A question of driving big data

How is insurethebox using big data to compete in the motor insurance market?

Brockman: We have developed a brand new motor insurance product which was launched two years ago in one of the most competitive markets in the world. Since then we have sold 100,000 policies. The essence of our product is a telematics device installed in the customer’s car that provides instant feedback on driver behaviour allowing us to adjust risk and customer premiums accordingly. The telematics box captures data on the number of trips, durations of trips, rest stops, g-forces, speed and location. Every month we accumulate 30 million miles of data, and customers are incentivised to review and improve their driving behaviour.

Is this approach to motor insurance proving to be disruptive in the insurance market?

Brockman: Undoubtedly. When we first launched the product there was some scepticism about whether we could recover the additional costs involved and there was speculation that drivers would be reticent about having their driving patterns monitored. But these concerns proved to be groundless and now many insurers are examining the feasibility of this approach. Our initial focus has been on inexperienced drivers as this is a segment that can benefit most from feedback on their behaviour and it was also a group that found it difficult to secure affordable insurance.

What are the main challenges of managing a data-driven business?

Brockman:As an actuary with experience of the traditional insurance model, I have found that this is a very different way of doing business. We can now actively influence customer behaviour and manage risk in a much more sophisticated manner. Other aspects of the business, such as claims management, are also impacted by the data because we now have detailed data on all accidents that allow us to protect the business (and our customers) from fraudulent claims. The technological challenge of managing the data has proved to be fairly effortless; the data warehouse runs on an IBM Netezza Analytics Appliance.

What was the most interesting data pattern that you have discovered?

Brockman: Perhaps the most interesting thing to be uncovered during the past year was an alert raised in the service centre when an insured vehicle experienced a very high g-force and was then observed to be stationary with the ignition switched on. We tried to reach the customer by telephone but received no answer. The location was a rural lane in Exeter and we were concerned that an accident had occurred and we reported the incident to the emergency services. When they arrived at the scene they discovered that the car had left the road, rolled on its side and that the occupants were trapped inside. It might have taken a number of hours for the accident to be otherwise reported. What is interesting about this case is that the current procedures of the emergency services do not provide for reports to be made by on-board telematics devices, but it is probable that this will become the norm in future years.

Can you see further possibilities for product and service innovations using big data?

Brockman: Once you become accustomed to viewing data as an asset, all kinds of possibilities can be imagined. The data can be used to customise value propositions to different customer segments and the data can also be used to expand the range of information services that can be provided to customers. These might include maintenance alerts, monitoring of fuel consumption and performance information for fleet management. We are also exploring the possibilities for linking the telematics box to the car’s on-board computer and developing mobile applications to provide real-time feedback to customers.