It seems that not a day goes by where we don’t read about some catastrophic natural disaster, somewhere: hurricanes in the Caribbean, earthquakes in Mexico or Taiwan, wildfires in California, and now volcano eruptions in Hawaii and Guatemala. The losses are devastating – in economic terms, for example, losses are in the tens of billions of dollars or more for the last spate of California wildfires; in human terms the losses are incalculable. How can the challenges of catastrophic loss be planned for, and when they occur, managed so that individuals and businesses can begin to rebuild?
Insurtechs are now offering many of the tools and solutions to help plan for and meet these extraordinary challenges, and innovators in the space are trying to apply them to an increasing number of real world occurrences.
Take drones. Drones are not just providing “eye in the sky” coverage for news channels. They are also becoming an increasingly important tool in managing risk and assessing damage. One good example would be the services provided by Betterview (see our Oliver Wyman InsurTech interview with David Tobias, Betterview Founder and Co-CEO).
Big data, another key insurtech tool, provides additional support for catastrophic natural disasters, like earthquakes. A tool like parametric insurance, which pays on the occurrence of a triggering event, relies on data to register the event’s occurrence and assess its magnitude. Kate Stillwell, CEO and founder of Jumpstart Recovery developed such a tool for building resilience around earthquake damage and spoke with us about it at InsureTech Connect 2017 (even better, Jumpstart brought along a van to InsureTech Connect that simulated an earthquake for willing volunteers).
A former president of the Structural Engineers Association of Northern California and longtime fellow at the Earthquake Engineering Research Institute, Stillwell notes that “Safe buildings are necessary but it is not enough unless we have these other puzzle pieces of resilience.”
Another example would be Jupiter Intelligence, which which provides data and analytics services to better predict and manage risks from weather and sea level rise, storm intensification and changing temperatures caused by climate change. A recent piece by Jupiter’s CEO Rich Sorkin, “A New Era in Modeling Catastrophic Risk” in BRINK outlined the ways that previous efforts to model catastrophic environmental risks have rested upon what many believe are faulty “stationary” models (based on past weather data and resting on the assumption that weather conditions will follow similar patterns). Jupiter has employed machine learning and artificial intelligence to large data sets in order to provide more dynamic models that can produce “asset-level predictions that are accurate from two hours to 50 years in the future,” according to Sorkin.
Awareness, preparation, assessment, and resiliency: these are key dimensions of meeting any risk, not just catastrophic environmental risks like those receiving headline attention in the news. But these larger risks, seemingly unpredictable in the past, present a challenge that insurtech innovators are trying to meet, armed with the ability to harness massive data sets to transform signal into noise, to prepare carefully and appropriately to meet risks better understood, to literally rise above the chaos of disasters to asses damages, and then to mobilize processes in order to deliver relief and remediation.