A practical governance framework for CCOs and CROs evaluating AI analytics tools — covering audit trail requirements, reproducibility standards, data residency obligations, and the structural reasons general-purpose AI tools cannot meet them.
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Each is individually traceable to a specific regulatory requirement. These are not aspirational — they are enforceable.
Same inputs, same output — every time. LLMs are temperature-sampled stochastic processes. They structurally cannot be deterministic.
Every run: input hash, method versions, parameters, user identity, timestamp, output. Immutable. Queryable by regulators.
EU client data sent to OpenAI's US endpoints violates GDPR. The analytics engine must run inside the firm's own environment.
Every method: formal specification, parameter schema, assumptions, limitations. Examiners must be able to point to the exact computation.
Before AI-assisted output is distributed, a documented human review step must occur. The reviewer identity and timestamp must be logged.
Anomalous output must be flagged before distribution. A metric 3σ below the firm's own history distributed silently is a compliance failure.
This document is provided for informational purposes and does not constitute legal advice.