Model quality assurance P&C - Explainable AI Comparison Tool

Purpose

Model quality assurance P&C - Explainable AI Comparison Tool supports quality assurance for insurance models by using AI to extract model interpretability metrics, such as SHAP, and GenAI to produce human-readable summaries based on the available explainability metrics and documentation.

Primary users

The primary user is not specified in the provided information.

Where it fits (process/stage/trigger)

This agent fits into model quality assurance activities for property and casualty insurance when model output explainability metrics and related documentation need to be reviewed and summarized.

Key capabilities / workflow

The agent works by loading model output explainability metrics and documentation, extracting interpretability signals, checking whether the required metrics are available, generating a human-readable summary, and refining the summary if clarity is not sufficient.

Inputs

Typical inputs include model output explainability metrics, such as SHAP where available, and related documentation; other inputs are not specified.

Outputs / Deliverables

The stated output is a human-readable summary generated from model interpretability metrics; additional outputs are not specified.

Value

The agent helps make model explainability information easier to review by transforming technical interpretability metrics into readable summaries for model quality assurance contexts.