Intro: The past 20 years of catastrophic events have taught us how important catastrophe models are, but now we rely on them too much. Jayant Khadilkar, partner at TigerRisk, says we should reduce our reliance on the probable maximum loss and develop new, more robust risk measures.

Catastrophe models saw limited usage when they were first introduced in the late 1980s. At the time, many insurers were content to carry on with their rule-of-thumb deterministic approach for calculating potential damage. But that all changed in 1992 with Hurricane Andrew. Overnight, the value of probabilistic event-based risk evaluation became clear. Since then, the industry has uniformly embraced catastrophe models so much so that we now rely on them too much.

In recent years a spate of catastrophic events — the multiple Florida hurricanes of 2004, Hurricane Katrina in 2005, Hurricane Ike in 2008, the swarm of tornados in 2011 have all demonstrated the fallibility of cat models. In case after case, insurers have found that their models understated loss projections by wide margins. What happened?