In the spring of 2003, RMS pioneered quantitative event cancellation risk analysis with a study for FIFA in respect of the 2006 World Cup in Germany. As it happened, SARS was first reported outside China in February 2003, and was rampant throughout the duration of the risk analysis. At that time in London, as in Asia, sensible precautions such as avoiding busy Chinese restaurants was a rational defensive measure. Since the World Cup was scheduled for three years later – the summer of 2006, SARS was not considered as a cancellation risk. Terrorism was the primary risk to which investors in Golden Goal Finance Ltd were exposed.
Thanks to intensive global contact-tracing, and the need for an infected person to be symptomatic before being contagious, the World Health Organization was able to declare the SARS outbreak contained in July 2003. Nearly seventeen years after SARS, a novel coronavirus related to SARS appeared in China over a month ago in December 2019. Whereas SARS had a case fatality rate of about ten percent, the novel coronavirus (2019-nCoV) is more benign. The case fatality rate is currently estimated at just a couple percent. But even this level is highly disruptive, and all risk stakeholders will be anxious over the number of months before 2019-nCoV is contained.
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.
In 2017, WannaCry infected computers in over 150 countries across the globe, taking out critical functions such as the National Health Service (NHS) in the U.K. One year later, the NotPetya cyberattack brought many household names to a standstill. The pharmaceutical giant, Merck, was reportedly the source of US$1.3 billion of total impact to (re)insurers from the NotPetya attack, 87 percent of which was considered silent exposure. These two major cyberattacks highlighted to insurance carriers the risk of being exposed to silent cyber events and the need to start quantifying and managing that risk.
Regulators have started to
take notice. Since summer 2017, the U.K. Prudential Regulatory Authority (PRA) is
asking insurance firms to provide action plans on how they plan to address
their silent cyber risk. In November 2018, Moody’s announced it will soon start
evaluating organizations on their risk to a major impact from a cyberattack.
Following this, in July 2019, Lloyd’s announced a deadline of January 1, 2020
for all syndicates to start to address their silent cyber risk where “… all
policies provide clarity regarding cyber coverage by either excluding or
providing affirmative coverage.”
NotPetya and WannaCry were just two examples of
costly silent cyber events. As pressure from regulators mounts and cyberattacks
become more common, it is imperative to understand where silent cyber exposure
can be found, and how much it could cost you.
The Risk Data Open Standard (RDOS) Steering Committee that guides and oversees this standard was busy in 2019 working to shape the RDOS, to enable the risk industry to simplify risk management and risk data portability. The RDOS has traveled a long journey and is now proudly an open standard.
Much has been
published already about what the RDOS is. So, for this post I won’t focus on
the mechanics of the RDOS, instead I’ll focus on the “why and how” the RDOS is
open, and how it enables anyone in the industry to use and contribute to the
Just in case you are not familiar with this new standard, I will quickly introduce the RDOS, but the majority of the post will be on diving into the “open” part of the RDOS, and to unpack how we are reusing learnings from existing “open source and open standards” that have successfully created international and industry wide collaborations.
Epidemiologists are disease detectives. The
investigative insights of a forensic epidemiologist are exemplified by Sherlock
Holmes, whose creator, Arthur Conan Doyle, qualified as a medical doctor in
Edinburgh. With limited information, some of which may be dubious and
misleading, epidemiologists search for hidden clues as to the cause of a
disease and its manner of population spread and use statistical modeling techniques
to estimate the degree of disease contagion and the number of cases of
Prof. Neil Ferguson heads the World Health Organization (WHO) Collaborating Center for Infectious Disease Modeling at Imperial College London. His search for scientific understanding using sparse observational data dates back to his theoretical physics PhD at Oxford. Like others trained in theoretical physics, Prof. Ferguson is not shy in making mathematical forecasts that may be at odds with partial data of suspect reliability. Misreporting blighted the Chinese response to the 2002 SARS outbreak.
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.
When the Middle East Respiratory Syndrome (MERS) was first identified as a coronavirus in 2012, the case fatality rate was very high at 35 percent; but thankfully there was very low human-to-human transmission. Such transmission happened in healthcare settings, or to a much lesser extent in households where people caring for an infected person had close contact.
Camels were identified as a “reservoir host” for MERS, with infection primarily caused through direct contact with camel fluids. As evidence of very low human-to-human transmission, there were no MERS cases reported in either the 2012 or 2013 Hajj pilgrimage to Mecca, although an Indonesian couple may have caught MERS in the 2014 Hajj.
In China, there is an even larger annual migration tied to the lunar calendar – as the lunar New Year starts on Saturday, January 25. This is normally a time of happiness and celebration during family reunions. This year, there will be fear and foreboding over the new coronavirus, which emerged in December from a seafood market in Wuhan, Central China. On January 21, Chinese health authorities confirmed human-to-human transmission of the coronavirus. Fortunately, the case fatality rate seems to be quite low, just a few percent.
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 this the centennial year of the great 1918 pandemic, I was invited to speak at a special symposium on emerging infectious diseases at the renowned Pasteur Institute in Paris. One presentation that was both fascinating and alarming was on viruses in fish. I haven’t eaten raw fish since. When I heard that, in mid-December, a new form of pneumonia had struck a seafood market in Wuhan, central China, it seemed like a new fish disease affecting humans might have finally emerged. It turns out that the seafood market at the center of the outbreak also sold live animals and meat from wildlife such as snakes and marmots, and a wildlife primary infection source is most probable.