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As a catastrophe risk modeler, RMS® provides a range of modeling options that best accommodate our clients' needs. One focus area for clients is around the availability and quality of their exposure data, which can necessitate using limited aggregated exposure data to manage their risks. 

There are a host of reasons why a (re)insurer might not use detailed exposure data for modeling. In developing markets, detailed exposure data may not exist or not be reliable. A (re)insurer could be entering a new market and not have comprehensive data. Many insurance companies collect and compile from their insureds aggregate information that needs to be modeled, or the data needs to be provided to their reinsurance partners for modeling.

Having aggregated data should not be a barrier to accessing high-quality risk modeling. RMS offers a comprehensive, robust range of Aggregate Loss Models (ALM®) that can take aggregated data. Using RMS ALM profiles, clients can run peril analyses on aggregate portfolios for over 60 countries and regions.

RMS Launches New Aggregate Loss Models Benefiting From HD-Model Framework

We are pleased to announce a major investment and product launch for clients using ALM. Recognizing the importance of aggregate risk modeling, RMS is launching new ALM for the countries and perils in our growing high-definition (HD) model suite. This includes:

All models will be available on the RMS cloud-based analytics platform Risk Intelligence™ and use our cloud-native Risk Modeler™ application.

These new ALM have a distinct advantage: the latest, award-winning RMS HD-model framework. This includes the use of extensive probabilistic event sets covering tens of thousands of years, the best-available local market intelligence, and comprehensive industry exposure databases (IED).

The models offer flexibility to select sub-peril risks, such as wind, inland or coastal flooding, or fire and tsunami, depending on the model chosen. All this high-quality insight is delivered fast – a major benefit of Aggregate Loss Models – with the ability to run profiles in minutes or seconds. This matches the speed and agility needed for success in an increasingly competitive market.

Built At Scale Using Trusted Risk Profiles

ALM analyzes a (re)insurer's aggregate portfolio for a specific peril and matches the geographic resolution and line of business of the exposure data to an ALM profile (Figure 1). Each ALM profile calculates the overall frequency, severity, and associated losses from catastrophic events.

RMS leverages our more than 30 years of risk experience, including constructing the most robust IED, and supplements this data with assumptions regarding geographic distributions, construction inventories, and insurance policy structures.

ALM profiles available for the New Zealand Earthquake Model
Figure 1: ALM profiles available for the RMS New Zealand Earthquake Model

Improve Risk Management With New ALM Solutions for the RMS HD Model Suite

ALM is a critical tool that can deliver immediate value for (re)insurers and brokers of all sizes, ranging from the largest global broker to regional primaries managing risk portfolios – across the entire insurance value chain. It can offer fast risk insight into new markets or provide certainty where exposure data is incomplete or insufficient.

With ALM, Detailed Loss Models (DLM), and HD Models™, all available on the Risk Modeler application, clients can select the most appropriate model type for the task at hand.

Whether a client has HD models or uses ALM as standalone models, let’s look at two ways that ALM can help:

1) ALM complements RMS DLM and HD Models: Within a given exposure set, the quality of portfolio data can vary. Where exposure data quality is comprehensive, modelers can benefit from DLM and HD Models by quantifying risk down to the sub-peril, together with the flexibility to model complex cedant terms.

But in reality (re)insurers can lack exposure data, such as primary building characteristics, insurance coverage type, or policy structures.

ALM solutions serve a critical need to leverage robust intelligence on local market conditions, and as ALM uses the same HD-model framework, including the financial model, they offer a consistent approach to pricing risk across portfolios of varying detail levels.

2) ALM stand-alone analysis: For (re)insurers evaluating new market opportunities or benchmarking their performance, stand-alone ALM offers a gateway to HD modeling and the best science, advanced technology, and the most realistic distribution of risk in the market.

ALM offers a fast and easy way to measure performance using the latest RMS view of aggregate risk for distinct markets. With all ALM solutions available on Risk Modeler, our cloud-native modeling application, each model is fast and easy to deploy without requiring complex on-premises software and hardware management. This can dramatically reduce time to market and accelerate the integration of high-quality insights into business processes.

This commitment to delivering high-quality risk modeling for all clients, whether there are requirements from aggregated through to HD modeling, is important to RMS. ALM provides fast, efficient analysis while recognizing that, for a range of reasons, clients might not have detailed exposure data, may struggle with accessing reliable exposure data, or are managing data from third parties,

By utilizing the latest market knowledge and capturing the latest advanced science within the HD-model framework – all this accessible via the cloud using the Risk Modeler application – our new Aggregate Loss Models delivers significant new risk insights for clients using aggregate risk analysis.

If you would like a demonstration of the RMS Risk Modeler application together with our new ALM solutions, please email sales@rms.com.

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Chesley Williams
Chesley Williams
Senior Director, Product Management

Chesley manages the commercial development of the Moody's RMS earthquake and tsunami models for the Asia-Pacific region. Chesley joined the Model Development Group at RMS in 1995, with expertise in developing seismic source models.

Through her tenure at Moody's RMS, Chesley was a model developer for key products including the 2018 Moody's RMS Japan Earthquake and Tsunami HD model and earthquake models for Europe, Asia, and Latin America. Chesley has recently shifted roles from model development to product management to use her years of experience at Moody's RMS to facilitate strategic product development, product marketing, and product management.

Chesley holds a master's degree in geophysics from Stanford University, where she researched ground deformation associated with the 1989 Loma Prieta earthquake.

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