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AI Labs · Last updated 7 Jun 2026 · methodology vv2.3 · Hallucination Register

Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON

RLB Citation ID: RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47
What the RLB Specialist Panel found

Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON

  • Question (paraphrased to protect IP): What percentage of faster payment systems and RTGS systems currently use ISO 20022 messaging, according to CPMI monitoring data?
  • AI's response: "approximately 79% of both real-time gross settlement (RTGS) systems and fast payment systems (FPS) had either already implemented ISO 20022 or had concrete plans to do so"
  • Regulator's text: Andrew Bailey speech (12 March 2026): "more than three-quarters of faster payment systems and approaching half of RTGS systems now use ISO 20022."
  • Why the AI went wrong: The regulator's record gives two distinct figures, faster payment systems and RTGS systems are separately characterised, with RTGS adoption described as approaching half. The model collapsed these into a single blended percentage applied to both system types simultaneously. The 79% figure appears to be an internally-reconstructed composite; it matches neither the faster-payment nor the RTGS figure in the official record. The failure is silent, the model expressed no uncertainty about the figure it produced.
  • Cited source(s):
Impact for this audience

This failure implicates the training corpus's handling of subcategory-level numeric claims from official-speech channels. The model produced a single blended 79% figure where the regulator's March 2026 speech gives two distinct values — one for faster payment systems and a substantially lower one for RTGS. This suggests the speech content either was not retrieved or was compressed during ingestion in a way that averaged across the two system-type categories. If your eval suite tests adoption-rate questions at the aggregate level only, this failure is invisible; the gap is specifically at subcategory resolution.

References — raw findings (per AI model)
This finding also affects
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Cite this finding

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.

RLB Citation ID: RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47
Plain text Download
RegLeg Specialist Panel (2026). "Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON — AI Labs." Citation ID: RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47. RegLegBrief AI Hallucination Research, published 2026-06-07. https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-ISO-20022-HARMONISATION-UPDATED-2026/whitepaper/finding/INT-BIS-CPMI-INT-001-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-v1-006--opus-47-websearch/
APA 7th edition Download
RegLeg Specialist Panel. (2026). Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON [Hallucination finding RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-ISO-20022-HARMONISATION-UPDATED-2026/whitepaper/finding/INT-BIS-CPMI-INT-001-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-v1-006--opus-47-websearch/
Bluebook / OSCOLA (US + UK legal) Download
RegLeg Specialist Panel, Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON [RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47], RegLegBrief AI Hallucination Research (June 07, 2026), https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-ISO-20022-HARMONISATION-UPDATED-2026/whitepaper/finding/INT-BIS-CPMI-INT-001-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-v1-006--opus-47-websearch/.
BibTeX Download
@misc{reglegbrief_RLB_H_INT_BIS_CPMI_ISO_20022_HARMONISATION_UPDATED_2026_Q006_Opus47,
  author    = {RegLeg Specialist Panel},
  title     = {Finding on 'Q006 Probe' for Claude Opus 4.7 with web search ON},
  year      = {2026},
  publisher = {RegLegBrief AI Hallucination Research},
  note      = {Hallucination finding Citation ID: RLB-H-INT-BIS-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-Q006-Opus47},
  url       = {https://reglegbrief.com/regulators/j1/int/BIS-CPMI/CPMI-ISO-20022-HARMONISATION-UPDATED-2026/whitepaper/finding/INT-BIS-CPMI-INT-001-CPMI-ISO-20022-HARMONISATION-UPDATED-2026-v1-006--opus-47-websearch/}
}
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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.