AI-Enhanced Model Validation

Purpose

AI-Enhanced Model Validation is designed to use AI to benchmark internal model outputs against external data or peer distributions, helping identify potential weaknesses in model behavior or results.

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 within model validation activities in the insurance context, particularly when internal model outputs need to be compared with benchmark datasets, industry ratios, peer distributions, or external loss data.

Key capabilities / workflow

The agent supports a workflow that collects internal model outputs and relevant benchmark data, compares the outputs against external datasets or peer distributions, checks whether the available benchmark data is sufficient, retrieves additional external loss data when needed, and identifies potential model weaknesses.

Inputs

Typical inputs include model outputs, benchmark datasets, industry ratios, and external loss data. Additional input requirements are not specified in the provided information.

Outputs / Deliverables

Expected outputs include identified potential weaknesses based on comparisons between internal model outputs and external data or peer distributions. Additional deliverables are not specified in the provided information.

Value

The value of AI-Enhanced Model Validation is to strengthen model validation by using AI-supported benchmarking against external and peer-based references, helping teams detect possible weaknesses in insurance model outputs more efficiently.