Jonathan Hewett, Chief Marketing Officer, Octo Telematics
We don’t drive cars anymore. We drive computers on wheels. Depending on the model, cars these days sport somewhere between 50 and well over 100 embedded microprocessors. These computers fine-tune our engines, keep us on the road, and help us find our way. They also generate a huge amount of data. Most of us, however, allow these data go to waste. It’s as if we’d be driving cars that fire on just a few cylinders each; we’d constantly allow petrol go unburned through the exhaust.
We fail to capture the data, even though we know that data are the fuel powering today’s digital economy. This attitude, however, is changing rapidly. The data revolution is reaching cars. The algorithms underpinning modern data analytics are now beginning to revolutionise the economics of driving.
Everybody in the automotive value chain – from drivers to manufacturers to transport authorities to insurers – are beginning to understand the huge potential that today’s Algorithm Economy can offer to the transport sector.
Experts predict that by 2020,connected cars will collect more than 11 petabytes of data a year, including from embedded telematics devices. To put this in context, 11 petabytes of songs playing continuously would last for over 22,000 years, assuming the average MP3 encoding for mobile is around 1MB per minute, and the average song lasts about four minutes.
One of the first industries to feel the immediate impact of this Algorithm Economy is car insurance.
The change, of course, will not come from the numbers themselves, but from making sense of the data. The data we once allowed to go uncaptured now can be feed into algorithms, which provide us with insights into driver behaviour, which in turn allows both drivers and insurers to take action.
Let’s start with the driver: just like a health app on your smartphone, getting instant feedback on your driving can provide powerful nudges to change behaviour – maybe drive more carefully and economically.
This in turn has a direct influence on something that data capture finally makes truly measurable: risk. Currently, insurers have to price their policies based on very rough and ready assumptions; the risk premium of an insurance, for example,is currently determined by the driver’s age or the model of car they own, regardless of their actual driving behaviour. However, by harnessing driver data and applying sophisticated data analytics, companies like Octo Telematics can give insurers the insights they need to forecast individual risk.
The impact can be immediate: more careful drivers pay lower premiums, while insurers can reduce their costs through fewer claims.
Insurers will also know immediately when a driver had an accident, and can alert emergency services or offer roadside assistance. More importantly, insurers now have the data to understand why an accident happened. Crash reconstructions will be much more accurate, which in turn will both speed up the claims process and can dramatically reduce fraud.
Right now, about £50 of every annual car insurance policy covers the cost of insurance fraud. With telematics and data capture in place, most of that fraud could be spotted straight away. Here’s a startling statistic: Insurance policies that are underpinned by telematics on average result in 50% fewer claims than traditional policies.
In other words, using telematics to bring the Algorithm Economy to the automotive sector will sharply reduce insurance fraud and bring down premiums.
Revolutionising car insurance, however, will just be a start. Octo is one of the pioneers of automotive telematics; this has given our company a huge amount of expertise not only in data capture and mobile connectivity, but also of using Big Data analytics to draw insights from complex and dynamic data sets. Understanding risk and driver behaviour is one application, but it also places Octo in a perfect spot to support connected and ultimately autonomous vehicles.
The Algorithm Economy, of course, is set to change and support our lives wherever data capture happens. As the Internet of Things spreads, everyday objects will soon be defined by the sophistication of the algorithms powering them. And customers, manufacturers and service providers will have to rely on companies skilled in secure data analytics to extract the data and provide the information needed for rapid insight and action.
Most of us still see the computerisation of our cars as being about driving convenience and fun. But that will be just one aspect of the transformation. Thanks to the Algorithm Economy, driving will also be cheaper, safer, and an integral part of the Internet of Things.