Reverse Stress Scenario Discovery

Purpose

Reverse Stress Scenario Discovery uses unsupervised ML to identify combinations of adverse events that would breach solvency or capital thresholds in an insurance context.

Primary users

The primary user is not specified in the provided information.

Where it fits (process/stage/trigger)

This agent fits into insurance risk, solvency, and capital assessment processes where teams need to explore adverse scenarios using capital model outputs, portfolio exposures, loss simulations, and balance sheet data.

Key capabilities / workflow

The agent analyzes the provided datasets, applies unsupervised ML to discover adverse event combinations, checks whether identified combinations breach solvency or capital thresholds, and supports review of reverse stress scenarios.

Inputs

Typical inputs are capital model outputs, portfolio exposures, loss simulations, and balance sheet data. Additional user-provided inputs are not specified.

Outputs / Deliverables

Outputs are not specified in the provided information. Based on the stated use case, the deliverables should be treated as findings related to adverse event combinations that breach solvency or capital thresholds, with details to be confirmed in documentation.

Value

The agent helps insurance teams discover reverse stress scenarios by identifying combinations of adverse events that may threaten solvency or capital positions, supporting risk exploration and capital resilience analysis.