In the Aftermath of the September 11, 2001, attacks, Congress passed a law requiring commercial and casualty insurance companies to offer terrorism coverage. That was reassuring to jittery business owners but a major hassle for insurers, who, after all, are in the business of predicting risk. They might not know when something like a hurricane or earthquake will hit, but decades of data tell them where and how hard such an event is likely to be. But terrorists try to do the unexpected, and the range of what they might attempt is vast. A recent study published by the American Academy of Actuaries estimated that a truck bomb going off in Des Moines, Iowa, could cost insurers $3 billion; a major anthrax attack on New York City could cost $778 billion.
How do you predict a threat that's unpredictable by design? By marshaling trainloads of data on every part of the equation that is knowable. Then you make highly educated guesses about the rest.
But Dr. Woo doesn't work at the Defense Department. He consults for insurance companies, and is currently putting his mind to work on the problem of how to price insurance policies covering terrorist acts. Among his tools: game theory, the statistical approach made famous in the recent movie "A Beautiful Mind" about the life of mathematician John Forbes Nash Jr.
In a paper on the subject, Dr. Woo predicted that the frequency and severity of future attacks would be influenced by the structure of terrorist networks, which he compares to insect swarms and German U-boat fleets. This perspective helps "get under the skin of these groups and figure out what their strategies will be," he explains. Gathering enough information on terrorists' swarmlike behavior, the nature of past attacks and the goals of al Qaeda will provide parameters for models to price insurance, he adds, though such modeling is in its early stages and remains a formidable task.
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