Compliance
Governing the use of AI in a regulated fund business
We identify where AI removes cost and where it quietly adds risk.
Every engagement begins with a scoping conversation. If a smaller package is the right starting point, we will say so.
Overview
AI adoption in private capital is now moving faster than the governance around it. Teams are using general purpose tools on fund and investor data, often without a clear policy, a record of what was processed, or an answer to the question an institutional allocator will inevitably ask during operational due diligence.
That question is becoming standard. How does the manager use AI, what data does it touch, who reviews its output, what happens when it is wrong, and how is any of this evidenced. A firm that cannot answer clearly is exposed on two fronts: regulatory expectation and investor confidence.
The Strategy
A governance framework is established covering permitted use cases, data classification, human review requirements proportionate to consequence, model and vendor selection, retention, and incident handling. The framework is written against the firm's actual regulatory obligations rather than as a generic policy, and it identifies which decisions may be supported by AI and which must remain human.
Controls are then implemented in the systems themselves rather than left as policy statements. Every AI interaction with fund or investor data is logged with its inputs, outputs, the model used and the person accountable. Review requirements are enforced at the point of use, sensitive data categories are restricted by design, and the resulting evidence is assembled into the pack that operational due diligence and regulatory enquiry will request.
Results Driven
The firm can adopt AI at pace with a defensible control environment behind it, which is a meaningfully different position from either avoiding the technology or deploying it informally. Teams know what they are permitted to do, and the accountable executives know what is happening.
Operational due diligence becomes a strength rather than an exposure. When an allocator asks about AI governance, the manager produces documented policy, implemented controls and a complete audit trail, which increasingly distinguishes a firm rather than merely satisfying a requirement.
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Of AI interactions with fund and investor data logged and attributable.
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Typical time to produce a complete AI governance evidence pack on request.
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Material findings raised on AI controls in investor operational due diligence.
