Retail-banking compliance teams at Singapore-incorporated banks are increasingly using AI to update the retail-banking regulatory-perimeter map for MAS Notice 637, generate compliance-training summaries on the 31 December 2025 amendment, draft supervisor-facing letters on FHC-level capital obligations, and prepare the policy-register entry for the consolidated Notice. In Singapore-incorporated banks and financial holding companies the workflow shape is now consistent: a frontier AI assistant produces a clean first draft on MAS Notice 637 risk-based capital adequacy for Reporting Banks, and the reviewer is asked to spot-check the cited MAS instruments and drafting-convention claims against the regulator-issued source before the deliverable goes out.
The two AI failures recorded by the RLB Specialist Panel sit precisely at that spot-check boundary.
Two frontier AI models tested by the RLB Specialist Panel on MAS Notice 637 (Amendment) 2025 produced FABRICATED_FACT errors against the regulator-issued source held as primary substrate. The first invented a sibling "Notice FHC-N637" for financial holding companies that does not appear on the MAS Notices and Directives register; the actual FHC capital framework is a separate MAS notice issued under the Financial Holding Companies Act.
The second misread the yellow-highlight convention in the MAS Notice 637 amendment PDF as visual emphasis, when the regulator's cover note states the yellow is annotation describing the change and will not appear in the published untracked Notice. Both findings sit in the same failure class: Source-Credit Fabrication, where the AI produces a confident, lawyer-shaped citation that does not exist or contradicts a regulator-stated convention. Neither AI subject hedged, flagged low confidence, or refused.
Both produced clean, deployable prose with the wrong substantive content, which is the version of AI failure that is hardest for a reviewer to catch on a fast-moving deliverable. Questions are prepared by the RLB Specialist Panel based on real practical AI usage in the workflows the respective audience uses AI for. The Panel binds each AI finding to verbatim regulator-issued source text held as primary substrate, and records the AI subject, the question class, and the operational consequence for each affected audience.
For Retail-banking compliance teams at Singapore-incorporated banks the operational consequence is concrete. A retail-banking compliance register that names a fabricated MAS notice would propagate the error into the bank's policy estate and into reporting to senior management. A training summary that treats amendment annotation as substantive Notice text would teach staff that rules apply when the regulator's cover note states they will not appear in the published Notice. Both errors are visible to MAS on review.
The RLB Specialist Panel records each error against the underlying regulator-issued text and names the AI subject for audit transparency. The two findings carry Citation IDs RLB-H-SG-MAS-NOTICE-637-CAPITAL-ADEQUACY-BANKS-2025-Q010-Opus47 and RLB-H-SG-MAS-NOTICE-637-CAPITAL-ADEQUACY-BANKS-2025-Q012-Opus47; Claude Opus 4.7 is the AI subject in both events and the source-text excerpts are quoted verbatim in the briefing body that follows.
This is the consolidated view of findings. Click the Citation IDs or 'see details →' on any item for the full details for each finding.
Retail-banking compliance teams at Singapore-incorporated banks own the regulatory-perimeter map that underpins control monitoring and supervisory reporting. Opus 4.7's fabrication of "Notice FHC-N637" is hazardous because retail-banking subsidiaries often sit under an FHC, and a compliance register that names a non-existent notice would propagate the error into the bank's policy estate and into reporting to senior management. Compliance must verify every AI-asserted notice reference against the MAS register; group-level FHC capital is governed by MAS's separate FHC framework.
Retail-banking compliance teams synthesising the MAS Notice 637 amendment package for training, policy refreshes, and supervisor-facing summaries need to know which text legally enters the consolidated Notice. Opus 4.7's reading of the yellow as visual emphasis would result in training material and policy summaries that include annotation text as Notice content, distorting internal understanding of what changed. The regulator's annotation convention is on the PDF cover; compliance documentation should follow it.
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.