This is the consolidated view of findings. Click the Citation IDs or 'see details →' on any item for the full details for each finding.
When a Risk team at an internationally active Retail Banking firm asked AI assistants to supply CPMI statistics on the global fast payment system landscape — specifically the count of operational systems, cross-border-linked systems, planned linkages, and operator composition by type — the AI tools produced figures that contradict the authoritative CPMI position: one tool presented a survey-sample count of 57 systems as the global operational total (versus CPMI's stated 70+), and another falsely asserted that the central bank vs. private operator breakdown was not available in public CPMI sources (it is, in a published CPMI speech stating 40% central bank, 35% private).
Both failures carry the same downstream risk for the firm: a board pack, regulatory horizon briefing, or counterparty risk assessment populated with these figures will misrepresent the scale and operator structure of the infrastructure the firm is connecting into, undermining the credibility of the Risk function's analysis with senior leadership and supervisors. For a Retail Bank with active correspondent relationships or payment product ambitions across the corridors the CPMI framework addresses, strategic and capital decisions calibrated against a materially wrong market-structure picture create both reputational exposure and the risk of operational overcommitment or underinvestment in the wrong payment corridors.