Author: Monique Hessling
Recently I had the pleasure to work with SMA’s Mark Breading on a study about the development of smart cities and what this means for the insurance industry (Breading M, 2017. Smart cities and Insurance. Exploring the Implications. Strategy Meets Action).
In this study Mark touched on a number of very relevant smart city related technical developments that impact the insurance industry, such as driverless cars, smart buildings, improved traffic management, energy reduction, or sensor-driven better controlled and monitored health and well-being. Mark also explored how existing risks and how carriers assess them might change, and how these might be reduced due to new technologies. However, new risks, especially around liability (think cyber, or who is to blame for errors made by technology in a driverless car or in automated traffic management) will evolve. Mark concluded that insurers will have to be ready to address these changes in their products, risk assessments and risk selection.
Here in the USA, the last weeks have shown again how much impact weather can have on our cities, lives, communities, businesses and assets. We all have seen the devastation in Texas, Florida, the Caribbean and other areas and felt the need to help. As quickly as possible. Insurance carriers and their teams too go out of their way (often literary) to assist their clients in these overwhelmingly trying times. And I learned in working with some of them that insurers and their clients can benefit from “smart city technologies’ also in times of massive losses.
I have seen SynerScope and other technology being used to monitor wind and water levels, overlaying this data with insured risks and exposure data. Augmented with drone and satellite pictures and/or smart building and energy grid sensor data (part of this is often publicly available and open), this information gives a very quick first assessment of damage (property and some business interruption) to specific locations. I have seen satellite and drone pictures of exposures being machine analyzed, augmented with other data and deployed in an artificial intelligence/machine learning environment that by using similarity analyses quickly identifies other insured exposures that most likely have incurred similar damages. This enables adjustors to proactively get involved in addressing this potential claim, hopefully limiting damages and getting the insured back to normal as soon as possible. Another use of this application of course is fraud detection.
Smart city projects use technology to make daily life better for citizens, business and government. The (big) data these projects generate however can also be very helpful in dealing with a catastrophe and its aftermath. We don’t always think creatively about re-using our data for new purposes. Between carriers, governments and technology providers we should explore this more. To make our cities even smarter, also in bad times.
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