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.
Terrorism is a global menace that spreads like a virus along social networks. On March 15, 2019, Brenton Tarrant killed 51 Muslims attending Friday prayers at two mosques in Christchurch, New Zealand. Terrorism is the language of being noticed. Shortly before his rampage, he emailed his white supremacist manifesto, The Great Replacement, to the New Zealand Prime Minister’s office and media outlets, and shared a link with 8chan, a counter-culture website associated with political extremism.
Ever since the Christchurch mass shooting, 8chan users have commented regularly on their desire to beat Tarrant’s high score of victims. On Saturday, August 3, 2019, 21-year-old Patrick Crusius posted a four-page document, The Inconvenient Truth, on 8chan, which has since gone offline.
This expressed support for the Christchurch shootings, and blamed immigrants and first-generation Americans for taking away jobs. He also called for the deportation of immigrants. Such a white supremacist tirade is not unusual on 8chan. However, shortly after this posting, he headed for the Walmart near the Cielo Vista Mall, El Paso, Texas, and opened fire in the parking lot and store with an assault rifle. Mid-morning on Saturday, Walmart was busy with shoppers. His twenty-minute shooting spree left 20 dead with 26 people hospitalized. He then surrendered to police officers.
From our numerous client conversations, climate change as a business issue has risen high on the agenda, and this has certainly escalated over the last twelve months. There is a growing recognition of the need to quantify the impact that climate change will have on your business. But – where do you start with this? One of the major challenges is knowing what question to ask. With the inclusion of climate change scenarios within the General Insurance Stress Test (GIST 2019), which the larger U.K. insurers and Lloyd’s syndicates are required to respond to, the Bank of England Prudential Regulation Authority (PRA) is outlining one approach.
RMS is particularly well placed to support insurers in responding to the “Assumptions to Assess the Impact on an Insurer’s Liabilities” portion of the climate change section within GIST, which examines how changes in U.S. hurricane and U.K. weather risk under different climate change scenarios may affect losses.
The revised earthquake coverages and caps proposed by the New Zealand Earthquake Commission (EQC) came into law as planned on July 1, 2019. As noted in an RMS blog back in February, these well signaled changes – to increase the building coverage from NZ$100,000 to NZ$150,000 and remove the NZ$20,000 contents cover, only had a small effect on the gross average annual loss for both EQC and the private market. Swapping the first layer of contents exposure for a larger, higher layer of building exposure produced a result that was close to neutral.
Examining the Exceedance Probability (EP) curve (see figure 1 below), the changes are small across all return periods. There are small increases in loss for the private market at short return periods (which produce the small increase in average annual loss reported earlier) but very little change at long return periods.
Critically, the modeled gross 1000-year loss to the private market is essentially unchanged, meaning there are no implications with regards to the Reserve Bank of New Zealand (RBNZ) solvency requirements. Further, these EQC coverage changes are not expected to affect the peril balance driving trans-Tasman solvency considerations where both the RBNZ and Australian Prudential Regulation Authority (APRA) standards must be met.
The recent events that shook a relatively remote part of the Mojave Desert region of Eastern California provide an acute reminder of the major risk posed by earthquakes in the state. It has been a while now since California experienced a large earthquake, and the main event in this sequence – with a magnitude of Mw7.1, was the most powerful earthquake to occur in the state in twenty years.
Since then, the field of seismology as well as earth scientific measuring capabilities have undergone quite substantial improvements and innovations. Immediately after the start of the sequence, several coordinated efforts from academic, government and engineering organizations resulted in focused field surveys and the installation of additional, more densely spaced instrumentation to monitor seismicity and surface deformation, in and around the epicentral area.
So far, extraordinary amounts of high-quality data have been collected that will undoubtedly provide new insights and understanding of earthquakes in general and earthquake hazard and risk in (Southern) California, in particular. Work on these new data sets has only just started, but what have we learned so far? Here is a summary of observations and interpretations based on various (preliminary) field surveys, reports and briefings.
Assessing the risks faced by the city of Goma in the Democratic Republic of Congo (DRC) would go well beyond the norms of the insurance industry. On January 17, 2002, a large part of the city center was destroyed by an eruption of Mount Nyiragongo, about 20 kilometers (12.4 miles) to the north. Volcano hazard is not a significant risk factor for many towns and cities – and nor is Ebola. Goma is exceptional in being at risk from both.
Outbreaks of Ebola have occurred in the DRC sporadically in 1976, 1994, 2003, 2007 and 2012. The most recent outbreak started on August 1, 2018, and even with the infection of 2,500 and the deaths of more than 1,700, the Ebola virus is still not contained. Endemic hostilities in the DRC make it hard for health organizations to track contacts of those infected, and to operate treatment centers without fear of military attack. Health workers expose themselves daily to lethal infection – and should not be exposed also to armed assault. But they are – two health workers were killed in mid-July.
We are pleased to announce that RMS Risk Intelligence™ version 1.12 has now been released. This new release includes many improvements such as the introduction of new Structure Tags and Domain Data Tables related to items such as “Line of Business”, “Underwriting Group” and “Offer Type”. The release also includes an assortment of quality improvements.
With these Structure Tags, users can now sort and filter data in the Data Directory, delivering effective data organization capabilities on the platform. But while we realize getting your data into the platform is important – getting insights from your data off the platform is even more important. There are already plenty of options available to do this. You can get these insights from the user interface (UI), exporting your data via CSV files and our APIs. You can now use SQL or your own preferred tools to obtain deep insights into your data.
So, for the rest of this blog post, I want to give you a deep dive into a new, valuable tool available for Risk Modeler users on the Risk Intelligence platform that will help you generate reports – regardless of how you access your data or deliver your final report output.
It was off to another prestigious London venue last week for the RMS team, to attend the Insurance Post British Insurance Awards at the Royal Albert Hall. In addition to fulfilling lifelong dreams to see Rick Astley perform live, the RMS team was also competing for the Risk and Resilience Award, alongside four other very worthy contenders. And, first presentation of the night, I was delighted to represent RMS to collect this important award.
This award recognized our longstanding charity partner Build Change, who we have worked together with for six years. Both organizations share a mission: to reduce lives lost from disasters by strengthening the built environment in economically deprived areas.
By combining RMS’ risk modeling expertise and institutional support with Build Change’s technical knowledge and grassroots approach, we’ve been able to demonstrate that retrofitting buildings, from homes to schools, in vulnerable neighborhoods across the globe can significantly reduce economic loss and save lives. And one of our many collaborations was an initiative to greatly improve the safety of seismically-vulnerable communities in Colombia.
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. At RMS, we believe that 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 only standards the industry uses are decades-old property cat schemas – venerable work horses 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, we need a new standard.
Earlier this year, RMS released its latest medium-term rates (MTR) forecast for the North Atlantic hurricane basin as part of the North Atlantic Hurricane Models Version 18.1 release. Applicable over the 2019-2023 period, the Version 18.1 forecast represents an update from the previous MTR forecast issued in 2017 for the 2017-2021 period, by reflecting hurricane activity from the 2017 and 2018 seasons.
The MTR forecast provides a forward-looking estimate of the expected average annual landfall rate on a five-year horizon. Available alongside the long-term rates (LTRs) – a view of hurricane frequency based on the climatological average for the period from 1900 onwards, MTRs provide an additional perspective on expected hurricane rates on a shorter timescale. This allows RMS to adjust our view of risk according to the observed climate variability, and to combine different scientific theories on the drivers of hurricane variability over time, ultimately providing a view of landfalling hurricane risk that best represents the near-term basin conditions.