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Insurance Solutions

Formerly Moody’s RMS

In my invited presentation on October 22, 2015 at the UK Institute and Faculty of Actuaries GIRO conference in Liverpool, I discussed how modeling of extreme events can be smarter, from a counterfactual perspective.

A counterfactual perspective enables you to consider what has not yet happened, but could, would, or might have under differing circumstances. By adopting this approach, the risk community can reassess historical catastrophe events to glean insights into previously unanticipated future catastrophes, and so reduce catastrophe “surprises.”

The statistical foundation of typical disaster risk analysis is actual loss experience. The past cannot be changed and is therefore traditionally treated by insurers as fixed. The general consensus is why consider varying what happened in the past? From a scientific perspective, however, actual history is just one realization of what might have happened, given the randomness and chaotic dynamics of nature. The stochastic analysis of the past, used by catastrophe models, is an exploratory exercise in counterfactual history, considering alternative possible scenarios.

Using a stochastic approach to modeling can reveal major surprises that may be lurking in alternative realizations of historical experience. To quote Philip Roth, the eminent American writer: “History, harmless history, where everything unexpected in its own time is chronicled on the page as inevitable. The terror of the unforeseen is what the science of history hides.”  All manner of unforeseen surprising catastrophes have been close to occurring, but ultimately did not materialize, and hence are completely absent from the historical record.

Examples can be drawn from all natural and man-made hazards, covering insurance risks on land, sea, and air. A new domain of application is cyber risk: new surprise cyber attack scenarios can be envisaged with previous accidental causes of instrumentation failure being substituted by control system hacking.

The past cannot be changed—but I firmly believe that counterfactual disaster analysis can change the future and be a very useful analytical tool for underwriting management. I’d be interested to hear your thoughts on the subject.

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Gordon Woo
Catastrophist, Moody's RMS

Gordon is a catastrophe-risk expert, with 30 years’ experience in catastrophe science, covering both natural and man-made hazards. Gordon is the chief architect of Moody's RMS terrorism risk model, which he started work on a year after joining RMS in December 2000. For his thought leadership in terrorism risk modeling, he was named by Treasury & Risk magazine as one of the 100 most influential people in finance in 2004. He has since lectured on terrorism at the NATO Center of Excellence for the Defense against Terrorism and testified before the U.S. Congress on terrorism-risk modeling.

As an acknowledged, international expert on catastrophes, Gordon is the author of two acclaimed books: “The Mathematics of Natural Catastrophes” (1999) and “Calculating Catastrophe” (2011). Dr. Woo graduated as the best mathematician of his year at Cambridge University and he completed his doctorate at MIT as a Kennedy Scholar and was a member of the Harvard Society of Fellows. He also has a Master of Science in computer science from Cambridge University.

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