GenAI Model Data Quality Scoring Assistant

Purpose

The GenAI Model Data Quality Scoring Assistant supports insurance model data quality assessment by computing data quality KPIs and generating qualitative scoring with explanations for dimensions such as accuracy, completeness, and consistency.

Primary users

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

Where it fits (process/stage/trigger)

This assistant fits into data quality review activities for model datasets, particularly when data quality KPIs and audit metadata are available and need to be transformed into qualitative scoring and explanations.

Key capabilities / workflow

The assistant uses model datasets, data quality KPIs, and audit metadata to support AI-based computation of data quality KPIs and GenAI-based generation of qualitative scores and explanatory rationale for accuracy, completeness, and consistency.

Inputs

Typical inputs are not specified by the user. The available dataset information includes model datasets, data quality KPIs, and audit metadata.

Outputs / Deliverables

Typical outputs are not specified by the user. Based on the provided use case, the assistant produces qualitative scoring and explanations for data quality dimensions including accuracy, completeness, and consistency.

Value

The assistant helps improve data quality assessment by combining KPI-based evaluation with qualitative GenAI explanations, supporting clearer review and auditability of model dataset quality in an insurance context.