Terms

• component analysis

Overview

The Grouping API collects API operations that support the creation and management of analysis groups.

An analysis group is an analysis that combines multiple analyses. An analysis group may include analysis results generated using ALM, DLM, and HD models as well as other analysis groups. By combining event loss data from multiple analyses, you can view an unified loss result for exposures across diverse perils and regions.

The analysis group is processed together and returns EP metrics that take all portfolio exposures into account when calculating the probability that financial losses from catastrophe events will exceed certain thresholds.

Entitlements

Client must be assigned one of the following entitlements to use this API:

• RI-RISKMODELER
• RI-UNDERWRITEIQ

Operations

The Grouping API exposes the following operations:

Analysis types

Platform API 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.

Single Analyses

Group Analyses

A group consists of two or more portfolio-level, EP analysis types.

• Analysis Type

Any analysis type can be grouped with any other analysis type.

DLM
ALM
GROUP
HD
CEP
CEPGROUP
Accumulation

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 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.

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.

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Note

You cannot group HD analyses run prior to Feb. 25, 2021. On the Risk Modeler Results page, check the Create Date of the HD analyses you want to group. Rerun the analyses if they were run before this date.

Methodology

Grouping results generated using different engines (ALM, DLM, HD) use different methodologies during grouping: