Catastrophe modeling remains work in progress. With each upgrade we aim to build a better model, employing expanded data sets for hazard calibration, longer simulation runs, more detailed exposure data, and higher resolution digital terrain models (DTMs).
Yet the principal way that the catastrophe model “learns” still comes from the experience of actual disasters. What elements, or impacts, were previously not fully appreciated? What loss pattern is new? How do actual claims relate to the severity of the hazard, or change with time through shifts in the claiming process?
After a particularly catastrophic season we give presentations around ”the lessons from last year’s catastrophes.” We should make it a practice, a few years later, to recount how those lessons became implemented in the models.
Today is World Tsunami Awareness Day — designated by the United Nations General Assembly, and according to the United Nations Office for Disaster Risk Reduction (UNISDR), on average, tsunami events have a higher mortality rate than any other hazard. Over the past 20 years (1998-2017) tsunamis have claimed more than 250,000 lives and are also attributable for US$280 billion of the US$661 billion of total recorded economic losses for earthquakes and tsunamis. Between 1978-1997, tsunamis claimed 998 lives, and US$2.7 billion in losses. Overall, tsunamis are rare, but as the UN points out, when they occur they are deadly and hugely damaging. This infrequency makes building awareness and preparedness more of a challenge.
The UN has promoted World Tsunami Awareness Day since 2015, and the UN Secretary-General’s Special Representative for Disaster Risk Reduction, Mami Mizutori, stated that “…it is an occasion to promote greater understanding of tsunami risk to avoid future loss of life. This year we also want to bring attention to the economic losses tsunamis can inflict as a result of damage to critical infrastructure located along vulnerable, densely populated coastlines.”
On October 18, 2018, Geoscience Australia (GA) released its latest view of earthquake hazard for Australia. A headline finding from the 2018 National Seismic Hazard Assessment (NSHA2018) is the reduction of the 475-year peak ground acceleration hazard estimates on rock conditions by up to 70 percent. While GA had updated the Australian seismic hazard model in 2012 (Burbidge et al., 2012), the basis of the Australia building code is a 1991 map described by McCue (1993) which is included in the Global Seismic Hazard Map (figure 1 below) published nearly twenty years ago (Global Seismic Hazard Assessment Program (GSHAP); Giardini, 1999). This 2018 update is pivotal in addressing the long running scientific debate started since.
As an organization, it is always great to get recognition from the industry for the work that you are doing; and industry recognition does make a real difference to the teams that work so hard to produce robust, quality solutions that are solving the problems that the market faces. And so, on September 27, off we went to Cipriani 25 on Broadway in New York, for the Eleventh Reactions Annual North America Awards, with RMS receiving the “2018 North America Risk Modeler of the Year” award.
This award is decided by votes from the industry and it recognizes our reputation for providing best-in-class support and leadership to our North America clients, and especially at times when insight is so critical to a business — such as during the significant cat events that ran through 2017. It also provides an endorsement for the approach that RMS is taking more generally to anticipate and deliver on the needs of the North America market, to keep pushing the boundaries and break new ground, to help a growing client base across the industry ranging from reinsurers and carriers through to capital markets.
It turns out the biggest killer in the Palu earthquake on the island of Sulawesi, Indonesia, may not have been the tsunami after all — but liquefaction. Two thousand victims of the earthquake and tsunami are confirmed but 5,000 people remain missing, many of them presumed swallowed up in extraordinary ground deformation and mudflows, which took off when the underlying solid ground liquefied. Some buildings were transported hundreds of meters, others were ripped apart, many collapsed into fragments that then became absorbed into the mud. Media reports state that in Balaroa, just a few kilometers from Palu City, many of the 1,747 houses in the village appear to have sunk into the earth. In Petobo, a village to the east of Palu, many of the village’s 744 houses have disappeared.
What we have witnessed at Palu merits the term “ultra-liquefaction”, as witnessed in the 2011 Christchurch, New Zealand earthquake when perhaps half the total insurance loss costs were a consequence of liquefaction. For Christchurch, in the eastern suburbs it was single storey houses, ripped apart by the ground movements. In the Central Business District (CBD), many mid-rise buildings had to be demolished because underlying liquefaction had led to one corner of the structure sinking by ten or twenty centimeters (four to eight inches).
A version of this article was originally published in Insurance Day
The Mw7.5 earthquake in Sulawesi, Indonesia on September 28 reminds us that fourteen years after the terrible Indian Ocean tsunami, and despite significant investment in systems intended to provide tsunami warnings, the risk to life and property is not going away. To understand why the destruction and loss of life in the city of Palu, with a population of 350,000, is so great (1,300 and rising) we need to understand why this location has proved such a nexus of vulnerabilities.
First, Palu is located less than one degree south of the equator. That means it is in the “shadow zone” for tropical cyclones. In most of the world’s oceans, no tropical cyclone can exist within ten degrees of the equator, although in the western Pacific the typhoon exclusion zone can narrow down to six to eight degrees from the equator. The lack of Coriolis force at the equator prevents a collection of thunderstorms gaining a structured rotation (and tropical cyclones spin in opposite directions in the northern and southern hemispheres).
The lack of tropical cyclones means there are no significant storm surges, or even much in the way of significant wind-driven waves, and as a result people build their houses right down to sea level. This means, in comparison even with a coastal city in Philippines or China, there were many more seafront buildings exposed to a tsunami that reached no more than three to five meters above sea level.
The earthquake and subsequent tsunami that struck the Indonesian island of Sulawesi on Friday, September 28, has already claimed the sinister accolade of being the deadliest earthquake in the world this year.
According to local authorities, there have so far been 1,374 reported fatalities, but this figure is set to rise as rescue efforts spread out from the main cities. At this stage, thousands of people are believed to still be trapped under the rubble of collapsed buildings, and at least 60,000 people are displaced with limited food and water supplies.
The 7.5 magnitude earthquake struck the island of Sulawesi on Friday, September 28, approximately 48 miles (78 kilometers) north of Palu, a coastal city with around 330,000 residents. The earthquake triggered a ten foot (three meter) high tsunami, that impacted the coastal areas of western Central Sulawesi, including Palu City and Donggala, a regency with a population of around 275,000.
There used to be several ways to ensure risk diversification in a California earthquake insurance portfolio. You could select risks on the Peninsula and risks in the East Bay; or select risks in Ventura and Orange counties; or risks in Santa Barbara and Los Angeles counties. Better yet, it was considered that selecting risks in the San Francisco Bay Area and in the Los Angeles region was a perfectly good way of achieving risk diversification. This practice was largely based on an understanding of the spatial correlation of expected loss between counties in California and selecting risks for counties which decreased loss correlations in the insured portfolio.
While California and the large-scale plate motions that it is subjected to have not changed in recent years, the way earthquake sources are modeled has. The two main areas scientists are trying to explore are: first, whether there are preferential locations in a fault network where ruptures are likely to start or stop. The second area examines what the relationship is, if any, between the timing of the latest events on a fault network and the timing of the next event that will overlap with those events. A third avenue of research that is relevant for California is the behavior of aseismic faults — faults that deform without making felt earthquakes, and what happens to them when large ruptures propagate in their direction.
RMS led a study to quantify the impact of these three major modeling assumptions on spatial loss correlations. The study used sixteen county portfolios made using the RMS Industry Exposure Database (2017), and two vintages of source model: the Uniform California Earthquake Rupture Forecast 2 and 3 (UCERF2 and UCERF3). One major conclusion was that new and different risk selection strategies would be required by the spatial loss correlation study to ensure portfolio diversification with the most recent United States Geological Survey (USGS) model (UCERF3) as compared to the previous versions of the model (i.e. UCERF1 or 2).
The pace of change continues to accelerate across the insurance industry, whether it is from technology, regulation or market developments, and EXPOSURE magazine helps risk professionals to explore some of the key drivers of these changes.
In this latest edition available for distribution at the Monte Carlo Rendezvous and online, the lead story looks at the recent market activity from Tower Insurance in New Zealand. By adopting high-definition earthquake modeling, Tower gained the confidence to launch risk-based pricing for its customers, providing savings for the majority of policyholders, but increases for others. EXPOSURE looks at the implications of Tower’s actions and how this could affect the New Zealand insurance market.
High resolution modeling has also helped Flood Re in the U.K. to better understand how it can work towards its remit of delivering a flood insurance market based on risk-reflective pricing that is affordable to policyholders. EXPOSURE shows how innovative use of modeling could guide Flood Re when recommending investment measures to protect properties at risk of flooding.
The rallying cry has sounded — to “close the protection gap”, the difference between what is paid out by insurance and the total cost of some incident or disaster. Here is an issue that can unite and promote the insurance industry, extending benefits to those in peril by expanding the insurance sector. Having ex-post access to funding after a loss, we know, can bring important benefits.
Yet in reality, there is not just one, but three distinct insurance “protection gaps”, each with separate causes and each requiring different remedies. These protection gaps are so different to one another that we should stop treating them as a single category. Lumping them together can cause confusion.
In this series of four blogs, I will explore each of these three distinct gaps, together with the role of protection gap analytics, and the actions we can plan to address these protection gaps.