High-definition (HD) models

Low-resolution exposure data refers to when an individual location or portfolio has limited site details for modeling. For example, locations may only include ZIP or CRESTA-zone information that covers very large geographic areas. It also means the model will have significant impacts on modeled loss, particularly for highly granular perils like flood, where even a few feet difference can dramatically change the hazard level.

Moody’s RMS HD Models can help you overcome exposure data challenges with two approaches: aggregate loss profiles and our new disaggregation methodology. The disaggregation methodology distributes low-resolution exposure data to high resolution based on data layers including land-use and new Moody’s methods. This process allows users to still benefit from the full suite of HD Model innovations.

For those who want to run the latest award-winning Moody’s RMS HD Models in low-exposure areas, our aggregate loss model (ALM) profiles benefit from over 30 years of risk experience to deliver insights in minutes or even seconds. ALM leverages our extensive industry exposure databases and supplements this data with assumptions regarding geographic distributions, construction inventories, and insurance policy structures.

Two factors that can impact model run times are the number of portfolio locations and the size of the event set for a given peril/region model. A highly granular peril model, such as flood, will often have significantly larger event sets and, when coupled with a portfolio with over 1 million locations, it can take several days to run. Analysts often use workarounds to reduce run times, including splitting larger portfolios into smaller sections and then aggregating the results, but this can create a significant amount of time-consuming manual work to prepare the data.  

To meet risk analysts’ and cat modelers’ complex needs at scale, Moody’s developed Risk Modeler — a next-generation, cloud-based modeling application on the Intelligent Risk Platform™. As a cloud-native solution, Risk Modeler has the power to quickly run large portfolios (over 1 million locations) against Moody’s RMS HD Models, the industry’s most detailed and complete probabilistic models. All RiskLink DLMs and ALMs, as well as HD Models, can be run through Risk Modeler, providing users the power and speed that cloud-native architecture allows. As an example, running 1 million locations against the North Atlantic Hurricane DLM historical event set was 36 times faster in Risk Modeler.

Insurers often use multiple solutions to analyze the same portfolio, including different modeling software, model versions, vendors, and exposure management tools. Each tool typically uses a distinct financial engine that incorporates different methodologies for capturing and applying insurance and reinsurance policy terms, leading to inconsistencies when generating and aggregating losses.

The applications on the Moody’s Intelligent Risk Platform utilize a shared financial engine, applying (re)insurance policy terms consistently at every stage of the portfolio analysis process. The advanced financial model has been designed to capture the most complex policy terms, including hours clauses, reinstatements, and multi-year contracts.