AI Risk Audit
Know your risk exposure before a regulator does
AI and data systems in regulated environments carry real accountability. When something goes wrong — a complaint, an investigation, an internal query — the first question is always the same: can you explain what your system did, and why?
Most organisations find they cannot. The system was built internally. The decisions seemed reasonable at the time. Nobody has independently examined whether the governance, data, or model holds up to scrutiny.
Independent risk assessment output — illustrative
The situations we're called into
When this becomes urgent
A regulatory enquiry lands
A regulator asks how your AI system reaches its decisions. You need to be able to answer — clearly, and fast.
A decision is challenged
A customer, employee, or partner challenges an automated decision. The accountability question goes up the chain to you.
An audit exposes gaps
An internal or external audit identifies AI and data systems with no documented controls, validation processes, or human oversight.
How the audit works
Data Inputs
Where does the data come from? Is it fit for purpose? Is the lineage documented? Are there quality controls?
Model Behaviour
How does the model operate? Is its behaviour consistent with its documentation? How does it handle edge cases?
Governance Controls
Who is accountable for this system? What approval processes exist? What happens when it produces an unexpected output?
Decision Outputs
What decisions does the system produce? How are they monitored? Can they be challenged or overridden?
What you receive
- A clear picture of where your risk exposure sits — before anyone external identifies it
- A gap analysis against what regulators expect to see
- A practical remediation roadmap, prioritised by severity
- Documentation you can present to an auditor, regulator, or board
- Recommendations for controls and validation processes
Delivery
Typically delivered within
2–3 weeks
from initial scoping call
Handled directly — no account management layer. You work with the person doing the analysis.
All engagements are treated in confidence. Work product is delivered to the commissioning organisation only.
Applied in practice
Designed regulatory reporting pipelines and data quality frameworks for a global bank's statutory submissions to the Bank of England — including validation controls and governance of data used in official regulatory reports.
Request an AI Risk Audit
A 30-minute call is usually enough to scope what's needed. No commitment — just a direct conversation about your situation.
Every enquiry is reviewed directly and treated in confidence.