While Hurricane Andrew is remembered for its path of destruction across South Florida 20 years ago, the storm also started a sea change in the way the insurance industry models catastrophe risks.
Andrew Castaldi, New York-based senior vice president and head of catastrophe perils for Swiss Re Ltd., said the relatively quiet hurricane activity in the two decades preceding Andrew had caused complacency in how the industry weighed hurricane risk.
“The industry was caught napping,” Mr. Castaldi said.
Bill Churney, Boston-based senior vice president of catastrophe modeling firm AIR Worldwide Corp., said the company introduced its first hurricane model five years before Andrew, but acceptance of the model's utility or accuracy was far from universal when the storm hit in 1992. When the company faxed its estimate of $13 billion in insured losses to clients in Andrew's aftermath, reactions ranged from “skepticism to outrage,” he said.
“Losses of this magnitude were not thought possible,” Mr. Churney said. “It was only months later that the insurance industry had to face the reality of a $15.5 billion bill.”
In the wake of the storm, primary insurers, reinsurers, rating agencies and regulators all came to realize the value inherent in catastrophe models, said Peter Nakada, New York-based managing director of risk markets at Risk Management Solutions Inc.
“Andrew was an inflection point,” Mr. Nakada said. “Prior to Andrew, catastrophe models were an interesting way to look at risk, almost an academic exercise. After Andrew, they became a must-have.”
The advent of modern catastrophe models highlighted some deficiencies in traditional risk-assessment techniques that relied on historical claims data, Mr. Churney said. For example, an underwriter or actuary might calculate a probable maximum loss in a given geography by using an arbitrary percentage of total insured value in the area.
“Prior to Andrew, most companies relied on traditional actuarial techniques to estimate losses,” Mr. Churney said. “But because these approaches were divorced from the actual physics of natural catastrophes, losses could far exceed the estimates, as we saw with Andrew.”
Mr. Churney said Andrew and the advent of the catastrophe modeling industry coincided with increases in computer processing power and great leaps in the sophistication of the instrumentation used to collect data on weather variables, such as wind speed.
“Certainly, catastrophe models are more sophisticated than they were in 1992, in large part the result of the exponential increases in computing power and the availability of ever more observation data at increasingly high resolution,” he said. “This data has advanced our understanding of the physical structure of hurricanes and improved our ability to estimate local wind speeds—both on the coast and as storms move inland—with greater precision.”
Taken together, these changes enable the industry to shift from assessing risk at portfolio of market basis to a more granular level that accounted for the geographic and structural peculiarities of individual properties.
“With the new technology, we were able to create more detailed location information, site specific information,” Mr. Castaldi said. “So instead of doing aggregate analyses, we now were doing individual risk analyses and then rolling them up into a portfolio.''
Sharon Binnun, Tallahassee, Fla.-based chief financial officer of Citizens Property Insurance Corp., the state-run property insurer of last resort, said this increase in capability has enabled insurers to use more complex models that account for more varied loss scenarios. “There are fewer surprises when you have different loss scenarios,” she said.
Moreover, newer catastrophe models have more complete functionality, Ms. Binnun said, adding that models now can help insurers plan for eventualities common in the wake of storms, such as shortages of supplies and critical services.
Looking forward, Mr. Churney foresees catastrophe models continuing to improving in terms of complexity and sophistication, while expanding to include more secondary perils, such as tsunamis, river-induced floods and also addressing how natural and man-made disasters might effect global supply chains.