Predictive Marketing Blog

Insurance for the Invisible Driver

Google’s self-driving car tests have logged more than two million miles and many other companies are following suit. General Motors has predicted that autonomous vehicles could be commonplace as soon as 2020. Driverless cars are no longer just a concept; they’re about to be a part of everyday life. Insurance companies face a much different market when they’re providing services for the invisible driver, with new considerations factoring into the products offered. Let’s take a look at how the landscape for insurance and autonomous vehicles is evolving.

Reduced Insurance Costs

From rear ending someone to falling asleep at the wheel, human error causes 94 percent of car crashes. When computers drive the cars rather than people, you remove this risk from the equation. While Insurance companies have always adapted to new automobile technology one element has remained constant: the driver. Insurance products that today revolve entirely around this [driver] premise won’t translate well for invisible drivers and the change could lead to a 30-percent reduction in premiums for consumers.

The insurance industry has to predict additional risks present in the driverless future, such as the potential for hacking or a program bug, as well as the changes in the interim where autonomous vehicles share the road with humans. Another question these companies must answer is where the car manufacturer falls when it comes to liability. Insurance companies are operating on limited information, but need to start preparing for the future now.

How Insurance Companies Historically Used Data

Insurance companies use a risk assessment to calculate the premiums for each driver. Multiple data sources allow you to calculate the likelihood of someone being in an accident, the average claim cost, and other factors that influence how much the consumer should pay for car insurance – including the driver’s credit score, where higher scores can equate to lower insurance rates, and even if you have a garage for your car. Drivers are also placed in risk pools, such as people with no accidents or those who have multiple traffic violations, which also affect premium rates. This historical approach centers on the individual buying the insurance and doesn’t work in the driverless future.

Adjusting to the Driverless Landscape

For the insurance industry to align their services with this evolving technology, they will have to add in countless additional data points into their risk calculations. Everything requires consideration, from the type of software the vehicle uses to the sensor placement to who is responsible in the event of an accident – the person, the vehicle or both. Insurance companies also need a way to gather real-world data and analyze it to create new risk pools for autonomous cars. Progressive’s Snapshot and Allstate’s Drivewise are examples of this data gathering initiative in action.

What is the key to making this leap? Auto insurance companies must gather and prioritize the right data to help determine and underwrite risk in the driverless economy. While companies may have loads of data at their disposal, just throwing in more data points won’t improve data modeling; insurance companies need tools to data mine the vast amount of data they’ll have for the right data to help them make decisions. And to really put this information to good use, insurance companies need to employ predictive analytics tools to work with data in real time. Instead of waiting weeks or months for reports, predictive tools analyze the right data as they continually adjust to new developments in technology, adoption rates, and a significant shift in driving habits. The outcome is more accurate risk calculations and a competitive advantage.

The automobile insurance industry is about to experience its biggest shakeup ever. Are you prepared with the right tools to take advantage of the new driverless landscape, or will you have to play catch up? Implement predictive analytics tools now so you stay one step ahead of this shift.