RMS is constantly adding new capabilities to the RMS Intelligent Risk Platform™ (IRP), our open, modular, cloud-native digital foundation for RMS models and unified risk analytics. As the gateway to robust risk analytics and in-depth data, the IRP brings together a trusted data repository, collaborative applications, and open APIs to help deliver better business outcomes.
Our powerful, cloud-native applications hosted on the IRP are designed to allow multiple users to gain insights into potential hazards, exposures, and accumulations. During September, RMS released multiple updates for both its ExposureIQ™ and Risk Modeler™ applications, to give clients access to the latest technologies and innovations. This update will help show how RMS is continuing to invest in the latest science, technology, and data by providing an in-depth look at the new features and a brief overview of our improvements to existing capabilities.
In the IRP September releases, we added new features to Risk Modeler, our cloud-native catastrophe modeling application that unifies all our client’s risk modeling needs for greater workload and cost efficiency:
In addition, we also made several big improvements to existing capabilities of Risk Modeler and ExposureIQ, including:
An individual policy may appear like a good risk based on your underwriting guidelines. But you may think twice about insuring it if you see how it contributes to the overall portfolio risk. In the September update, Risk Modeler added the ability to run a marginal impact analysis to quantify the impact of writing additional layers to your reference portfolio. Marginal impact analysis will be available for the following financial perspectives:
Marginal impact analysis allows users to better understand the risk drivers within a portfolio, to improve profitability and deliver effective capital allocation.
RMS now has the largest portfolio of climate change catastrophe risk models, which includes North Atlantic Hurricane, North America Wildfire, U.S. Inland Flood, Japan Typhoon and Flood, Europe Inland Flood, and Europe Windstorm perils.
In the September update, RMS expanded the capabilities to run climate change model analyses on U.S. Inland Flood HD Model results. Users can now apply climate change model analysis to a broader range of existing analyses and ensure that the application of climate change is consistent with the assumptions used in the development of the event mapping files. This update expands the High Definition (HD) profile settings to support additional simulation sets, 800,000 simulation periods, and number of samples greater than one.
Build a more consistent view of a book of business by aligning climate change model parameters with a reference view of flood and hurricane risk.
The latest Risk Modeler release updates the HD model RDM schema so that users can store and share results more easily at different granularities with their internal and external stakeholders.
The new RDM schema facilitates sharing HD results with other parties, helps consolidate storage for HD and DLM/ALM loss results, and simplifies query loss results using SQL scripts.
Risk Modeler currently supports 380 API operations. The September 2022 release updates RDM export and earthquake hazard lookup and adds a new service for marginal impact analyses APIs. For details, see the changelog in OWL.
Automate key workflows across applications using standardized, pre-defined processes.
ExposureIQ enables users to visualize and report on global exposure concentrations and hotspots. With a range of accumulation reports available, users can drill down to detailed geographic resolutions helping to quickly identify key drivers of loss.
RMS has expanded the set of geocoding resolutions on which users can run a geopolitical analysis or geopolitical spider accumulation to offer more geographical granularities for analysis. For geopolitical spider accumulations, users can now specify more geographic areas, including CRESTA and city-level. In addition, users can select from the expanded list of resolutions at which to calculate losses, such as running accumulations for every city within a given country. The table below summarizes all the types of accumulations currently supported by ExposureIQ.
|Sample Use Case
|Computes exposure concentrations by applying a set of damage factors to regions specified at some level of geographic granularity.
|Find the total exposure by postal code region.
|Computes exposure concentrations by applying a set of damage factors to regions defined by hazard layers
|Find the exposure for a theoretical loss scenario based on different damage levels realized for each depth band of a flood hazard map.
|Computes exposure concentrations by applying a set of damage factors to regions defined by event files representing real-world events.
|Find the exposure to an actual historic event based on different damage levels realized for each intensity band in the event footprint.
|Locates circular areas of a fixed diameter containing the highest level of exposure by applying band-specific damage factors to all exposures in up to three damage bands.
|Find the top 100-meter circles worth of total exposure within a specified search region.
|Locates geopolitical regions of a specified granularity that contain the highest level of exposure within the boundaries of a broader region.
|Find the Admin1 regions that have the highest total exposure within a set of countries.
Identify key loss drivers and more focused areas of exposure concentrations and hotspots.
For additional information on Risk Modeler, ExposureIQ, or the IRP, you can visit the Risk Modeler, ExposureIQ, or Intelligent Risk Platform webpages. You can also access release notes on OWL, the RMS Client Support portal.