IT Best Practices.
How The Insurance Industry Uses Big Data And Telematics
Insurance premiums are based on a risk assessment of the insured. The greater the probability that a customer will file a claim, the higher his rates. If the insurer gets this risk assessment wrong, the company either loses money when the premium is too low, or loses safe drivers to the competition when the premiums are too high.
Insurance companies have traditionally relied on statistical analysis based on a limited number of variables. These variables are basic attributes such as a person’s age and sex. While the average 20-year-old male is a higher risk than the 40-year-old female, the cautious and careful 20-year-old male that rarely drives could be a lower risk.
The lack of personalized information is the weakness of using averages. The bell-shaped curve has a fair number of exceptional individuals well to the right of its middle section. These exceptional individuals represent an insurer’s best customers who dutifully pay their premiums and rarely make claims. To avoid losing these customers to the competition and to make the system more equitable, some insurance companies are offering a pay-how-you-drive system that bases premiums on the customer’s individualized driving habits.
The Pay-How-You-Drive System
This system makes use of a telematics device installed on the customer’s car that sends GPS information as well as sensor readings of acceleration, braking, cornering, and gas consumption. Aggressive drivers tend to accelerate, corner, and brake hard while safe drivers have the opposite profile. Risk assessment can be further refined from the number of miles driven in what locations and at what times of the day or night. This assessment is both real-time and individualized.
This system also benefits the poor risk customer who wants to change his ways. With the pay-how-you-drive system, the high risk customer doesn’t have to demonstrate years of good driving history before seeing a reduction in his premiums. Some insurance companies provide their customers with useful feedback by allowing them to view their telematic data. The feedback literally teaches the customer how to drive safer.
Big Data Benefits
Telematic devices generate a lot of information. Date, time, speed, position, acceleration, mileage, and fuel consumption data points are generated every second. It is not hard to appreciate the magnitude of information that must be processed by an insurance company with a large customer base. Progressive Insurance for example, has over 1.6 million customers that have generated more than a trillion seconds worth of driving data.
While big data technology greatly facilitates this data handling problem, it also promises other benefits that extend beyond the current pay-how-you-drive system. Thanks to the greatly expanded customer database provided by telematic devices, big data analytics can refine risk profiles to an unprecedented level. Hundreds of new variables can be incorporated into risk models that provide more accurate forecasts of the future driving behavior of an insurance applicant based on his past. Such a model will better assess how the cautious and careful 20-year-old male stacks up against the middle-aged business man who makes frequent business trips with his car.
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