AI-Assisted Climate Risk Stressing

Purpose

AI-Assisted Climate Risk Stressing is designed to combine external climate models with AI pattern recognition to simulate how event frequency and severity may shift under climate scenarios for insurance-related climate risk analysis.

Primary users

The primary user is not specified in the provided information. The agent is associated with the AQS team and owned by Ronan Davit.

Where it fits (process/stage/trigger)

This agent fits into climate risk stressing activities where insurance teams need to assess changes in event frequency and severity under defined climate scenarios using climate projections, hazard data, exposure data, catastrophe models, and loss data.

Key capabilities / workflow

The agent uses external climate models and AI pattern recognition to analyze provided climate and risk datasets, evaluate whether sufficient information is available, simulate scenario-driven shifts in event frequency and severity, and iterate until the stress scenario analysis is complete.

Inputs

Inputs are not specified in the provided information. The datasets explicitly listed for the agent are climate projections, hazard data, exposure data, catastrophe models, and loss data.

Outputs / Deliverables

Outputs are not specified in the provided information. The available use case indicates that the agent supports simulation of event frequency and severity shifts under climate scenarios.

Value

The value of AI-Assisted Climate Risk Stressing is to support insurance climate risk analysis by combining external climate models with AI-based pattern recognition, helping users explore how climate scenarios may affect event frequency and severity.