Tag Archives: hurricane rita

A Lesson From Hurricane Laura?

Although 2020 kept dishing out pain last week — the pandemic, the economic crisis, the protests and counter-protests on racism, our crazy politics and even wildfires and hurricanes — one event wasn’t as absolutely awful as it could have been.

It was still awful: Hurricane Laura caused billions of dollars of damage and killed 14 people in Louisiana and Texas. But the hurricane didn’t cause nearly as much damage as initially feared.

That suggests that people are starting to take the sorts of precautions that will be increasingly important as we have to adapt to the changing climate. Those precautionary principles also represent a key opportunity in front of the insurance industry: to go from indemnifying customers after a loss to helping them avoid those losses in the first place.

Now, some of what happened with Hurricane Laura was just good fortune. The hurricane pretty much threaded the needle between New Orleans and Houston, so it hit mostly rural areas, not the dense populations and expensive properties in those metropolises. The hurricane moved inland quickly, rather than sitting over an area and dumping tens of inches of rain, as Hurricane Harvey did to Houston in 2017. The storm surge, predicted to be as high as 20 feet, peaked at about 11 feet — still an almost inconceivable wall of water washing inland, of course.

But, as this New York Times article details, people mitigated the damage because they learned lessons from Hurricane Rita, which hit Louisiana and Texas in 2005. Rita killed 120 people and did some $25 billion in damage (measured in today’s dollars), including business interruption. Because of Rita, building codes have become much stricter, and structures more resilient. Some houses near the coast, for instance, are now on stilts 15 feet high. Partly as a result, while Laura’s winds were even stronger than Rita’s when the hurricanes made landfall (150 mph vs. 130 mph), the early estimates are that Laura did about $20 billion of damage while killing those 14 unfortunate souls.

Again, the storm was a catastrophe. I grieve for those 14 people, for their families and for all those who are now having to try to knit their lives back together after suffering $20 billion — $20 billion! — of damage. But, assuming that the difference between Rita and Laura wasn’t just 2020 finally cutting us some slack, there has been considerable improvement in the resilience of those in the hurricanes’ path, and I vote for more resilience, with the insurance industry helping as much as possible.

Technology should help. With Laura, the National Hurricane Center got the time of landfall precisely right, more than 3 1/2 days in advance, and was only a mile off in its prediction of the location of landfall. Predictions will only get better, giving people more time to evacuate or find shelter.

The industry can also mine its data for insights that will help people prepare better. For instance, of the 14 people who died in Hurricane Laura, more than half succumbed to carbon monoxide poisoning emitted by emergency generators. With that pattern identified, carbon monoxide poisoning seems like a danger that can be reduced or even eliminated through better inspection or education for those using generators.

Government will need to play a role, too, as climate change intensifies storms and raises the level of the oceans, endangering coastal communities. The Federal Emergency Management Agency (FEMA) has already funded “buyouts” of 43,000 homeowners in the U.S. who chose to relocate rather than continue to fight nature in places such as Isle de Jean Charles, in Louisiana, which has been 98% swallowed by the Gulf of Mexico.

We’re still not out of the woods even on this year’s hurricane season, let alone on everything else that 2020 is throwing at us, but maybe we can take a lesson from Rita and Laura. Maybe we can learn how to be even smarter and more resilient, and maybe the insurance industry can lead the way.

Stay safe.

Paul

P.S. Here are the six articles I’d like to highlight from the past week:

3 Big Opportunities From AI and ML

Machine learning can speed underwriting while reducing costs and providing valuable information on why certain proposals fail.

How CISOs Are Responding to COVID

77% of chief information security officers identified incidents that they feel they need cyber coverage for and report being unable to get it.

COVID-19: What Buyers Want Now

Insurers must examine customer pain points and life changes and accelerate digital adoption.

New Sense of Urgency on Going Digital

Events have forced C-suite leaders to realize that their digital transformation efforts need to be expanded and accelerated to light speed.

The Missing Tool for Cyber Resilience

With AI able to assess cyber risk, cyber insurance no longer has to be a long, drawn-out and complicated process.

Payments at the Speed of Light

Insurers and solution providers are making significant advancements to speed delivery of payments and expand digital payment options.

Hurricane Harvey: A Moment of Truth

The first major hurricane to make landfall in the U.S. since hurricanes Dennis, Katrina, Rita and Wilma in 2005, Hurricane Harvey will cause billions of dollars in economic damage and disrupt countless lives. In the wake of massive economic losses and untold human suffering, including loss of life, millions of individuals and businesses will turn to their insurers for help. This will be a make-or-break experience, a real moment of truth.

Insurers will be presented with a golden opportunity to justify the public’s trust and earn the respect of policyholders, regulators, legislators and others in government. But insurers also run the risk of failing to live up to expectations and incurring the wrath of voters and their elected representatives.

See also: Flood Risk: Question Is Where, Not When  

The first test may well be distinguishing damage caused by wind from damage caused by flooding, as virtually all insurance policies exclude losses due to flooding (the exception being those policies issued by the National Flood Insurance Program). Insurers will need to be careful, thorough and fair when settling claims.

Equally important, insurers will need to be perceived as having been so, and communication will be key. Insurers would be well advised to do what they can to make policyholders feel they have been treated with respect, dignity and compassion even when their claims must be denied or settled for some amount less than the claimant sought.

Moreover, insurers would be well advised to settle claims as quickly as possible without unduly sacrificing sound loss adjustment and efforts to weed out fraud and abuse.

Finally, with the media sure to draw attention to heartbreaking stories about human tragedy in Harvey’s aftermath, insurers might benefit from doing what they can to shine a light on their efforts to help individuals and businesses recover. Surely it is worth noting that, as others evacuate, insurers gear up to send large numbers of claim adjusters to work in extremely difficult conditions in hard-hit areas.

Hurricane Harvey will also lead to many other moments of truth. For example, the devastation caused by Harvey may well prove to be the first real test at extreme scale of new insurtech created to improve loss adjustment. Will use of drones, aerial imagery, artificial intelligence, digitalization, big data, predictive analytics and the like prove as beneficial as hoped? Will insurtech entrepreneurs and insurers who have invested in these technologies be vindicated? And, on a more positive note, will experience coping with Harvey reveal new opportunities to use emerging technologies to increase speed, efficiency and fairness?

Insured losses from Hurricane Harvey may also test reinsurance mechanisms, including catastrophe bonds, other insurance-linked securities and sidecars. And what about so-called hedge fund reinsurers, which sought to profit by investing insurance float using strategies like those typically employed by hedge funds? Will they continue to participate as claims mount, or will they instead seek to exit the business? Some past catastrophes triggered significant inflows of fresh capital, as investors sensed opportunities to profit from a turn in reinsurance markets. Such was the case following Katrina, Rita and Wilma in 2005. Will the “fast money” come rushing in again, and, if it does, will it prove to also be “smart money”?

All of the above raises the question, “Will Hurricane Harvey lead to a reset of catastrophe models, pricing for hurricane risk and underwriting?” Some past storms, such as Hurricane Andrew in 1992, convinced insurers that they had previously underestimated hurricane risk and thus led to dramatic resets in coastal property insurance markets, with attendant price increases and availability problems. Whether Harvey brings about such a reset seemingly depends on whether current catastrophe models did an adequate job alerting insurers to the risk of an event like Hurricane Harvey. If so, changes in coastal property insurance markets may be muted. If not, expect price increases and availability problems.

See also: Is Flood Map Due for a Big Data Make-Over?  

Last, and let’s hope least, Hurricane Harvey may test insurers’ enterprise risk management. Prior to Harvey, the property/casualty industry had ample surplus, and most insurers were well capitalized. But surplus was not evenly distributed across insurers, and only the surplus of those insurers that wrote policies covering properties struck by Harvey is available to cover claims from Harvey.

If an insurer only wrote risks in Oregon, its surplus won’t be called upon to cover claims from Harvey. Bottom line, insurers that covered properties affected by Harvey, that were aware of potential losses and that have ample financial resources to cover claims and continue operations can give themselves good grades for enterprise risk management.

On the other hand, Insurers that covered properties affected by Harvey, that were surprised by their losses and that lack the resources to cover claims must give themselves failing grades for enterprise risk management.

And then there is a gray area: insurers that intelligently judged the risk of insolvency to be acceptably small, took a calculated risk and then lost that bet. Though such insurers will fail, it cannot be said that their enterprise risk management failed. Eliminating even the most remote chance of insolvency is not practical. Neither is it economically viable. Sound enterprise risk management consists of: 1) understanding risks; 2) making conscious, intelligent decisions about which risks to take, which risks to avoid, which risks to mitigate and which risks to transfer; and, 3) enforcing controls that keep operations within the bounds established by an enterprise’s appetite for risk.