Question

A financial services firm has deployed a custom AI model in Dynamics 365 Finance that scores vendor payment risk. Regulators require the firm to demonstrate, during an audit, exactly who changed the model's training data, when grounding data was modified, and when the model was retrained or its scoring thresholds adjusted. The architect must design the ALM and governance approach so these requirements are met without relying on manual record-keeping. Which approach best satisfies the regulatory requirement?

Accepted Answer

Enable auditing in Dataverse and Microsoft Purview to capture immutable audit logs of data and configuration changes, and manage model retraining and threshold updates through source-controlled ALM pipelines that record each deployment.

Answer

Store a shared spreadsheet in a SharePoint library where the data science team logs each retraining event and threshold change after it occurs.

Answer

Grant regulators direct read access to the production model and the underlying Dataverse tables so they can inspect the current state whenever needed.

Answer

Configure Azure Monitor alerts to notify the compliance team by email each time the model endpoint receives a scoring request.