This article is for informational purposes only and does not constitute financial or legal advice. You should consult with a qualified professional before making any decisions about your choice of platform.
What Questions Should I Ask About My Wrap Platform's AI and Automation Systems?
Ask your wrap platform where it uses AI, which client-facing or operational decisions it affects, and what evidence it can share about security, outages and human review. Tailor the questions to the services your clients actually use.
First establish what the provider actually uses in the services your clients receive. Do not assume that a platform uses AI in trade routing or other decisions without provider evidence. Assess the relevant advice, client-outcome and resilience requirements for the firm and service separately; a questionnaire response is not proof of regulatory compliance.
Why You Need to Ask About AI
Where a provider confirms AI use, consider whether the existing review covers these risks and what additional evidence is needed:
- Algorithmic Bias: The AI could be making decisions that unfairly disadvantage certain groups of your clients.
- "Black Box" Decisions: The platform may not be able to explain why the AI made a particular decision, leaving you in the dark.
- Automation Complacency: Over-reliance on automation can lead to errors being missed by human oversight.
- Security Vulnerabilities: AI systems can be a new target for cyber-attacks.
A Due Diligence Questionnaire for the Age of AI
Use these questions for the services and decisions relevant to your clients. Ask the provider which uses are live, which are planned and what supporting records it can share, including any limits on disclosure.
| Due Diligence Area |
Key Questions |
| 1. AI Governance & Accountability |
Who is the Senior Manager at the platform responsible for the governance of AI systems? Can you provide details of your AI governance framework? How do you ensure that your use of AI is compliant with the Consumer Duty? |
| 2. Use Cases & Transparency |
In which specific business processes are you using AI and automation (e.g., onboarding, fraud detection, customer support, trade routing)? Are you using generative AI in your client-facing communications or support channels? How are you transparent with advisers and clients about your use of AI? |
| 3. Algorithmic Fairness & Bias |
How do you test your AI models for bias to ensure they are not producing discriminatory outcomes for different groups of customers? What data are you using to train your AI models, and how do you ensure it is representative and free from bias? |
| 4. Human Oversight & Intervention |
What level of human oversight is in place for your automated processes? In what scenarios does a human review a decision made by the AI? What is the process for an adviser to challenge or appeal a decision made by an AI system? |
| 5. Security & Data Protection |
How do you protect our client data when it is being processed by your AI systems? Have your AI systems undergone independent security testing? What are your policies on using third-party AI tools (like ChatGPT) with client data? |
| 6. Performance & Reliability |
How do you monitor the performance and accuracy of your AI models over time? What is your process for managing "model drift"? What happens if an AI system fails? What are your backup and contingency plans? |
What a Good Answer Looks Like
Look for an answer that identifies the relevant system, owner, decision and available evidence. If the provider cannot share a record, ask what limitation that leaves in your assessment.
- Bad answer: "We use AI to enhance our services, and we take compliance very seriously."
- Good answer: A service-specific response naming the actual owner and live use, explaining review and escalation thresholds, and pointing to dated testing, change and incident records. Assess those records and their limits; no particular SMF role, universal fairness audit or transaction amount is prescribed by this example.
The Bottom Line: Your Reputation is on the Line
Record how the provider evidence relates to the services and client needs being assessed. Identify any gap that matters to the recommendation, rather than treat a broad technology assurance as an answer for every platform feature.
Check any applicable regulatory requirements against current primary guidance and the firm's activities. Review operational dependencies and recovery arrangements where relevant; this article does not establish the scope of an FCA obligation for a particular adviser or platform.
For an unresolved gap, request evidence and record an owner and review date. Assess the consequences and alternatives before changing a platform recommendation; uncertainty alone does not justify moving clients.
Take the Next Step
For support reviewing the firm's own AI use and supplier evidence, discuss an AI Risk & Efficiency Audit. Agree the priority areas, evidence available and review scope before commissioning work; it does not certify a platform's compliance.
Book a Discovery Call → or learn more about the AI Audit.
Need help assessing an AI workflow and its unresolved risks?
Map the provider's confirmed AI uses and the decisions they affect. Check which Consumer Duty, SM&CR and other requirements apply to the firm and service, alongside client-data and recovery arrangements; the mapping itself is not compliance evidence.
