Digital Insurance spoke with Dan Campany, vice president of innovation and head of IoT at
The Hartford's IoT executive talks tech use for prediction, prevention
Published September 15, 2022 6:30 AM
1 Min Read
What is the mission of the IoT Innovation Lab?
Dave Everett Imagery
What IoT devices have proved relevant and useful for the lab’s work?
To prioritize which types of technology and which customers to work with, we look at our loss data and understand what types of losses our customers are experiencing that we believe could be preventable or could be predicted. As a result of that analysis, we've prioritized sensors like water damage prevention technology , both at a personal level in the home and at a commercial level on construction sites, large office buildings, schools and universities. Each of those requires nuance in the technology and how we work with those customers to set up an effective water damage prevention technology system.
In addition to water damage prevention, we are looking at worker safety, which includeswearables for ergonomics . It also includes computer vision, where artificial intelligence can effectively watch video streams and identify risky things like forklifts that are doing donuts in the warehouse or workers who are jumping over assembly lines. We can use those insights to work with those customers to help make their operations safer for their employees.
We are also looking at commercial fleet telematics. Most think of telematics as a personal lines thing today. But we believe there's a ton ofopportunity in commercial fleets. That technology includes not just the data that you can get off a mobile phone app, but also includes in-cab cameras that face both at the driver and out towards the road to understand the real-time conditions. Is the driver distracted or drowsy? What kind of traffic conditions are they facing or weather conditions are they facing? We can use that data in a lot of different ways both in helping them be safer, but also if a claim does happen, understand what happened, why and who's at fault.
In addition to water damage prevention, we are looking at worker safety, which includes
We are also looking at commercial fleet telematics. Most think of telematics as a personal lines thing today. But we believe there's a ton of
Does a lot of your IoT effort go into working with the policy side at The Hartford?
The way we are set up, the IoT lab is designed to be an incubator of ideas. We source the ideas from our own research, from our loss data, from our underwriters, from our risk engineers. We take those ideas and frame them into a vision. We extract the key hypotheses for the idea to be successful at a meaningful scale. Then we experiment on a smaller scale with five, 10, 50 or 100 customers to really test the idea in the marketplace.
If that is successful and we can figure out the process, the economics, the technology and the customer experience, we take those ideas back to the business units as '90% baked,' something compelling to scale and operationalize within the business. We work with them to transition that capability into the core business. Sometimes that's as simple as risk mitigation and using our risk engineers to go out and install devices. In other cases, that's, 'Hey, we're getting telematics data and we think that can be used for pricing segmentation.' That gets more into the risk selection, the policy structure and how we use it in our rating models.
If that is successful and we can figure out the process, the economics, the technology and the customer experience, we take those ideas back to the business units as '90% baked,' something compelling to scale and operationalize within the business. We work with them to transition that capability into the core business. Sometimes that's as simple as risk mitigation and using our risk engineers to go out and install devices. In other cases, that's, 'Hey, we're getting telematics data and we think that can be used for pricing segmentation.' That gets more into the risk selection, the policy structure and how we use it in our rating models.
What impact on policies do you anticipate from this research and the invention of these systems and methods?
At a very broad level, we're trying to take losses and take risk out of the equation. The insurance policy is a financial backstop for things that can't be prevented from happening. We aspire to take those preventable and predictable risks out of the system, so we only need to lean on the insurance policy as a financial backstop for the truly unpredictable or unpreventable claims. Because of the investment we're making to prevent claims from happening, over time we expect to be able to recognize that in the way we price the policies that we offer our customers.
What is the most important thing for carriers to gain from the lab?
The capture and analysis of the data is a key component for IoT innovation, long term, for carriers to get the full potential, not just subsidizing devices for customers to deploy. Using the data -- with consent, of course, from the customer – can create more value for us and for the customer. The data from IoT is unlike the historical data that insurers use, because it changes in real time second by second. There's a very high volume of it. It's very complex.
Take wearables as an example, where data is coming from many different sources. We have many different wearable partners and all their data looks a little bit different. The same is true in telematics. The work around harvesting the full value of devices from a data perspective is not inconsequential, but it is a critical part of unlocking the full value in terms of how we understand that risk at a more granular level, and how we adjust our pricing and deliver new products based on it.
Take wearables as an example, where data is coming from many different sources. We have many different wearable partners and all their data looks a little bit different. The same is true in telematics. The work around harvesting the full value of devices from a data perspective is not inconsequential, but it is a critical part of unlocking the full value in terms of how we understand that risk at a more granular level, and how we adjust our pricing and deliver new products based on it.
