Peril Models

Understand RMS peril models


Risk Modeler enables underwriting organizations to analyze and project financial loss for exposures using a variety of RMS peril models.

A peril model is a computer-based model that estimates losses from natural or man-made hazards, such as earthquakes, floods, hurricanes, and acts of terrorism. RMS peril models enable insurers, reinsurers and other organizations to quantify the potential magnitude and probability of economic loss from catastrophe events.

Risk Modeler supports three types of peril models: Aggregate Loss Module (ALM) models, Detailed Loss Module (DLM) models, and High Definition (HD) models.

Depending on the peril model used to generate the risk analysis, Intelligent Risk Platform may generate many different event loss data. The analysis result is a projection of the losses to an exposure for all financials and perils based on a peril model.

ALM models

ALM peril models provide a faster alternative to the Detailed Loss Module (DLM) for streamlined analysis results. Rather than using detailed modeling capabilities, ALM is designed to use data with no per-risk details, such as precise locations or building characteristics. Values are entered as exposed limit per line of business.

DLM models

DLM peril models simulate natural catastrophe events and generates hazard analyses and estimates of potential loss. It performs exceedance probability analyses (EP analysis) and considers a full range of possible events and losses.

The word detailed refers to the type of information required by the module for analysis: detailed address information (postal code or better) and primary building characteristics (construction, occupancy, year built, number of stories) are preferred during a DLM analysis. Secondary modifiers may also be considered, if available.

HD models

HD peril models leverage the benefits of distributed cloud computing to realistically represent the exposure and losses from catastrophic events. These models simulate both the severity and frequency catastrophic events and consequently more realistically represent exposure and losses from these events.

HD modeling integrates correlation and time-based simulations, an approach that elminates the need to make assumptions about the probability distributions that describe the occurence of events and allows clear drill-paths through results from exceedance probability (EP) to location coverage (risk item) level.

HD modeling relies on a simlutation-based framework. RMS builds high definition models using a simulation approach that works at the highest possible resolution, and integrates correlation and time-based simulations. This approach removes the need for assumptions about the probability distributions describing event occurrence, and allows clear drill-paths through results from exceedance probability (EP) to risk-item level.