Swiss Re streamlines insurers’ natural disaster response with AI

Natural disasters have been increasing in frequency, severity, and diversity in recent years, pressuring insurers to be more efficient and to anticipate event and claim fallout. The same goes for reinsurance firms, which provide insurance for insurers, reducing their likelihood of large payouts—a significant factor in the insurance industry’s response to natural disasters.  

According to the US National Oceanic and Atmospheric Administration (NOAA), the US has experienced 360 weather and climate disasters since 1980 in which overall costs reached or exceeded $1 billion for each one, totaling more than $2.57 trillion. In 2023, through July 11, NOAA confirmed 12 such events, including floods and severe storms. To keep up with the unsettling pace, Swiss Re, one of the world’s largest reinsurers, now leverages predictive analytics, machine learning (ML), and artificial intelligence (AI) to help its clients anticipate disasters and mitigate costs.

“If you look at the severity of losses over the past 10 years, one of the trends is that losses in the last five years are almost twice as much as those in the first five,” says Anil Vasagiri, SVP and head of property solutions at Swiss Re. “That’s an unmistakable trend and one which insurers, and reinsurers like Swiss Re, are having to understand and prepare for in order to operate in this sort of environment.”

Along with the overall cost of claims stemming from natural catastrophes (NatCats), insurers face operational challenges from the sudden and voluminous influx of claims that result. Immediately after such disasters, affected areas are frequently difficult or impossible to access, delaying response time to claims.

In his role, Vasagiri is responsible for the data and software assets deployed to Swiss Re’s clients, as well as the company’s overall data strategy. Late last year, Vasagiri’s property solutions division released a significant new tool to help its clients. Dubbed Rapid Damage Assessment (RDA), the platform blends advances in computer vision with other modeling techniques to help insurance clients better understand, plan, and analyze their portfolios before disasters strike, monitor their portfolios as events unfold, and then leverage technology to find and mitigate claims in the wake of an event. This can help identify claims of which policyholders are unaware, says Vasagiri, perhaps because they have holiday homes that have been affected and they live elsewhere, or they were forced to evacuate and have been unable to return. So RDA helps its clients inform those policyholders about how they could file claims.

“If you identify certain claims sooner and put them in remediation, it reduces the severity of losses,” Vasagiri explains. “For instance, putting up a temporary tarp covering a roof that had been blown off minimizes your loss,” he adds as a metaphor for how RDA can help mitigate insurers’ losses as a result of a NatCat.