Automated Assumption Management System

Purpose

Automated Assumption Management System is designed for insurance use cases where machine learning detects shifts in claims or exposure trends and recommends updates to assumptions automatically.

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 assumption monitoring and update processes, triggered when claims or exposure trends are analyzed against available historical and external datasets.

Key capabilities / workflow

The workflow analyzes historical losses, exposure data, and external economic indicators, checks whether shifts are detected, validates whether indicators support the shift, and then recommends assumption updates when appropriate.

Inputs

Typical inputs include historical losses, exposure data, and external economic indicators. Other input requirements are not specified.

Outputs / Deliverables

The main output is a recommendation to update assumptions when shifts in claims or exposure trends are detected. Other deliverables are not specified.

Value

The agent supports faster and more systematic identification of changes in claims or exposure patterns, helping insurance teams keep assumptions aligned with observed trends and available indicators.