At this moment, you might expect a blog about European windstorms to be about recent Storms Ciara-Sabine, Dennis and Jorge causing wind and flood losses of a couple of billion euros in Europe. However, the losses this winter are modest in a longer-term context. Instead, I think the recent insights into longer-term variations in wind losses could have much more impact on how we price windstorm risk.
We first noticed multidecadal variability of European windstorm activity ten years ago, with 50 percent lower frequencies of damaging storms in the new millennium than in the eighties and nineties. This variability is important: a company’s length of loss experience is unlikely to match the model calibration period, which impacts model validation. It also held the promise of improved risk management, if the storminess changes could be anticipated. We needed to know more about it.
Natural disasters and other large catastrophes can trigger huge economic losses potentially among multiple insurance lines. RMS, in collaboration with research partner Cambridge Centre for Risk Studies at University of Cambridge, have developed eight template scenarios that model liability clash triggered by natural or man-made catastrophic events.
This research was primarily focused on property–liability clash modeling and was the continuation of the two-year Global Exposure Accumulation and Clash (GEAC) project. GEAC laid the foundations for a risk data schema for the various insurance lines, as well as an approach to modeling insurance clash among life and non-life insurance. Please see here for more information.
The project resulted in liability loss assessments for various scenarios including natural catastrophes, cyber and terrorism (see Figure 1 below). Although these scenarios are extreme, they are well within the realm of possibility and are aimed at stressing the various types of liability insurance.
Data – the buzzword of the decade. The world understands its value, but the insurance industry has not only lagged behind in exploiting data, it has also created huge inefficiencies in how it is handled and exchanged. This situation needs urgent attention, but no single company is going to solve this problem – it will take collaboration.
The data that drives risk analytics has proven particularly tricky to handle and leverage. Right now, the standards the industry uses are decades-old property cat schemas – venerable workhorses that took the industry from an almost total lack of exposure data to a relatively high degree of understanding. They transformed how property cat risk is transacted, priced, and managed. But these old formats have run their course and if we want to gain meaningful efficiency, improve profitability, and pursue new opportunities beyond property cat. The industry needs an improved standard.
Fortunately, an intriguing possibility exists. Over the past several years, RMS has researched and built a comprehensive and flexible new data container called a Risk Data Object. This data specification can handle any type of model, any line of business, and any financial terms and conditions.
Mid-January saw the publication of the annual World Economic Forum (WEF) “Global Risks Report” timed to set the agenda during this week’s WEF Annual Meeting in Davos.
With each new edition – and this year’s edition is the fifteenth, inevitably, one first turns to the opening page of the report, to discover the Top Five Global Risks for 2020, in terms of their “likelihood” and “impact”. What has been trending and what has slipped down the chart?
The World Economic Forum (WEF) has celebrated its fiftieth-year at its annual meeting in Davos. Increasingly the business/political nexus has become that articulated in WEF founder Klaus Schwab’s Davos Manifesto, that corporations “… must assume the role of a trustee of the material universe for future generations.”
In 2020, “Action on climate change” has now become the number one risk in terms of impact in the World Economic Forum’s Global Risk Report. The work at RMS on quantifying risk and exploring how risk is expected to shift under climate change has never been more important or timely.
In March 2018, RMS hosted the U.S. Geological Survey (USGS) workshop at our Newark headquarters in California to discuss the interim updates planned for the 2018 USGS National Seismic Hazard Map Project (NSHMP). Details can be found in my previous blog: Are You Ready for an Interim USGS NSHM Update?
The USGS informed the public and technical community about this interim update ahead of their regular six-year cycle of updates anticipated after 2020. The main purpose was to incorporate new ground motion modeling advances for Central and Eastern U.S. from Project 17, which has significant value for the national building code (details can be found here).
Towards the end of 2018, the USGS published the draft document and national hazard maps to receive scientific peer review and public feedback from the user community (Petersen et al. 2018). Since then, the USGS has been very busy incorporating the updates and finalizing the models. In December 2019, they published the official 2018 USGS NSHMP document in the Earthquake Spectra journal.
In our previous blog post, we reviewed how RMS has developed Risk Maturity Benchmarking, a tool to help clients understand their current processes and maturity and create a blueprint for improvement tied to their business strategy.
In 2017, RMS conducted a Risk Maturity Benchmarking (RMB) study for IRB Brasil Re (click here to read the full case study) to assist IRB on the implementation of their three-year transformation plan.
The IRB Transformation
Plan objectives were closely aligned to the company’s primary strategic
drivers. These included:
To grow IRB’s international presence as a “best in class” global reinsurer
To achieve greater capital efficiency across all business lines
To develop a market-advancing Enterprise Risk Management capability
To maintain a focus on innovation as a key differentiator
To achieve a competitive advantage by advancing modeling and analytical capabilities
Helping clients through the evolution of catastrophe modeling is a core mission for RMS Consulting. To assist in the process we have developed a tool called Risk Maturity Benchmarking, which we’ll introduce below, that helps our customers do this. Secondly, we will review an example where we have applied this framework with a client to create their own target operating model for catastrophe risk.
I don’t believe we would have achieved what we have if we had not first undertaken the RMB study
Luis Brito, head of catastrophe modeling, IRB Brasil Re
The industry is presented with both challenges and opportunities as the pace of change in the (re)insurance industry accelerates. Challenges include increased M&A activity, the entry of alternative capital and continued rate pressure, coupled with catastrophe losses from 2017 and 2018. These headwinds are contrasted by opportunities: an expanding protection gap which is not being filled quickly enough by the market, and technology – from data analytics to automation, frequently touted as the Holy Grail. All these factors have forced the industry to look at itself and reexamine how and where to compete in this brave new world.
This week marks the tenth anniversary of
the devastating earthquake in Haiti. The magnitude 7.0 event ruptured a thrust
fault associated with the Enriquillo-Plantain Garden fault system 25 kilometers
(16 miles) west of the capital city Port-au-Prince. This fault system runs
along the length of the Tiburon Peninsula and is no stranger to earthquakes,
with major events impacting Haiti in both 1751 and 1770. This large time gap since
the last major events meant that there was little to no societal memory or
preparedness for earthquakes in the region, making the 2010 event particularly
In the 2010 event, the strong ground shaking lasted 30 seconds and caused extensive collapse of masonry and concrete structures due to both poor design and construction practices, and poor construction material quality. An estimate for the resulting death toll is a staggering 150,000 people.
The scale of the damage and the number of people killed impacted all aspects of life for the remaining inhabitants of Port-au-Prince and the surrounding regions. Vital infrastructure including hospitals, communication systems and transportation facilities (e.g., the airport and port in Port-au-Prince) was severely damaged or destroyed, hampering disaster response. With 250,000 homes severely damaged, more than one million people needed to be housed and fed.
The sheer scale of the Australian bushfires is hard to comprehend, as what has already been a long bushfire season continues apace. Australia’s most-populous state, New South Wales (NSW) has been the worst-affected, with 12.1 million acres (4.9 million hectares) burnt over the current bushfire season. According to the New South Wales Rural Fire Service, damage has recently escalated with 672 homes destroyed since January 1, during a season which has seen 1,870 homes destroyed and 653 damaged.
There has also been reports of significant damage in the neighboring states, including Victoria to the south and Queensland to the north of NSW. Overall, across southeast Australia, 15.6 million acres (6.3 million hectares) have burned, and 25 people have been killed as of January 7. According to the Insurance Council of Australia (ICA), as of January 10, a total of 10,550 claims have been filed since November 8, amounting to around AU$939 million (US$645 million) in insured losses. The ICA notes that it expects more claims to be filed in the coming weeks.
Australian insurers are under the spotlight, but are holding up very well – insurer IAG has publicly stated it was “… on track to blow its perils allowance for the six months to December by AU$80 million” but had strong reinsurance in place. The article in Financial Review commented that there may be a modest effect on earnings for the industry overall, and premiums may have to rise.