AI Systems Regulatory Audit
AI governance that audits what your systems actually do
Entercept AI evaluates AI-agent behaviour against applicable regulatory requirements and organisational policies, creating an auditable record of the rules that applied, the behaviour observed, the resulting findings, and the evidence supporting them.
The domain
Audit AI systems and autonomous agents against the rules that apply to them
Entercept AI examines how an AI system actually behaves, evaluates that behaviour against applicable regulatory obligations and internal policies, and produces an auditable record of the findings and supporting evidence.
Regulatory obligation mapping
The obligations that apply to this system, in this jurisdiction, for this use case are identified and stated before anything is tested. Every later finding points back to a specific obligation rather than a generic risk score.
AI policy evaluation
Your own AI policies, acceptable-use rules and model standards are treated as testable requirements. We check whether the system's behaviour matches what your organisation has committed to, not whether the document exists.
AI-agent behaviour auditing
Agents are exercised under defined and adversarial conditions: what they decide, what tools they call, what they disclose, when they escalate and how they fail. Observed behaviour is the subject of the audit.
Evidence generation
Each observation is captured with its inputs, parameters and method version, then digested and committed before any finding is written. Conclusions reference evidence by digest, never by description.
Audit trails
Scope decisions, runs, reviewer actions and report issuance are written to an append-only log. The chain from raw observation to published finding stays verifiable long after the engagement closes.
Governance controls
Access, change management, logging, monitoring and escalation paths around the system are assessed as operating controls, with the gaps between the designed control and the one running in production recorded.
Human oversight requirements
Where a regime or an internal policy requires meaningful human review, we test whether that review is real: whether the reviewer can see enough, has time to act and can actually overturn the system's output.
The distinction
Policies on paper against behaviour in production
Most AI governance work stops at whether a policy exists. An audit has to go further and establish whether the system does what the policy says, because that is the question a supervisor, an auditor or a customer will eventually ask.
See the assessment stages- Policy check
- A policy exists and is signed off
- Entercept audit
- The system's behaviour is tested against what that policy requires
- Policy check
- A control is described in a document
- Entercept audit
- The control is exercised, and the gap to production is recorded
- Policy check
- An agent is declared to have guardrails
- Entercept audit
- The agent is probed until the guardrails either hold or do not
- Policy check
- Human oversight is named in a process map
- Entercept audit
- The reviewer's ability to see, question and overturn is tested
The output
An auditable record, not an opinion
Every audit produces the same four-part record. It is designed to be handed to someone who was not in the room and still hold up.
- 01
The rules that applied
The regulatory obligations and organisation-specific policies in scope for this system, in this jurisdiction, for this use case, fixed before testing begins.
- 02
The behaviour observed
What the system and its agents actually did under defined and adversarial conditions, captured with the inputs, parameters and method version that produced it.
- 03
The findings that follow
Each finding stated against a specific obligation or policy clause, with its severity, its rationale and the remediation required to close it out.
- 04
The evidence behind them
Content-addressed evidence committed before interpretation, written to an append-only trail that remains verifiable after the engagement closes.
Regulatory domains
Where the audit is applied
The same audit core, applied to the regulatory context you operate in. Financial services and legal services are where it is asked for most often.
AI governance and regulatory auditing for banking, fintech, insurance, and investment and financial services.
Areas covered
- Banking
- Fintech
- Insurance
- Investment and financial services
AI governance and regulatory auditing for law firms, legal technology and AI-assisted legal workflows.
Areas covered
- Law firms
- Legal technology
- AI-assisted legal workflows
AI Systems Regulatory Audit
Audit AI systems and autonomous agents against applicable regulatory requirements, organisational policies, and governance controls.
Audit scope
- Regulatory obligation mapping
- AI policy evaluation
- AI-agent behaviour auditing
- Evidence generation
- Audit trails
- Governance controls
- Human oversight requirements
Which requirements apply depends on your organisation, your jurisdiction, the AI use case and the regulatory framework in force. Each engagement assesses the obligations and organisation-specific policies agreed as in scope. Entercept AI does not provide legal advice and does not guarantee regulatory compliance.
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See how independent, evidence-backed assurance works on a real high-risk AI system, then get an audit-ready report your regulators, board and customers can rely on.