Your platforms provide controls. We build the governance program around them.

Financial firms are adopting AI ahead of the governance that has to stand behind it. The platforms handle identity, policy, and audit. No platform ships the program itself: output controls, model risk, and the record a regulator will actually test. That is the mandate.

The Framework

Identity, policy, and audit come with the platform. The program does not.

Map any modern platform against the controls a regulator expects and the same pattern appears. Identity, policy, and audit are native. Data loss prevention is partial. Output controls and model risk management are a gap on every platform. No vendor ships a program.

That invariant is the practitioner mandate. It is also the standing answer to the obvious question: won't the platforms just build this? Platforms provide technical controls. They do not build your governance program, own your risk, or sit across the table during an examination.

Fig. 1The invariant: where platform controls leave gaps
Identity · Policy · Audit
Native to the platform. Provisioned, enforced, and logged by the system of record.
Native
Data Loss Prevention
Partial. Present in fragments, rarely mapped to a defensible policy across the AI surface.
Partial
Output Controls · Model Risk
Gap. No platform ships a program. This is the practitioner's work.
Gap
The framework's existence is the credibility signal. The mapping itself is the paid artifact: the Platform-to-Program Control Mapping.
Engagement

A defined path from first conversation to a program that holds under examination.

  1. Stage 01

    Orientation

    A working conversation about your stack, your regulators, and where AI has moved ahead of your controls.
  2. Stage 03

    Program Build

    Output controls, model risk management, and governance policy, built to close the gaps the mapping surfaced and designed to be sustained in daily operations.
  3. Stage 04

    Standing Advisory

    Board reporting, regulatory narrative, and examination support on a continuing basis, kept current as your obligations, platforms, and business change.
Regulatory Ledger

The program is built against current guidance, not last cycle's.

SR 26-2 · Model Risk Management
Interagency guidance for banking organizations with over $30 billion in total assets and, in some cases, smaller banking organizations with significant model risk exposure. It supersedes SR 11-7 and SR 21-8. Generative and agentic AI models are outside its scope.
Issued Apr 17, 2026
Financial Services AI RMF
Developed by the Financial Services Sector Coordinating Council in collaboration with Treasury, the framework includes 230 control objectives across the AI lifecycle and can be scaled to a firm's stage of AI adoption.
230 control objectives
SEC · FINRA
Marketing, communications, and surveillance obligations. This is the examination surface where AI adoption meets existing rules.
Exam context
Who We Serve

Firms adopting AI ahead of the governance infrastructure to hold it.

  • Registered investment advisers, broker-dealers, funds, and fintech firms that need clearer ownership, controls, and evidence around AI-enabled operations.
  • Tech-forward practices moving faster than a template compliance program can follow.
  • Firms that want a practitioner in the room, not a report on the shelf.
  • Teams preparing for an examination who need the record to hold before the regulator asks.
Perspectives
  • Analysis

    Reading SR 26-2: the carve-out for generative and agentic AI

    SR 26-2 supersedes SR 11-7 but places generative and agentic AI models outside its scope. What that means for a firm running models it did not build.
    Forthcoming
  • Essay

    The four ways autonomous leverage fails

    A synthesis of where AI-enabled scale breaks a compliance program, and which of those breaks a regulator sees first.
    Forthcoming
The Practitioner

Twenty years of registered practice, on the side of the table you're preparing for.

Two decades inside financial services: managing client relationships, navigating examinations, and operating under the same rules our clients live by every day.

That experience is the work AI-powered infrastructure alone cannot do: interpreting risk, building governance policy, and telling leadership what the findings actually mean for the firm.

We build governance that can be explained and supported with evidence before regulators, boards, and clients.

Contact

Start the conversation about what your firm needs to be ready.

Whether you are preparing for an examination, evaluating AI vendors, or building a governance program from the ground up, this is where it begins. Send an inquiry and we will follow up by email. A free consultation is available.

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