Insurers, Big Data and Changing Consumer Behavior

It’s not about having data, but what to do with it, right? Recently, someone suggested a new life insurance product to test out what would be a better fit for me than the traditional product I already had. The catch was that this new program would utilize the big data on my smartphone, connected devices and actually tracked my lifestyle, rather than relying on standards and doctors reports. True to my geek nature, I leaped at the chance to test this out.

While this program is not the first of its sort, technological maturity is starting to permeate where these devices are at hand, and the data is actually accessible. It’s becoming practical for both the insurer and the consumer. And as many questions of fancy technologies and paradigm shifts (such as Big Data and AI), once it becomes practical, then the market can start to truly shift.

Let’s be honest. Life insurance products are not innovative. And in most cases, they are standardized. They are based on probability. If the improbable happens and I drop dead, then the insurance will foot the bill for my family. For every such case, however unfortunate, there are millions where no payout is due, just the annual premium. Probabilities and statistic for a number of people are quite precise and predictable. And the more data and reliable information the insurer has, the better the algorithms at work can perform. So, just how much data do you have on your phone?

In this particular program, the insurer has built ways to leverage this big data, i.e. utilize the devices we carry such as the Apple Watch, the iPhone, Fitbit devices, sports and activity watches (Suunto, Polar, Garmin, etc.). By tapping into this data, the insurer gets reliable information and data; in return, you score a lower premium.

The bonus is that these apps add a lot of other values, from motivation to exercise, including education on eating habits and caloric intake calculations. But that’s the value-added, not the primary decision driver.

This new life insurance product is a simple end-to-end example, but it’s fascinating to follow it in real life. There are, however, a few other questions that come up from this use case. One is regarding the issue of adverse selection; the other is if this type of alignment of interests or subtle manipulation with incentives can be focused on biggest health related issues like obesity.

Will Data Polarize Market Behaviors?

Imagine that you’re an active tri-athlete who exercises daily. Would you give up your data to your life insurance provider? Most probably, you’d expect a positive effect. Now, imagine that you are slightly out of the game so to speak: imagine that you’re not a fan of doing exercise and you loathe visiting doctors. Would you be interested in giving up this data to your insurer? Maybe you’d think twice and even prefer the standard assumptions that your insurer would make.

What might self-selection like this get us in the market? Would the adage if you have nothing to hide, you hide nothing become self-fulfilling? The insurers will surely factor it into their data and algorithms. And even selection does end up a factor, how much privacy are you giving up in order to participate in a significant reduction of your annual premium. Will it be worth it? This is not just a specific theme for insurance, but of course a common question for data-driven products and privacy in general.

Having All This Data, Can You Actually Alter Behaviors?

Doctors have been riddled with the outbreak of obesity in prosperous nations. Could you as an insurer start having an impact on costly societal issues such as obesity by introducing ways to align interests even further with incentives and motivators? It’s actually a simpler formula than one might think. Fitbit makes a big deal of how the biggest value they provide is actually the motivation instead of just the device. Using the entire insurance program, could you have an effect on people’s behaviors, not only to report healthy trends but to eat healthily, exercise and monitor health habits? There is little data, yet the implications are vast.

You can turn that question around and ask yourself this: what type of incentives and motivators would you need in order to take up healthier habits? Badges and celebratory messages – sure. Extra perks – definitely. Money – that’s also on the table.

Incentives and Shared Goals

InsurTech has been a prominent topic in the news, and new innovators are finding ways to utilize the new paradigm to create new innovative products and services. Data availability is becoming far more profound and pronounced. And opportunities to align interests between those that utilize data and those that use the products are gaining momentum. Armed with reliable data and not mere self-filled questionnaires, service providers may come to trust the data they acquire and provide services they otherwise would not.