telematics has revolutionised premium pricing.

While telematics data has provided insurers with new insights on driving behaviour and redefined risk-pricing, the motor insurance industry is also taking important lessons from companies; pioneering mobility solutions, such as Uber, which has honed the per-trip charging model, have redefined how people think about urban travel, challenging the concept of car ownership and laying the foundations for journey-based insurance pricing. There is an urgent need to provide the car-sharing community with the ability to pay for cover and split bills on a per-journey basis, an important next step in an increasingly connected future and shared economy.