This water tower, shown Aug. 25, 1992, a landmark at Florida City, Fla., still stands over the ruins of the Florida coastal community that was hit by the force of Hurricane Andrew. The storm damage to the South Florida area was estimated at $15 billion, leaving about 50,000 homeless. (Photo: Ray Fairall/AP Photo)

Enter Hurricane Andrew

As Hurricane Andrew was making landfall on Aug. 24, 1992, there was again disbelief when the first hurricane model projected that the loss could exceed $13 billion.

In fact, it would take more than six months for the industry to fully realize it was going to pay out $15 billion in losses. And it didn't take much math to calculate that had Andrew hit farther north, closer to downtown Miami, the loss could have been $60 billion.

Fast forward to 2016 and complacency has once again set in.

It's been 10 years since a hurricane has made landfall in Florida — unprecedented in the historical record — and no major hurricane has made landfall near a populated area in the United States since 2005's Katrina. Coastal property values in Florida and elsewhere have continued to swell. The catastrophe models have now become the traditional tools, and the industry has become far too comfortable relying on the model-generated probable maximum losses. 

Over the past few years, new tools have come into the market, and these innovative scientific techniques clearly show that the traditional catastrophe models don't provide a full picture of an insurer's loss potential. In many cases, the traditional model-generated probable maximum losses give a false sense of security — just like the traditional approaches used in 1992. 

And as in the pre-Andrew days, there's inertia, and even some resistance, to new scientific methodologies and insights into catastrophe loss potential. 

Figure 1. Source: Karen Clark & Co.

Using the characteristic event methodology

Among the new tools is the characteristic event methodology that provides insurers with information on what size losses different return period events will cause.

CEOs, boards and other senior decision makers in the insurance industry often mistakenly refer to their 1-in-100-year probable maximum lossess as the 100-year events. But the model-generated probable maximum losses don't refer to any specific events — they're simply points on the estimated loss distributions. And what is also often forgotten is the 100-year probable maxim loss shows the loss amount for which there's a 1% chance of exceedance. 

Related: Here's what 100 years' worth of hurricane data says about losses and catastrophe reinsurance

The characteristic events clearly illustrate where insurers can have losses from the 100-year events that exceed their 100-year probable maximum losses. This is important underwriting information the traditional models don't provide, and while the probable maximum losses may be similar, the characteristic event profiles can be very different between insurers. For some companies, the gap between the 1-in-100-year probable maximum loss and the loss from the 1-in-100-year event is significant as shown in the two contrasting CE profiles for Company A (Figure 1, above) and Company B (Figure 2, below).

Figure 2. Source: Karen Clark & Co.

Obviously, an insurer will be better informed with both perspectives on its large loss potential — the 100-year loss and the loss from the 100-year event. The characteristic events help insurers take underwriting actions in order to avoid unpleasant surprises along with highlighting clearly where companies can grow profitably without adding to peak exposures.

Figure 3. Source: Karen Clark & Co.

Multiple approaches provide better information

Multiple approaches and perspectives on risk lead to better pricing, underwriting and risk management decisions. Using multiple models is not the same as using multiple approaches because all the traditional catastrophe models use essentially the same fundamental approach. Savvy underwriters, CEOs and other insurance company executives instinctively understand the value of the newer characteristic event method. 

It's the catastrophe modelers who need the most convincing this time around because many don't see the need for anything other than the traditional modeling perspective. There's been too much reliance on (and resource spent on) this one approach. Ironically, some of the 1992-era skepticism of the models would serve the industry well today. Will it take Andrew II to awaken the catastrophe-modeling community from its current complacency? 

A storm like Andrew — the one-in-100-year characteristic event in South Florida — will make a direct hit on Miami this year or in a future year. When it does, the resulting loss will be greater than many companies' probable maximum losses, the industry loss will likely exceed $200 billion and certain insurers will be financially impaired. Although many insurer CEOs will be surprised if they aren't given the vital characteristic event information, no meteorologist will be surprised because a Category 5 hurricane is just as likely to strike Miami as Homestead, Fla.  

Credible scientific approaches

In a state such as Texas, the traditional model-generated probable maximum loss is almost meaningless. The Texas coastline is relatively sparsely populated except around Galveston and Houston. The characteristic events profile in Figure 3 (above) illustrates that if the 100-year Texas hurricane hits most areas along the coast, the losses will not be too significant. However, a landfall anywhere around Galveston or Houston will produce an insured industry loss exceeding $50 billion, and just the right landfall points could produce losses in excess of $150 billion. 

The traditional catastrophe models generally agree that the 100-year probable maximum loss for Texas is around $40 billion. So the largest loss from the 100-year event is four times the 100 year probable maximum loss. Clearly, Texas companies managing to their 100-year probable maximum loss could easily be overly exposed to the 100-year-event. 

Given the well-known limitations of the traditional models and the uncertainty surrounding catastropohe risk, it's wise to embrace all credible scientific approaches to understanding and managing large loss potential. It does not serve the industry well to stay locked into one way of thinking about catastrophe losses. Is this déjà-vu, and could history repeat itself this hurricane season?

Karen Clark is president and chief executive officer of Boston-based catastophe risk management firm Karen Clark & Co.

Related: 4 tips to limit the risk of a big catastrophe getting bigger