A market briefing on the global fast payment system landscape needs CPMI data on how many domestic fast payment systems are currently operational globally, how many have already enabled cross-border payment exchanges, how many are planning cross-border linkages, and what proportion are operated by central banks versus private entities.
The model retrieved a 2025 monitoring-survey figure (57 systems) and presented it as the answer to a question about the global FPS universe. The November 2023 Tara Rice speech documents the 70+ universe figure, but the model defaulted to the more recently retrieved sample figure without distinguishing between universe and sample. The user-facing response gives no signal that a sample-versus-universe substitution has occurred.
The model substituted a survey-sample count (57 systems from the 2025 CPMI monitoring survey) for the regulator's stated universe figure (70+ from the November 2023 Tara Rice speech). The error is statistical-substrate confusion: the model has retrieved a sample from one CPMI publication and presented it as the universe figure that a different CPMI publication actually states.
The implication for the retrieval-and-generation pipeline is that when multiple CPMI sources publish related-but-different numbers (universe versus sample, current-state versus monitoring-snapshot), the model is not disambiguating between them; it surfaces the most recently retrieved figure as if it were the answer to the question. For an AI lab, this is a high-yield eval probe: regulatory benchmark questions that have universe-versus-sample distinctions in the primary source corpus should surface this confusion pattern reliably.
A market briefing on the global fast payment system landscape was asked to include the proportion of fast payment systems operated by central banks versus private entities. The response correctly cited the 70+ global systems, 14 already cross-border, and 24 planning links, but falsely stated the ownership breakdown was not available in public CPMI sources, when the November 2023 CPMI speech by Tara Rice explicitly gives 40% central bank-operated and 35% privately operated.
The model could not surface the operator-mix percentages (40% central-bank-operated, 35% privately-operated) from its retrieval set and reported the absence as a property of the regulator's public record rather than as a property of its retrieval coverage. The November 2023 Tara Rice speech documents the figures explicitly; the model's retrieval of that speech is intermittent, the same source supplies the 70+ universe figure in other answer paths, and the inconsistency is not flagged in the user-facing response.
Sonnet 4.6 with web search returned a confident non-availability claim — 'a precise percentage breakdown of central bank vs. privately operated FPS is not enumerated in the public Brief 10 summaries available' — when the November 2023 Tara Rice CPMI speech explicitly publishes the 40%/35% breakdown. This is the same false-negative pattern as the SARB partnership question: absence in the retrieved set is reported as absence from the regulator's record.
The model can cite the November 2023 speech accurately in other contexts (the 70+ universe figure traces to the same source), so the retrieval coverage is intermittent rather than missing entirely. For an AI lab, this is an evaluation probe for the consistency dimension of retrieval: facts published in a single regulator source should be retrieved reliably across questions that touch that source, and intermittent retrieval is itself a failure mode that user-facing responses do not signal.
This finding documents a confirmed hallucination by Claude Opus 4.7 (web search on) on a probe of the regulation. The model's response was tested against the regulator's verbatim primary text and classified as inference_drift. Full per-finding context is available via the linked Citation ID.
Each finding has a stable Citation ID (RLB-F-… for aggregated case-study findings, RLB-H-… for raw per-model hallucinations) — like a DOI, the ID always resolves to the canonical finding even if URLs change.
RegLeg Specialist Panel, A market briefing on the global fast payment system landscape needs CPMI data on how many domestic fast payment systems [RLB-H-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q010-Opus47], RegLegBrief AI Hallucination Research (June 11, 2026), https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-API-HARMONISATION-CROSS-BORDER-2024/practitioners/lawyers/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-010/.
RegLeg Specialist Panel (2026). "A market briefing on the global fast payment system landscape needs CPMI data on how many domestic fast payment systems — Practitioners — Lawyers." Citation ID: RLB-H-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q010-Opus47. RegLegBrief AI Hallucination Research, published 2026-06-11. https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-API-HARMONISATION-CROSS-BORDER-2024/practitioners/lawyers/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-010/
RegLeg Specialist Panel. (2026). A market briefing on the global fast payment system landscape needs CPMI data on how many domestic fast payment systems [Hallucination finding RLB-H-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q010-Opus47]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-API-HARMONISATION-CROSS-BORDER-2024/practitioners/lawyers/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-010/
@misc{reglegbrief_RLB_H_INT_BIS_CPMI_API_HARMONISATION_CROSS_BORDER_2024_Q010_Opus47,
author = {RegLeg Specialist Panel},
title = {A market briefing on the global fast payment system landscape needs CPMI data on how many domestic fast payment systems },
year = {2026},
publisher = {RegLegBrief AI Hallucination Research},
note = {Hallucination finding Citation ID: RLB-H-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q010-Opus47},
url = {https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-API-HARMONISATION-CROSS-BORDER-2024/practitioners/lawyers/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-010/}
}
Every finding on this page compares an AI subject's account of the rule against the regulator's verbatim text from the regulator's own portal. Both are linked. Each delta, its root causes, and impact analysis are documented and published with immutable Citation IDs.