Smartphones have powerful sensors. The accelerometer and gyroscope measure how we move and can pinpoint the phone’s position in space. They’re assisted by GPS, which provides the phone’s location. The magnetometer measures magnetic fields while the barometer measures air pressure. The proximity sensor determines how close the phone is to nearby objects and the ambient light sensor measures the amount of light near the phone.
If you take this raw smartphone sensor data, fuse it together, and feed it through machine learning algorithms, you can open a world of driving behaviors never seen before. You can identify the mode of transportation and know if a person is on a plane, train, bus, bike, or car. For example, if a person is on a bus, the magnetic signature will be much heavier than a car, there will be more Bluetooth signals, and they’ll follow a predetermined bus route. Once you know a person is in a car, you can tell if they’re the driver if they rotate 90º counterclockwise to enter the car (and the reverse when exiting) and if they’re in the front seat by the vibrations created by the front and rear axles when going over bumps in the road.
Smartphones can also reveal driving habits. Like connected cars, smartphone data can show how frequently a driver brakes harshly, accelerates quickly, speeds, and where and when they travel, and where they park. But, unlike connected cars, the smartphone provides data at an individual level, so insurers get personalized data for all their customers, making it easy to distinguish between a parent and a teen driver.
If this were the full potential of smartphones, there would already be a strong argument for carriers to use them for their digital programs today over connected cars. But smartphones deliver much more than driving data.
Smartphones sensor data also reveals distracted driving. You can see where the phone is in the car – in the cupholder, on the seat, on the dashboard in a mount, against the driver’s ear, or in their hand. You can see if the driver is actively using their phone, texting, making a phone call, or using apps like Facebook. You can see passive phone use, like listening to music, or navigating with Google Maps. This is data connected cars won’t be able to easily provide.
Distracted driving is a national epidemic, killing over 9 people every day. But beyond the daily tragedies, it’s also a business challenge for insurers, dramatically increasing their loss ratios. Due to the increase in frequency and severity in crashes, we’ve found that every 1% increase in distraction in an insurer’s book increases their loss ratios by 2%. As a result, insurers can better price risk when they include distraction in their analysis. They can even try to reduce distraction with data-driven safe driving programs. Whatever their goal, an insurer will want distraction data, even if their customer is driving a connected car.
Smartphones take next-generation claims even beyond the promise of connected car data. This is because you can create personalized movement signatures for behaviors that happen outside of the car with smartphone data. For example, smartphones can reveal how a person walks before and after an accident. If their walking signature is the same after an accident we know that they didn’t suffer major injuries, and can account for it in fraud detection. We can also use smartphone data to see what a driver does immediately after an accident. Do they get out of the car, walk around, take photos of the scene, get back in the car, and then drive away? If so, there’s no need to deploy an ambulance or tow truck, and the insurer will know if they need to investigate deeper if the driver claims any major injuries.
Beyond personalized driving, distraction, and movement data for every customer, the smartphone provides insurers with a new and intimate channel for communications. Even with connected cars, carriers will want an easy to way to connect with their customers – in and outside of the car. The opportunities are endless, but here are a few examples. Imagine your insurer knows the typical route you take to work and when you leave the house. They could notify you when there’s extra traffic, dangerous driving conditions, or a deal on gas or coffee along the way – before you leave the house. Or, in a scarier scenario, if you get in an accident your insurer could automatically send your loved ones a text message and provide updates with crash-scene and location data. If an ambulance takes you to the hospital, they could provide alerts on your location and let them know when you arrive. In a lighter example, people love competitions, and could receive push notifications when they fall behind or jump ahead in a safe driving group challenge. Regardless of if an insurer gets the data from the phone or the car, the phone will continue to be the platform for personalized communication.
With scalable, cost-effective, and personalized driving, distraction, and movement data, not to mention a new, personalized, data-driven communications channel, the smartphone is the ideal platform for next-generation digital auto insurance programs. And, unlike the connected car, 85% of drivers have a smartphone today.
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