Banking & Investment
AI Model Risk Management
for Agentic AI in Banking
SR 26-2 replaced SR 11-7 in April 2026 and left generative and agentic AI out of scope. Examiners still expect those agents to be governed. Lumenova AI gives your model risk, AI, and technology teams the controls, tests, and evidence to do it.
What Does AI Model Risk Management Look Like for AI Agents?
AI governance in finance was built for models that predict. For agents that act, AI model risk management rests on four disciplines:
- Materiality Tiering
Scrutiny scaled to what each agent can affect, from internal notes to moving money. - Effective Challenge
Validators who can question an agent’s controls, independent of the team that built it. - Use Limitations
Enforced boundaries on where and how each agent may act, not conditions in a memo. - Change Triggers
A fresh review whenever an agent’s model, tools, or policy changes.
Lumenova AI does all four in one place, so banks and investment firms can scale agents without losing control.
AI model governance in finance shifted on April 17, 2026, when SR 26-2 and OCC Bulletin 2026-13 replaced SR 11-7 and left agentic AI outside their scope. That puts the decision on your second line, the model risk and validation teams who decide how far to trust each agent.
In Canada, OSFI Guideline E-23 covers every model, AI included, from May 1, 2027, so AI governance for financial institutions now spans two very different rulebooks.
Where AI Agents Work in Banking and Investment
From credit reviews to client service, agents handle sensitive data and support consequential decisions.
Each use case needs clear limits on access and actions, with a record of what the agent did.
Credit and Lending
Agents gather documents and draft file summaries for underwriters. If a decision leads to an adverse action notice, the bank may have to explain the agent's part in it.
Fraud and Financial Crime
Agents triage alerts and assemble case files with access to account and transaction data. A wrong closure is a missed case, and a leaked file is a data incident.
Wealth and Client Service
Assistants summarize portfolios for advisors, answer client questions, and update accounts. One unapproved statement or exposed record reaches a client directly.
Capabilities
How Lumenova AI Helps Banks and Investment Firms
Bring AI initiatives into production with controls your teams can enforce, evidence reviewers can verify, and clear accountability across the firm.
Agent Inventory
Register each agent with its owner, approver, and risk tier, and catch unregistered agents calling models on your network.
Validated Evaluations
Test agents before launch and in production, and check automated scores against your own reviewers.
Pre-Action Limits
Set what each agent may do, such as a refund ceiling or the accounts it may touch, and enforce it before the action runs.
Second- and Third-Line Evidence
Every decision is recorded with the rule, the reason, and the input, ready to export for validation and audit.
Vendor Agent Testing
Probe third-party agents from the outside and keep the evidence behind each finding for your third-party risk review.
Spend Controls
See AI cost by agent, team, and use case, and set budget ceilings before the invoice arrives.
Frequently Asked Questions
No. SR 26-2 and OCC Bulletin 2026-13, issued April 17, 2026, place generative and agentic AI models outside their scope and point banks to their broader risk management practices. Traditional models and non-generative AI remain in scope. Banks still have to show examiners how agents are governed, which is the gap Lumenova AI fills.
A model produces an estimate that a person uses. An agent acts: it calls tools, moves data, and hands work to other agents. Governing it means controlling each action before it runs and recording why it was allowed, on top of testing the model underneath. Lumenova AI does both.
An examiner wants to see what the agent did, what it was allowed to do, and why. Lumenova AI records each decision with the rule that applied, the outcome, the reason, and the full input, and traces every step the agent took. Banks and other BFSI firms get the decision lineage an examiner asks for, without rebuilding events from logs.
Yes. Lumenova AI tests vendor agents from the outside, the way a real user or attacker would, and keeps the request and response behind each finding. Vendor agents whose calls pass through your gateway can also be registered, limited, and monitored like your own.
OSFI Guideline E-23 takes effect May 1, 2027 and covers all models at federally regulated financial institutions, AI included, across their lifecycle. Lumenova AI supports that work with an agent inventory, lifecycle approvals from intake to retirement, continuous evaluation, and decision records your model risk team can use as evidence.