A data-connected automobile generates some 25 gigabytes of data every hour. That’s equal to about a dozen HD movies and more than the storage capacity of most smartphones.

We know what the car is telling the network–everything from route, speed and even road conditions. Vehicles today have about 40 microprocessors and dozens of sensors that collect telematics and driver behavior data, and that data can be analyzed in real-time to keep the vehicle’s performance, efficiency and safety in check.

How do insurers effectively use telematics data?

It would be unwise and impractical to just dive into all those gigabytes of data and most companies don’t have the capacity to do so. For insurers to benefit from driving data, you will have to aggregate the data first and then categorize it by extracting certain features from the data. An example of feature extraction could entail calculating the percentage of a certain vehicle driving in a specific area such as a rural area vs an urban area or on a highway. The data that comes out of the feature extraction process must then be integrated with the established data your company has used to write policies (claim history, age, place of residence, etc.) into a system that combines them both. After the data has been gathered and unified, the data needs to be analyzed using robust quantitative methods. With the right analytical software solutioninsurers will have the power to move data insights into actionable, bottom line savings, improved efficiency and better claims experiences for customers.

In other words, it’s time to merge the old world of insurance underwriting into the new world of telemetric data gathering. Armed with telematics data, insurers can improve their risk based pricing by being able to assess the true risk profile of drivers. Furthermore, we have seen insurers using telematics data to create reward based programs. These have included the following programs

  • Status reward program: similar to airline frequent flyer programs, drivers are given discounts and special offers based on their status or the status group they belong to in the program. However, instead of flying miles being used to achieve a higher status, a driver’s good behavior allows them to earn more points.
  • Pay as you drive (PAYD) Pay how you drive (PHYD) and mile-based auto insurance programs: these program are dependent upon the type of vehicle that is used or measured against time, distance, behavior and place. For example, the more a driver is on the road, the more he has to pay. With telematics data, the frequency of driving can be monitored and used in calculating the driver’s payment rate.
  • Cash back, rebate and coupon programs: over a certain period, a driver can accumulate points for good driving behavior. At the end of the period, the driver can receive cash back, rebates or coupons on his insurance policy if he qualifies. If his driving is below par, this may impact his insurance rate for the next period.

Telematics adoption is inevitable

Yet merging the old and new worlds, is easier said than done when many actuaries and statisticians may put up some resistance. Resistance to telematics, however, is futile.

That’s because usage-based insurance (UBI) policies derived from telematics data are poised for rapid growth worldwide. In the Europe, all new passenger cars and light vans in the EU will need to be equipped with an automatic emergency alert system called eCall from March 2018. Businesses across the globe that don’t use this technology will fall seriously behind their competition. In the United States about 70 percent of all auto insurance carriers are projected to use telematics by 2020. A survey of 47 U.S. state and territory insurance departments found that in all but five jurisdictions insurers currently offer telematics UBI policies.

Using actual data that can answer when, where, how and how frequently a vehicle is driven is a much more accurate way to measure risk and price insurance policies than using age, history and location. Progressive Insurance, a telematics pioneer has found that telematics data is significantly more powerful and has provided a large improvement in the firm’s accuracy of rating policyholders.

Yet the migration to using telematics data will not happen immediately. Insurers rely heavily on their current data for calculating risk premiums, with established systems in place to use the data as is. At least in the beginning, while telematics data is still in its infancy, this data will be considered as supplemental rather than foundational. During this transitional phase, insurers can use the time to find ways to integrate this new data with their old data, as well as set up the necessary analytical software platforms to make the most of the data. Over time, the insurance market will gain confidence and establish new rules of engagement using telematics and the insurance world as we know it will change forever.

Another important thing to keep in mind as you work to merge traditional underwriter metrics with new telemetric information is that all this data might not reveal what you would expect. For example, that 20-year-old new male customer who just bought his first car may be driving considerably more safely than a long-term 55-year-old man who’s never had a fender bender but who just started going through a mid-life crisis and is now driving in a much riskier manner?

I expect Eran Shir, co-founder and CEO of Nexar—and one of the keynote speakers at the 2017 Earnix Analytics & Innovation Summit—to hit upon these trends when he addresses attendees this November. Data will be the new oil of the automotive industry as it transitions from a hardware-centric to a data-centric model. As Shir likes to say, we are no longer talking about cars with central processing units, but vehicles as computers with wheels.

So while everyone agrees that telematics is a game changer in the auto insurance industry, many insurers have yet to build a reliable ecosystem to support this new technology. Finding the right analytical software and technological platforms to analyze the data will be key to being at the forefront of the insurance industry. Those insurers that can learn to harness analytics will ultimately improve their understanding of risk, pricing power, and claims loss ratios.

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