The Analytics Behind the Aid

The World Food Programme's recent deal with Axa Re was a derivative, or a financial transaction that transferred the risk from one entity to another, based on an index. In this case, the index was rainfall in Ethiopia. But the terms of payment involved complex equations that used modeling techniques to incorporate variables such as rainfall levels, different types of crops and more than two dozen recording sites around the northeast African nation.

Unlike the traditional insurance policy that indemnifies an insured for a measurable loss, an index-based product uses an index, such as rainfall or temperature, as a proxy for determining loss.

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A combination of evolving computer software programs, mathematical wizardry and brainy engineers have helped spur the development of such tools and catastrophic risk modeling in general over the past decade. Also referred to as extreme risk or parametric risk modeling, this technology is helping the insurance industry and large companies quantify and manage the risks emanating from natural hazards such as hurricanes, earthquakes, windstorms and floods.

Analysts say the billions of dollars lost during Hurricane Andrew in the summer of 1992 helped spur its development.

"Up to then, it (catastrophic risk modeling) had been a curiosity," says Warren Isom, a senior vice president at the Philadelphia office of Willis Re. "But a lot of people lost a lot of money in Hurricane Andrew. And for some small firms, it was a real embarrassment."

The Northridge Earthquake that hit 20 miles northwest of Los Angeles in 1994 and the Kobe Earthquake in Japan a year later just accelerated the process.

Today, three firms--AIR Worldwide Corp., headquartered in Boston; Risk Management Solutions Inc. in Newark, Calif.; and Eqecat Inc. in Oakland, Calif.--have taken the lead in helping companies make crucial decisions about managing their catastrophic risks. Experts weave sophisticated computer technologies and mathematical formulas with the latest data and research findings in meteorology, seismology, hydrodynamics and structural engineering to create models that help quantify the losses from natural disasters.

Insurers and reinsurers can then better underwrite hazards, price their products and make decisions about transferring their risks. Corporations with large real-estate holdings, such as big-box retailers, factories or power plants, also use the information.

September 1, 2006

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