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By Rob MacKethan

Better driver analytics can reduce fraud and improve risk management.

You may have noticed a lot of buzz about driving analytics lately, and for good reason. Driving analytics are primed to change the way vehicles and drivers are insured, and even conceivably change the way individuals drive, for the better.

I’ve put together a ten point primer to help you better understand this technology and its impact on the industry.

  • What is driving analytics? Also referred to as telematics, driving analytics tracks driver data like distance driven and location. By using this technology, a fleet owner could know where all her trucks are at any time, for example, or an insurer could know how safely his insureds are driving.
  • Driving analytics has become driver analytics. In the past, driving analytics has been a physical dongle, called On Board Diagnostics (or OBD), which plugged into a car or truck. It collected data like the number and location of miles driven and speedometer readings. Today, driving analytics has turned toward driver New phone-based systems can also measure risky behaviors like distracted driving, and follow a driver between multiple cars. What’s more, phone-based analytics capture more types of data and are more accurate than old school dongles.
  • Better driver data means better risk measurement. Ninety percent of all collisions are due to human error, so measuring the human instead of the car makes sense. Leading actuarial firm Milliman found driver behavior is up to six-times more accurate at predicting collisions than the insurance industry’s standard methods. In addition, we know that factors like phone use while driving contribute to about 26% of collisions, and that the amount of distracted driving on the roads is about 100x worsethan we thought. That’s a lot of risk to measure.
  • More insurers are using driving analytics than ever before. Progressive was the first to pioneer this technology, years ago. Today, technology that sits on a phone makes it easier for both consumers and businesses to deploy the tool, so they can get savings from improved risk analysis. It’s no wonder the trend is expected to more than double by 2021, as Progressive is joined by Allstate and State Farm, and even automakers like Mitsubishi and Ford are sharing data with insurers.
  • Not every driver is excited about driving analytics with their insurance. Some drivers are wary for reasons of privacy, or because they don’t want the risk of higher insurance prices. In the consumer world, there are apps from auto insurers that offer discounts, but they are only 4% of policies sold today. In the commercial world where employees expect monitoring, driving analytics-based insurance is growing faster.
  • Driving analytics doesn’t have to mean Big Brother. Driver analytics comes in all shapes and sizes. In many solutions, no personally identifiable information is stored (PII). Privacy laws in many countries limit what can be done with driving data. And, some tools use data analytics to help train new drivers and don’t share the analysis with anyone but the user. Others automatically call a family member if they detect a collision.
  • Driving analytics will drop most people’s rates. A recent study shows that the bottom 25% of a fleet’s drivers account for 50% of collisions, which means that the top 75% of drivers are subsidizing them. Driving analytics helps insurers make individuals’ or even fleets’ pricing more fair, which usually means lower.
  • Driving analytics can reduce risk. Not only can an insurer choose to only insure better drivers, but driving analytics can also reduce risky driving overall. When a fleet used the technology to see which of their drivers drove poorly, they targeted them with a coaching program to improve. Not only did their risk of a future collision drop by 49%, but they also reduced their employer’s losses. This type of coaching can translate to anywhere from $874K to $2M of estimated reduction in losses for bodily injury and property damage liability per 1000 risky drivers per year!
  • Driving analytics can reduce fraud, too! Someone who drives for a ride-hail service wouldn’t be able to say that a collision occurred on company time if it was actually detected when they were off duty. A driver who claims another driver smashed into them while they were stopped at a light would be caught easily if they were going 90 mph at the time. Since all this data is automatically recorded it also makes claims filing much easier and faster, leading to a better customer experience.
  • Driving analytics in insurance will only grow. As companies see massive improvements in their risk analysis platforms, the savings for insurers, brokers, and drivers alike will only increase. As it helps improve the customer experience by making insurance more transparent, and helping reduce overhead and fraud in claims filing, driving analytics makes more and more sense. And as social norms lean towards sharing data to get better service (see social media and digital assistants), insurance customers will be more comfortable using this data measurement.

Driving analytics is here to stay, but rest assured it can and will  improve all parts of the insurance experience.