Unlocking the Value of Performance Data in the Insurance IoT Ecosystem

What do marathons and insurance have in common? The short answer is: performance data. Every time a world class runner finishes a race, performance data is generated. Her size, training habits, age and diet are all predictors about how she or her peers might perform in the next race. Every race adds richness, reliability and value to each single data point. These data points enhance training schedules and dietary models, and create efficiencies that lead to improved future performance. Performance data in insurance works the same way, and leveraging that performance data within IoT strategies is the key to understanding its predictive value.

Performance data feeds predictions

As an insurer, you are in the business of making predictions. And those predictions feed pricing models that generate the payment schedules to which individual policy holders agree. The performance data that you rely on to make those predictions includes claims history, driving behavior and insurance history. It’s impossible to predict with certainty the future claims activity of a single home built in 1997 with three bedrooms and three water claims in a single zip code. But it becomes easier to predict future claims activity of hundreds of homes of a similar profile, and becomes increasingly easier to do it with hundreds of thousands of similar homes.

But what does that have to do with the Internet of Things (IoT) and insurance? Well, if we want to understand the predictiveness of certain sensors in a home, we need performance data. The effectiveness of a “smart” security system and its companion smart phone app, or a water leak sensor can only be understood by seeing how homes with those devices compare against those without them. To compare the two, we must ask certain questions, such as:

• What are the claims trends of each group of homes?
• What are those trends saying about the devices’ preventative power, or the homeowner’s level of conscientiousness (i.e. self-selection bias), or likelihood of adopting and installing a device?

Other performance data that matters to IoT is insurance history (think shopping, switching and retaining). For example, if insurers are to build strategies around shipping branded sensors and devices to policy holders, won’t it be important to know what impact those investments might have on your retention rates? Those stories can only be told through performance data.

The data is readily available

The good news is that you have your own performance data—the claims and insurance history of your policy holders. That’s a big deal, as you can begin overlaying those data points on top of whatever IoT data you are already collecting, and then researching where that might fit into your rate plans and customer experience strategies. Carriers that have not begun that process are falling behind. But you may be asking what happens with a customer or a risk that hasn’t been on my book of business for very long? How do I account for them in my models since I have very little performance data on those folks? Well, (clearing my throat here)…that’s where we come in. When you look at IoT, you need data. Not only device data but also claims and insurance history data.  But all you have is the claims and insurance history data of your own customers and whatever limited IoT data you may (but probably don’t) have.  That’s why you need us, because we have industry data, and IoT data.

Bridging the data gap

For a single insurer working with a single device manufacturer, that’s not a terribly daunting challenge. But how do we bridge the gap between this wildly expansive ecosystem of IoT devices and platforms, and the insurance market? (Insert more throat clearing here…) We are here to solve those challenges. We have made a business out of bridging the gap between ecosystems and insurers across thousands of data sources, for hundreds of use cases. Just as we’ve done with telematics in our connected car business, our IoT exchange will behave like a marketplace where device manufacturers can monetize data. We marry that data with performance data to create attributes and models that you can use for rate making, claims handling and customer selection; and consumers can use for deeper discounts, better claims processing and an overall richer insurance experience. And the good news is that in a recent survey, 78%¹ of consumers with smart devices said that they are ready to bring their smart home data into their insurance transactions.

Unlocking the meaning

So, if you’re an insurer with IoT data and you want to unlock the insurance meaning behind it, our performance data can help. Initially, that might mean simple claims trend comparisons that eventually lead to production-grade opportunities like real-time device validation platforms offered by your existing data partners (that’s the final throat clear, I promise).

For device makers, it starts with having the proper consent to begin leveraging device data in new ways that benefit your customers. For insurers it likely means widening the scope of your existing trials and then digging into the data in a more robust way. If you are looking to unlock the power of your data and strengthen your predictive models, contact your representative today, or call us at 800.869.0751.

1. LexisNexis Internal Study 2020. To Download the Study Click Here