A compliance engineer is configuring Microsoft Purview for a banking organization that uses AI for loan underwriting decisions. The EU AI Act requires that high-risk AI systems maintain logs sufficient for post-hoc auditability of individual decisions. Which combination of Azure services provides the required audit trail for each AI-driven loan decision?

B is correct because EU AI Act auditability for individual loan decisions requires capturing the complete decision context: the input data (loan applicant features), the model version used, the model's output (score/recommendation), and the decision rationale. Azure OpenAI diagnostic logs capture the prompt and response (including input features and model reasoning), while Azure Cosmos DB provides a structured, queryable audit store for per-decision records with all required fields. This combination enables post-hoc reconstruction of any individual decision. A is incorrect because model monitoring with drift detection and performance metrics provides aggregate model health insights, not individual decision-level audit records required for EU AI Act compliance. C is incorrect because Purview Audit (Premium) captures event metadata and API call records but may not contain the complete input feature set and decision rationale needed for individual decision auditability. D is incorrect because Data Factory pipeline logs track ETL data movement and AML experiment tracking monitors training runs; neither provides individual inference decision audit records.