When Hurricane Katrina slammed into New Orleans in August 2005, causing greater insurance losses than any other natural disaster in history, it became clear that a lot of the city’s flood protection engineering — walls, pumps, levees — had failed.
Something else failed, too: Insurers’ catastrophe models.
The models at the time overestimated the strength of the levees. They also underestimated the exposure of commercial properties. And they didn’t fully account for storm surge. It was the storm surge — amplified by huge wind-driven waves — that drowned New Orleans.
“Katrina was a very tricky storm,” said Karen Clark, co-founder and chief executive of Karen Clark & Co., a catastrophe modeling firm in Boston. “The storm surge turned out to be a lot more impactful than the models had assumed for a Category 3 hurricane.”
Related: 20 Years Later, Hurricane Katrina’s Impact Echoes in Models, Mitigation and Reforms
Today, nearly 20 years after Katrina, the financial stakes from hurricane hits have risen dramatically. Thousands of people have moved to the coast and built homes that are a lot more expensive to repair or replace, a development that’s been exacerbated by the effects of inflation.
“What we build today is not what we built 10 or 20 years ago,” said Clark, one of the pioneers of catastrophe modeling. “It’s now three-car garages and five marble bathrooms.”
The other X factor is climate change. Swiss Re Institute says that higher temperatures are expected to increase hurricane intensity, while rising sea levels could magnify storm surge in coastal areas. Both will have a “substantial impact” on future insured losses, it says.
“Hurricane Katrina does not represent a worst-case tropical cyclone loss scenario,” the institute warned in a recent report. “Some of the North Atlantic hurricanes that occurred during [the] early 20th century, if they were to strike today, would cause insured losses well above $100 billion in 2024 prices.”
Today’s catastrophe models are undeniably more powerful, thanks to the increase in computing power, the greater availability of granular asset-level data, and advances in AI. The models have also incorporated once-ignored outcomes such as storm surge.
But significant blind spots remain, especially when it comes to hazards like tornadoes, hailstorms and floods. These so-called secondary perils are causing greater losses but are also harder to model compared to “peak” perils like hurricanes or earthquakes.
Last year, Hurricane Helene tore through the US southeast, causing unprecedented inland flooding and landslides, even in elevated areas such as Asheville, North Carolina.
“The disconnect between [catastrophe] models and the reality of Helene’s destruction raises significant concerns, as many models fail when the environment shifts in ways that historical data cannot account for,” Jencap, a wholesale insurance broker, said in a report. “In the case of Helene, traditional models focused on coastal impacts, underestimating the potential for severe inland flooding.”