For years now, telematics has been used in both business and personal vehicles for everything from asset tracking to fleet management to general safety. Users of the popular OnStar service know that through telematics, car doors can be unlocked remotely, emergency personnel summoned in the event of a problem, and so on.
The arrival of the connected car, long touted by the automotive industry as the Next Big Thing, has increased both consumer appetite for, and acceptance of, in-car connectivity. While telematics is possible without the types of features marketed so heavily by manufacturers today, the introduction of mobile communications inside the vehicle offers opportunities to collect new levels of data that can be accessed in real time. For insurance companies, this translates into the ability to create an enhanced and more granular view of the driving habits of their customers.
Insurer firms rely on drivers’ behavioral information to understand expected claims costs and set prices accordingly. Until recently, such information about driver behavior was primarily restricted to police ticketing, accident history, and certain assumptions made by taking into account the driver’s age, gender, address, credit history, and even the color and other details of the car. While these metrics are helpful in painting a picture of a driver’s performance, they are limiting in that the information is:
- Not directly related to driver behavior or weakly correlated at best
- Overwhelmingly negative in nature, meaning insurance companies can only use them to punish a driver for poor performance, as opposed to rewarding them for adopting safe driving habits
- Available for only a small subset of drivers who have committed offenses
- Backwards-looking, meaning that a risky driver is only identified after a driving issue arises
Telematics and big data change all of that, offering insurers a deeper peek into more detailed driving characteristics such as the speed at which motorists drive vis-à-vis the posted speed limit, cornering and acceleration tendencies, frequency of hard breaking, time of driving, etc. Insurance companies today have a new opportunity to collect and analyze behavioral data, better assess a particular driver’s risk, understand future risk factors, potentially weed out undesirable customers, and arrive at more accurate policy pricing.
Insurers can also use this information, not just to punish offenders, but also to proactively reward and incentivize good drivers with discounted rates, potentially earning greater customer loyalty and brand affinity. It also offers the insurer more positive touch points with the customer during the lifespan of their relationship.
There are three primary components required for telematics to become an effective tool for insurers. The first is the car itself. It must have the ability to measure performance and behaviors against the tracking metrics outlined above. The second is the connectivity aspect and the ability for data to be sent and shared with the insurer. The third is the analytics layer; that is, the ability to assimilate, correlate, and convert the collected data -- a fairly high volume of it -- into something that is practicable.
Saurabh Sharma is founder and CEO of Indus Insights, a leading Big Data consulting firm specializing in helping organizations use analytical and statistical techniques to improve their performance.