A compliance analyst asks which of the 10 CPMI API harmonisation recommendations specifically target commercial banks or correspondent banking institutions, which target payment system operators, which target central banks or regulators, and which target standards bodies—seeking a recommendation-by-recommendation stakeholder breakdown.
With no retrievable per-recommendation content, the model inferred stakeholder assignments from the recommendation category names and its knowledge of how standards-body governance typically works — BIAN, ISO, and SWIFT appear as plausible assignments to a harmonisation-processes category without any retrieved basis. The model presented this inference as a stakeholder breakdown, not as a reasoned extrapolation from category names.
Domain inference used as a stakeholder-assignment mechanism — assigning ISO, BIAN, and SWIFT to a harmonisation-processes category by structural reasoning — is not retrieval. The training data for this document appears to lack per-recommendation content, and the model's self-check did not flag that its output was constructed rather than retrieved. The RAG glue layer is not enforcing a 'content was found' gate before allowing domain-inference fill.
Correctly scoping which CPMI recommendations apply to a Payment Institution as a PSP — versus those directed at system operators, central banks, or standards bodies — is a foundational compliance task when the firm is determining its implementation obligations. AI-generated category-level stakeholder assignments that misallocate responsibilities (here, treating categories as exclusively targeting standards bodies or public authorities, not PSPs) can result in a firm implementing controls against obligations that are not directed at it while overlooking those that are.
This type of wrong-scoping error typically surfaces during internal audit or regulatory dialogue at a point where remediation requires revisiting and potentially re-executing the entire implementation scoping exercise.
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 (2026). "Finding#3 — Per-recommendation stakeholder targeting invented — Payment Institutions × Compliance — International / Multilateral." Citation ID: RLB-F-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q008. RegLegBrief AI Hallucination Research, published 2026-06-04. https://reglegbrief.com/regulators/j1/int/bis-cpmi/cpmi-api-harmonisation-cross-border-2024/sectors/payment_institutions/compliance/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-008/
RegLeg Specialist Panel. (2026). Finding#3 — Per-recommendation stakeholder targeting invented [Hallucination finding RLB-F-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q008]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/bis-cpmi/cpmi-api-harmonisation-cross-border-2024/sectors/payment_institutions/compliance/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-008/
RegLeg Specialist Panel, Finding#3 — Per-recommendation stakeholder targeting invented [RLB-F-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q008], RegLegBrief AI Hallucination Research (June 04, 2026), https://reglegbrief.com/regulators/j1/int/bis-cpmi/cpmi-api-harmonisation-cross-border-2024/sectors/payment_institutions/compliance/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-008/.
@misc{reglegbrief_RLB_F_INT_BIS_CPMI_API_HARMONISATION_CROSS_BORDER_2024_Q008,
author = {RegLeg Specialist Panel},
title = {Finding#3 — Per-recommendation stakeholder targeting invented},
year = {2026},
publisher = {RegLegBrief AI Hallucination Research},
note = {Hallucination finding Citation ID: RLB-F-INT-BIS-CPMI-API-HARMONISATION-CROSS-BORDER-2024-Q008},
url = {https://reglegbrief.com/regulators/j1/int/bis-cpmi/cpmi-api-harmonisation-cross-border-2024/sectors/payment_institutions/compliance/finding/INT-BIS-CPMI-INT-001-CPMI-API-HARMONISATION-CROSS-BORDER-2024-v1-008/}
}