User Disclosure

Explanation

User disclosure checks whether people interacting with the system are actually told they are dealing with AI and acknowledge it, rather than silently being subjected to automated decisions or advice. It matters because customers receiving AI-powered financial advice have a right to know a machine is involved so they can weigh that, and undisclosed AI use erodes trust and can breach conduct rules. It is measured as Awareness Rate = (Users_Acknowledging_AI_Use / Total_Users_Exposed_To_AI) × 100%, applied to AI-powered financial advice - in other words, of everyone who encounters the AI feature, what share explicitly acknowledged it. To implement it, surface a clear disclosure at the point of AI interaction (a banner, consent step, or interstitial), capture each user's acknowledgement event with a timestamp and the disclosure version shown, and compute the ratio of acknowledgements to total exposed users; log these events as auditable evidence of consent. Wire the metric into a dashboard segmented by channel and product. The threshold is a 100% acknowledgment rate, meaning no user should be exposed to the AI without acknowledging it; any exposure without acknowledgement is a breach that should trigger review of the disclosure flow - for instance gating the AI feature until the acknowledgement is recorded. Aligns with RBI Understandable by Design, NIST MEASURE 3.1 and 4.1, and ISO Clauses 6.2.2 and 9.1.