Model risk management for banks running AI, before the examiner asks.

"We need a complete, current inventory of every model in production, including vendor models and AI systems."

SR 26-2, Model Inventory Requirements Inventory completeness is the most common examination finding. 68% of banks with AI platforms have at least one system that does not appear in the model inventory. OCC issued MRAs to 14 institutions in 2024 for this single gap.

→ Nexovern's automated discovery identifies models and AI systems across the environment before examiners arrive, closing the gap between what is deployed and what is recorded in the inventory.

"Every model requires independent validation with effective challenge, documented and repeatable."

SR 26-2, Model Validation Validation must be performed by parties independent of the model development and implementation process. Examiners evaluate whether the challenge function is substantive, not merely procedural, and whether findings are tracked to resolution.

→ Nexovern provides correlated app-layer and system-level evidence for every model and AI system, giving independent validators the raw data they need for substantive challenge and reproducible findings.

"Models must be monitored continuously for performance degradation, drift, and unexpected behavior."

SR 26-2, Ongoing Monitoring Periodic review alone is insufficient. Examiners expect continuous monitoring with defined thresholds, escalation procedures, and documented change-control processes whenever model behavior deviates from established baselines.

→ Nexovern's runtime monitoring captures continuous performance and drift evidence, providing the documented baselines and deviation alerts that examiners expect to see in production.

"The board must approve a model risk management policy with clear ownership, risk tiering, and escalation paths."

SR 26-2, Governance and Controls SR 26-2 requires a board-approved MRM policy that defines roles, responsibilities, risk appetite, model tiering criteria, and reporting lines. Governance gaps contributed to the 41% increase in examination findings during 2024.

→ Nexovern enforces governance policies at the endpoint, ensuring that risk-tiering decisions, approval gates, and escalation paths are applied consistently across all AI systems, not just documented in a policy manual.

"Documentation must cover the entire model lifecycle, from development through deployment, monitoring, and retirement."

SR 26-2, Documentation Standards Examiners evaluate documentation for completeness, accuracy, and currency. Model documentation must include purpose, assumptions, limitations, data sources, validation results, and performance monitoring outcomes for every model in the inventory.

→ Nexovern's evidence exports produce examination-ready documentation that maps directly to SR 26-2 expectations, reducing the manual effort of assembling lifecycle records across siloed teams.

"Generative and agentic AI systems are excluded from SR 26-2 scope, but they still require governance."

SR 26-2, Scope Exclusion for GenAI SR 26-2 explicitly excludes generative and agentic AI from the formal model definition. However, the interagency statement confirms that general risk management, third-party risk, and consumer protection obligations continue to apply. A planned interagency RFI on AI model risk management will address these systems directly.

→ Nexovern governs AI agents regardless of whether they meet the formal "model" definition, providing the inventory, monitoring, and evidence trail that will be required when the interagency RFI produces binding guidance.