CodeParticle tools
Answer 10 quick questions. Get a score and the one layer, from PCI scope to reconciliation, most likely to stall your fintech AI before it ships.
Free, takes about two minutes. Built by senior engineers who ship AI into regulated production systems.
1. Do you start AI features for money-touching flows from a written specification of expected behavior and business rules?
2. Do you capture edge cases and failure conditions before a model or agent implements the feature?
3. Is what the AI can retrieve constrained by the requester's permissions at the data/access layer, not just the application interface?
4. Can you identify and audit which sensitive data, such as cardholder data or PII, the AI accessed?
5. Can an AI-generated output be traced back to the source records or data that supported it?
6. Can you identify the model/version, context, and process that produced an AI-generated output?
7. Are money movement, limit, or eligibility actions gated outside the model so the AI cannot execute them autonomously?
8. Is human or deterministic review, including reconciliation, proportional to the consequence of getting the output wrong?
9. Has the AI feature been tested under realistic production conditions, such as real transaction volume and adversarial conditions, not just a demo?
10. Do you understand and control its cost and behavior at production scale?
Answer all 10 to see your score.
