What Insurers Can Learn From Errant Forecasts

Most actuaries know about projections that go awry, so we have quite a bit of sympathy for the weather forecasters who missed the mark early this week, says I.I.I.’s Jim Lynch:

Weather forecasts have improved dramatically in the past generation, but this storm was odd. Usually a blizzard is huge. On a weather map, it looks like a big bear lurching toward a city.

This storm was relatively small but intense where it struck. On a map, it looked like a balloon, and the forecasters’ job was to figure out where the balloon would pop. They were 75 miles off. It turned out they over-relied on a model — the European model, which had served them well forecasting superstorm Sandy, according to this NorthJersey.com post mortem.

There are lessons for the insurance industry from the errant forecast and the (as it turns out) needless shutdown of New York City in the face of the blizzard that wasn’t:

  • – Models aren’t perfect. Actuaries, like weather forecasters, have multiple forecasting models. Like forecasters, actuaries have to know the pros and cons of each model and how much to rely on each one given the circumstances. Actuaries and forecasters both bake their own experience into their final predictions.
    Property catastrophe models are considerably cruder than the typical weather forecasting model. By crude I mean less accurate. Cat models project extreme events, where data are sparse and everything that happens has an oversize influence on everything else that is happening. Woe to the insurer that over-relies on cat models, something cat modelers themselves say regularly.
  • – It’s hard to pick up the flag once you have planted it. Forecasters suspected late Monday that New York City would be spared the brunt of the storm, but acknowledge now they were reluctant to make too big a change because it could hurt their credibility, particularly if the new forecast had proved too mild. This is a human failing both by the forecaster and its recipient, both of whom worry about crying wolf.
    The tendency also helps explain why it is hard to project market turns, whether they are from growth to recession or from rising insurance rates to falling.
  • – Policymakers have egg on their faces today, but they appear to have been following sound risk management principles. It’s not unusual to prepare for disasters that don’t happen, something to think about next time you unbuckle a seatbelt or unlock a door. The scale this week was much larger, but the principle was the same. Needlessly closing a subway is better than stranding hundreds on it, and the occasional forecaster’s error is certainly better than the crude prognostication that gave us the Galveston hurricane or the Schoolchildren’s Blizzard.

I.I.I. has Facts and Statistics about U.S. catastrophes in general and winter storms in particular.

Check out this timelapse video of the blizzard hitting Boston:

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