Telematics and Fleet Insurance

A few years ago I did some research on telematics. At the time, an insurance underwriter in the UK was exploring the idea of using telematics data to price automotive and fleet insurance. Since then, underwriters have started using GPS/telematics to price automotive insurance. Progressive Insurance has a program called Snapshot where it mails a telematics device to a customer who then installs it in his car and Progressive tracks the data for 30 days. If the data from the device shows the customer is a safe driver, the driver is eligible for discounts of up to 30 percent.

A few weeks ago, one of my colleagues handed me a brochure he had received in the mail for a trade show called Insurance Telematics USA 2012. One of the keynote speakers was James Noble, the Line of Business Director for Motor Fleets at the Zurich Services Corporation. Jim’s job is to provide fleet operators with products and services aimed at identifying and reducing losses.

Insurance coverage for a fleet is based on the overall risk, including drivers, equipment, and company practices. In order to obtain a good risk profile, the data from telematics needs to be combined with other data, including CSA data and motor vehicle records that document the behavior of individual drivers (speeding tickets, violations for not wearing seat belts, etc.), past crashes at both the fleet level and the individual level, and even driver observation data. So, for example, if the trucks have writing on the back that says “How is my Driving?” and provides a 1-800 number for people to call in, this data can be used as well.

But telematics is an exciting new source of risk data. Historically, when insurance companies tried to predict which drivers were dangerous, they used lagging indicators – speeding tickets, a crash occurred. Telematics data is more immediate; you can monitor how drivers are actually behaving. And here again, more data is better. A telematics device that can provide data on hard braking, hard cornering, hard acceleration is better than a device that only provides data on speeding. Even idling data might be useful one day; it might show if a truck is in a high theft area and how long it remained in that area.

But the single most important thing for fleet operators to remember is that improving their risk profile depends far less on the possession of telematics devices and far more on how the data from these devices is used to change driver behavior. Is the data actively monitored? Are individual drivers coached if their driving is not acceptable? Are drivers who refuse to change bad driving behavior fired? These are the things that matter.

Jim also stresses that using telematics data for insurance purposes is still in its infancy. “We’ve only scratched the surface regarding how telematics information can be used to predict behavior.”

Comments

  1. State Farm has another twist on this subject. State Farm has an iPhone app that uses the accelerometer in the phone to track hard acceleration, hard stopping and hard cornering. State Farm notes these three driving habits are directly linked to drivers with higher-than-average accident rates.

    State Farm states they do not collect data from the app. Consider the app the camel’s nose under the tent – not only for State Farm, but other insurance companies.

    Here are links about it:
    http://www.engadget.com/2011/05/02/state-farm-app-uses-iphone-sensors-to-grade-your-driving-habits/
    http://www.autoweek.com/article/20110504/carnews/110509934

    The GPS functionality in a phone could be used to track vehicle velocity, too.

    I envision a future where insurance companies’ linking measurable driving behavior to insurance premiums will do more to incent safe driving than all the radar traps in the world. This is especially true if they share this driver information in a common industry data base. People will be motivated to driver safer and/or turn off their phones while driving.

    The beauty of this, from the insurance company view, is data collection is very low cost.

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