Solutions

AI Governance Platform for Financial Services and Banks

Financial institutions run the most demanding AI governance requirements in the economy: SR 11-7 model risk expectations, GLBA data safeguards, SEC and FINRA conduct rules, fair lending law, and the EU AI Act for global operations. Trussed AI gives banking, capital markets, and fintech teams a unified control plane that governs AI where the risk actually occurs, at runtime, with real-time enforcement, complete auditability, and cost control.

What is an AI governance platform for financial services?

An AI governance platform for financial services is a runtime control layer that enforces policy across every AI model, application, and agent the institution operates, evaluating data access, outputs, and agent actions against regulatory and internal requirements before execution, and generating examination-ready evidence from every interaction.

What does regulated finance demand from AI governance?

Model risk discipline, SR 11-7-aligned inventory, monitoring, and documentation extended to LLMs and agents
Data protection, GLBA-aligned controls on customer financial information in prompts, outputs, and agent contexts
Conduct and communications, controls on AI-generated client communications under SEC/FINRA expectations
Fair lending, decision lineage for AI touching credit, with evidence to answer disparate-impact scrutiny
Operational resilience, failover, routing, and monitoring so AI dependencies don't become outage vectors

How Trussed AI governs financial AI

AI Control Plane, centralized runtime governance across apps, agents, and developer tools: policy enforcement, audit logging, security controls, usage visibility, and deployment flexibility for regulated environments.
Agentic Governance, real-time authorization of agent tool calls, data access, and workflow triggers with end-to-end oversight of multi-agent systems.
AI Audit Assurance, continuous evidence from every governed interaction, policy results, timestamps, model versions, data lineage, for internal review and regulatory examination.
Cost Governance, spend tracking and budget enforcement by team, workflow, and provider, with routing optimization and ROI visibility.
Governance Advisory, strategy, operating models, and approval workflows that move institutions from pilots to production controls.
Platform Integrations, proxy-based deployment, SDKs, and partner integrations across cloud and model providers.

Why financial institutions choose Trussed AI

Static policies and quarterly reviews can't govern systems that act in milliseconds. Trussed enforces policy at execution time, as a drop-in proxy with sub-20ms overhead and no application changes, and converts every interaction into exam-ready evidence. Institutions report roughly 50% less manual governance workload with violation rates under 1%.

Frequently Asked Questions

Can Trussed govern both internal copilots and customer-facing AI? Yes. One control plane governs employee tools, developer workflows, and production customer-facing AI, with policies scoped per use case and risk tier.

Does the platform support self-managed deployment? Yes. Managed and self-managed options keep sensitive data within your security boundary and satisfy institutional infrastructure requirements.

How does this relate to our existing GRC stack? GRC systems track the program; Trussed enforces it. Runtime evidence flows back to GRC as proof that documented controls actually operate.

Related resources