Author Archives: Robert Muir-Wood

About Robert Muir-Wood

Chief Research Officer, RMS

Robert Muir-Wood works to enhance approaches to natural catastrophe modeling, identify models for new areas of risk, and explore expanded applications for catastrophe modeling. Robert has more than 25 years of experience developing probabilistic catastrophe models. He was lead author for the 2007 IPCC Fourth Assessment Report and 2011 IPCC Special Report on Extremes, and is Chair of the OECD panel on the Financial Consequences of Large Scale Catastrophes.

He is the author of seven books, most recently: ‘The Cure for Catastrophe: How we can Stop Manufacturing Natural Disasters’. He has also written numerous research papers and articles in scientific and industry publications as well as frequent blogs. He holds a degree in natural sciences and a PhD both from Cambridge University and is a Visiting Professor at the Institute for Risk and Disaster Reduction at University College London.

Crossing the Terrorism Casualty Protection Gap

This blog was first published as an article in Insurance Day

The victims of the Las Vegas shooter Stephen Paddock, the injured and the dependents of the 57 who died have one comfort following their tragic predicament. Their vicious and indiscriminate attacker (whose reported comments get the attack classified as “domestic terrorism”) chose to fire at the 20,000-plus crowd attending the Route 91 Harvest music festival from the 32nd floor of the Mandalay Hotel, part of the MGM chain with a US$735 million liability insurance coverage. As a result (reflecting in part the “moral hazard” of insurance limits), the victims will receive the distribution (after substantial lawyers’ fees) of a near-US$800 million settlement.

In the lead-up to the attack on October 1, 2017, Paddock had researched renting a high-rise condo in Las Vegas and also explored the crowd numbers on the beach at Santa Monica and considered other festivals to target in Boston and Chicago. If he had chosen to shoot from a residential building or clifftop, to the same effect, the only compensation the victims could have expected would have been the US$11 million raised in a public appeal after the shooting: equal to around US$200,000 for each of those who died. As it is, their compensation should work out 30 times more generous.

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The Year of the Kitten

Almost three months ago we passed a remarkable record in catastrophe loss.

And yet no one seems to want to celebrate it.

No banner headlines in the newspapers. No speeches at the Monte Carlo Reinsurance Rendezvous.

The first half of 2019 generated the lowest catastrophe insurance loss for more than a decade. The estimates come in at: US$15 billion (Munich Re), US$19 billion (Sigma), or US$20 billion (Aon). In straight dollar terms, independent of any adjustment for inflation or exposure, this is lower than any year since 2006.

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Hurricane Dorian: Who Takes Responsibility for the Loss of Life?

In late 2005 I was on New Providence Island, Bahamas, producing a map to show which properties around the island were within the storm surge flood zone. The northern islands of the Bahamas had been battered by 19 feet (six meters) of storm surge in 1999 during Hurricane Floyd and flooded again in 2004 Hurricanes’ Frances and Jeanne.  

While wandering around the poorer, south side of Nassau, I came across a single-story building, probably a community center or clinic, with barred windows, on which was written “Hurricane Shelter”. It was sufficiently surprising that I even took (and kept) a photo – see below, for the “Hurricane Shelter” was only two to three feet above sea level. If people gathered at this shelter as a strong hurricane approached, they would be placing themselves in mortal danger from an accompanying storm surge.  

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Finding the City That Holds Your Climate Future

Imagine, instead of trying to communicate the prospective climate change future, you could just time travel to experience the weather of 2050.

In place of having to convince the city engineers of Paris or Chicago to invest in better street drainage and passive-cooling architecture, you could take them to experience their city in thirty years, well within the lifetime of the facilities and infrastructure they are constructing today. Rather than having to factor in seemingly arbitrary modifiers to flood or heatwave risks, to stress test your future insurance losses, you could visit an insurer already experiencing and pricing those future climate extremes.

In evaluating climate, we already have an alternative to time travel – we can travel in latitude. You could accomplish all these tangible goals, if you could identify the place which today already experiences your future climate.    

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The Disappearing Tokyo Risk Audit

Without the ability to measure, how do we know if we are making progress?

In December 2012, in preparation for the renewal of the UN Millennium Development Goals, I wrote a report for the U.K. Government Department for International Development (DFID) advocating that catastrophe models should be used to measure progress in disaster risk reduction. I suggested goals could be set to target a 50 percent reduction in expected casualties and a 20 percent reduction in normalized economic losses, over the period of a decade, based on the output of a catastrophe model.

Two years later, the seven targets agreed at the UN meeting on Disaster Risk Reduction, held on March 14–18, 2015, in Sendai, Japan – were a disappointment. The first two targets for “Disaster Mortality” and “Affected People” would simply compare data from 2020-2030 with 2005-2015. The third target was to “reduce direct disaster economic loss in relation to global GDP by 2030”. Yet we know, especially for casualties – even at a global level, a decade is not enough to define a stable mean. For cities and countries, comparing two decades of data will generate spurious conclusions.

And so, it was a relief to see that only two weeks later, the Japanese and Tokyo city governments announced they had set themselves the challenge of halving earthquake casualties over a decade, measured by modeling a hypothetical event based on the M7 1855 Edo earthquake under Tokyo. I referenced this announcement and quoted it widely in presentations, to highlight that risk modeling had been embraced by the country with the most advanced policies for disaster risk reduction.

Over the last two years, I started searching for some update on this initiative. What kind of progress in risk reduction was being achieved, whether the targets for Tokyo would be met? And I found my original links had all stopped connecting. Perhaps in my enthusiasm I had dreamt it?

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Blue Chip Catastrophes

What do the 393 grounded Boeing 737 MAX aircraft have in common with BP’s “Deepwater Horizon” fire and uncontrolled oil release, or with Volkswagen’s (VW) “cheat technology” that ensured its diesel engine cars could pass stringent U.S. and European emissions test standards?

All three situations cost their respective companies tens of billions of dollars. Two of them concerned the development of in-house software that caused more self-inflicted damage to the company’s balance sheet than any corporate hit from an external cyberattack. And all three highlight defective risk management and regulation.

Volkswagen Group, BP and Boeing are all world class companies: ranked #18, #24 and #49 globally in the recently published Forbes Global 2000. For investors these are “blue chip” stocks: “… the stalwarts of industry – safe, stable, profitable and long-lasting companies, they represent safe, low volatility investments.” Investors might prefer to return to the original definition of “blue chip” in poker-playing, where it designates the highest value token but says nothing about the risk.

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Cyber and the War Exclusion

In 1915, Cuthbert Heath – pioneer of catastrophe insurance at Lloyds of London, decided to offer insurance policies to cover the impacts of war, far from the front line. Zeppelin airships were arriving over London during World War One, dropping bombs and incendiary devices. Later in the War, the bombs were being thrown out of Gotha biplanes.

Heath did some simple calculations: the number of Zeppelins, the frequency of attacks, the number of bombs each airship could carry, the damage area of an explosion, and how much of London was built up compared to open spaces. Having generated a risk cost estimate, he then multiplied it by six to arrive at his proposed rate for the insurance coverage. As the intensity of air attacks went up and down so his insurance prices followed.

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The All-Peril Cat Five

Why the Saffir-Simpson Hurricane Intensity Scale had five levels we don’t know. The digits on a hand? Better than three, but lower resolution than the dozen rungs for wind speeds or earthquake intensity? Whatever the reason it seems to work.

In the late 1960s, Herbert Saffir, a Florida building engineer, was sent by the United Nations to study the hurricane vulnerability of low-cost housing in the Caribbean. He realized something was needed to rank hurricane destructiveness. Saffir had some “Richter envy” from observing the ease with which seismologists now communicated with the public. In 1971, he contacted Robert Simpson, head of the National Hurricane Center to help link damage levels with wind speeds.

Seeing the opportunity to communicate evacuation warnings, Simpson also added details around the height of advancing storm surges. Better information was clearly needed, after the loss of life in Hurricane Camille on the Mississippi coast in 1969.

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The Age of Innocence

Professor Ilan Noy holds a unique ”Chair in the Economics of Disasters” at the Victoria University of Wellington, New Zealand. He has proposed in a couple of research papers that instead of counting disaster deaths and economic costs, we should report the “expected life-years” lost, not only for human casualties but also for the life-years of work that will be required to repair all the damage to buildings and infrastructure.

The idea is based on the World Health Organization’s Disability Adjusted Life Years (DALYs) lost through disease and injury (WHO 2013). The motivation is to escape from the distortion introduced by measuring the impact of global disasters in dollars, as loss from the richest countries will always dominate this metric. Noy’s proposal converts injuries into life-years lost, based on how long it takes for the injured to return to complete health, while also factoring the degree of permanent disability multiplied by its duration. This is topped up by a “welfare reduction weight” for all those exposed to a disaster. The final component of the index attempts to capture how many years of human endeavor is lost to recovering the buildings and assets destroyed in the disaster.

There is plenty to argue over in terms of how deaths, injury and damage should be combined. In particular, the assumption that additional work to rebuild a city, is the same as a shortened life, seems somewhat reductive.

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Global Risks for 2019? Or a Retrospective of the Risks of 2018?

The World Economic Forum (WEF) Global Risk Report was released a week ago, in time to generate discussion and provoke debate at the WEF Annual Meeting in Davos.

Among the headlines of the Global Risk Report, as in every annual update, there are two lists of the top five risks for 2019, according to their expected Likelihood and Impact. These lists are based on the WEF Global Risks Perception Survey conducted four months ago, with around a thousand responses from the WEF’s multi-stakeholder communities, professional networks of its Advisory Board, and members of the Institute of Risk Management.

There is a sense about these top five lists, that they are reactive – reflecting what has recently happened, more than being an effective and objective analysis of risk. We know that the most dangerous events are precisely those which one has not recently witnessed and that arrive as something of a surprise.

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