With the driver as the central underwriting focus, it's ironic that the vast majority of telematics devices have focused on the vehicle. Onboard diagnostic devices that plug into the vehicle only measure the car. Any driver can be behind the wheel.

Conversely, the smartphone facilitates the first insurance UBI platform focused on measuring the driver's actions. The great thing about smartphones is they're personal and rarely left behind. In fact, according to ZipCar's annual millennial survey, 40% of millennials believe that losing their phone would be a bigger hardship than losing their car, TV or computer/tablet.

2. Complete or fragmented view?

Brilliant: Gaining an interrupted, continuous picture of the driver's activity
Bombing: Measuring only a fragment of what really happened

One would assume that a 360-degree view of driver activity provides a more accurate basis for underwriting than a 180-degree view. Let's examine this hypothesis using Jack's situation.

• Jack drives his own Honda Accord. Sometimes his girlfriend Hannah also drives his car.
• Hannah drives a Toyota Forerunner. Jack drives the Toyota whenever the two are travelling together.
• Jack also frequently drives his parents' Suburban.

What portion of Jack's driving activity can be viewed and analyzed by an insurer?

If the insurer uses an onboard diagnostic device (OBD), it will collect data when Jack drives his Honda Accord. It also will collect data when Hannah drives the Honda Accord. The two sets of data will be integrated as one. Instead of seeing Jack, the insurer will analyze, rate and price for Jack-Hannah. Jack's activity in the other vehicles will never be considered.

If the insurer uses a smartphone-UBI platform, it will collect data on Jack's activity in all of the vehicles he drives, as long as he has his smartphone along.

What if Hannah is driving Jack's car? Over time, through sensor-fusion technology, machine-learning and pattern recognition, smartphone-UBI platforms will have the ability to develop a unique signature for each driver, and detect deviations from normal driving pattersn for each driver.

Moving beyond the issue of multiple drivers and vehicles, significant data gaps occur with OBD monitoring, such as:

• Vehicle speed is often measured by on-wheel sensors, which can vary by up to 20% based on inflation levels and other factors.
• Speed values read by an OBD device are not time-stamped, making it difficult to reconstruct what happened.
• Drivers can unplug the OBD device at any time.
• Data gaps occur when the OBD device fails to connect with cell towers at trip inception often due to variation in the OBD sleep-mode wake-up variances in different car models.

Smartphone monitoring has opportunity for data gaps as well. Most notably, if the smartphone app requires the user to turn the app on and off, the insurer may not get the complete picture. Fortunately, some smartphone apps have auto trip detection overcoming this challenge. Likewise, if the driver turns the phone off completely, tracking is interrupted. However, the UBI platform will record the exact time and location the app was turned off and on again, allowing for time and distance gap handling.

Cell service availability is generally not an issue for smartphone-UBI. The smartphone is equipped with an internal memory thousands of times larger than that of an OBD device, allowing it to store up to two weeks of average driving data. Smartphones are designed to seek out data connections when they are available, so UBI driver data is automatically uploaded to the cloud as soon as the driver re-enters cell or Wi-Fi range.

3. Is Information Actionable or Just Accessible?

Brilliant: Starting with a data “control” group and an established scoring algorithm
Bombing: Starting from scratch and waiting two years for enough actionable data

Whether you measure speed from an OBD device or a smartphone, a record is created every second. In 60 hours of driving, 216,000 records are generated–and that's just for speed monitoring. However, this vast amount of information is useless until it is translated into human parameters.

That's where actuaries come in. How long will it take them to develop a scoring algorithm? How will they translate the data into rating parameters? What will they compare data against?

These are formidable questions, unless you have a UBI platform that already has collected substantial driver data that you can use as your “control” and already has established a scoring algorithm that you can use as-is or adjust to your specifications.

In the case of our driver Jack, you can present your actuaries with hundreds of thousands of individual records and let them figure it out. Or, you can present them with Jack's average driving score of 82 out of 100, along with supporting data and control data to compare against. When Jack's driving data is compared to that of other 23-year old males in California, he can be punished or rewarded via a rate increase or decrease based on his deviation of norm.