NEWARK, CA – March 10, 2022 – RMS®, a world leading risk modeling and solutions company, today announced an expansion to its latest suite of RMS Climate Change Models, to enable customers to strategically assess the near- and long-term impacts of climate change across a wider range of perils and regions.
The new models are now generally available for major perils including U.S. Flood, U.S. Wildfire. Japan Typhoon (including tropical cyclone induced inland flood) will be generally available in August. The existing North Atlantic Hurricane Climate Change Model will also now incorporate sea-level rise projections for the United States, including the impact of vertical land movement, for example, areas of land sinking in the Gulf region.
The RMS Climate Change Models address the growing need for climate change analytics in operational underwriting and portfolio management activities, in addition to supporting the increasing demands of regulatory requirements such as those from the Task Force on Climate Related Financial Disclosures (TCFD), and the Network for Greening the Financial System (NGFS).
These new RMS Climate Change Models will complement the existing suite launched in 2021, including Europe Flood, Europe Windstorm, and North Atlantic Hurricane Climate Change Models. The new Climate Change Models empower RMS’s economic modeling framework with a robust climate science consensus, including from the Intergovernmental Panel on Climate Change (IPCC).
Across all the RMS Climate Change Models, customers will be able to simulate the effects of climate change across four greenhouse gas concentration trajectories (known as Representative Concentration Pathways, or RCPs) at any time between 2020 and 2100.
Julie Serakos, Senior Vice President, Model Product Management, at RMS, said: “The effects of climate change up until now are already incorporated into RMS models, including all major peril models. What is becoming increasingly important for businesses is the ability to look forward at the potential impacts of climate change, across portfolios, risks and liabilities. There is also a growing need to capture sensitivity around the potential impacts of historical climate change, for example in perils where the consensus on this is limited. Only with detailed, consistent, and reliable information around future climate change risks are businesses and executives able to make informed long-term strategic decisions to best reflect the interests for their business, stakeholders, and regulators.
As disasters with a climate related footprint, such as flooding, wildfires, and hurricanes, increase in incidence and severity, it is also clear that this is a problem not just for the future, but one that needs to be strategically dealt with today, with the best tools available to give the clearest insights.”
Paul Wilkinson, Head of Aggregation and Risk Strategy, Canopius, said: “The RMS models enable adjusting time horizons for the near- and long-term, combined with the full flexibility and range of the IPCC’s Representative Concentration Pathway (RCP) scenarios. Climate change presents one of the most significant risks to the (re)insurance industry. It is important to us to incorporate the latest science relating to climate change into our risk analytics in a manner that can be tailored to our needs and fully integrated across key business operations, such as portfolio management, near-term underwriting, and business planning.”
RMS climate change solutions also include climate change specialist advisory and consulting expertise, and regulatory, environmental, social, and governance (ESG), TCFD, and NGFS support.
The RMS Climate Change Models address the perils most impacted by climate change and feature:
RMS has been modeling natural catastrophe risk for the insurance industry for more than 30 years and has been leading research into the impact of climate change on catastrophic losses since RMS’s involvement in the 2007 4th Intergovernmental Panel on Climate Change (IPCC) Assessment Report.
You can learn more about RMS Climate Change solutions here: