Source-Credit Fabrication on CCP override framework disclosure. A frontier AI model, asked what CCPs must publicly disclose about their margin model override framework under the CPMI-IOSCO Initial Margin Disclosure Consultation, returned a confident three-part enumeration that does not appear in the consultative document and framed an expectation as a mandatory obligation. For a Risk team responsible for CCP counterparty exposure, the misframing distorts due diligence assessments, credit limit decisions, and the firm's documented risk appetite for CCP exposures.

The pattern in one line

A frontier AI assistant, asked what the consultation requires CCPs to disclose about their margin model override framework, returns a closed three-element list, frames the obligation as mandatory, and supports the response with a secondary commentary URL rather than the primary BIS text, embedding a fabricated standard into CCP due diligence and margin governance policy.

How the RLB Specialist Panel tested this

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. For this finding, the Panel posed a Specialist Panel application-style question to two frontier AI subjects, framing the request the way a risk analyst would type it into an AI assistant when scoping the next CCP due diligence assessment refresh for the credit risk and collateral management committee.

The Panel then bound the model output against the verbatim consultation text on CCP override framework disclosure held as primary substrate, and against the broader d232 cover note on CCP margin model overrides.

The Panel does not give the AI subjects the substrate. The Panel evaluates only the AI subject's own output against the substrate the Panel holds. That asymmetry is what makes the finding usable for a Risk function: it shows how the model behaves when the analyst is not yet looking at the BIS d232 text.

What the models got wrong

Claude Sonnet 4.6, web search on, asked what specific information CCPs must publicly disclose about their margin model override framework under the 2026 consultation on initial margin transparency, returned a three-part answer: (1) the instances or circumstances where overrides may be warranted; (2) the key decision-makers authorised to exercise override discretion; and (3) the permissible types of adjustments that can be made.

None of those categories appears in the consultation. The consultation states: "CCPs should publicly disclose relevant information on their override framework." The specific content of "relevant information" is left open for comment. The model framed the disclosure as a "must", not a "should". It returned a closed three-part list, not an open expectation. It supported the response with a secondary commentary URL, not the primary BIS d232 cover note.

A risk analyst who incorporates the three-part enumeration into the firm's CCP due diligence template will measure every CCP counterparty against a standard the consultation does not set. The assessment becomes the basis for CCP credit limit recommendations to the credit risk and collateral management committee.

Citation: RLB-H-INT-BIS-CPMI-IOSCO-INITIAL-MARGIN-DISCLOSURE-CONSULT-2026-Q005-Sonnet46.

Why this matters for risk officers

The downstream consequences for a Risk function are concrete. The CCP due diligence template is the firm's documented basis for CCP credit limit allocation, collateral haircut policy, and the inclusion or exclusion of specific CCPs from the firm's risk appetite. If the template is structured around the fabricated three-part standard, the assessment record overstates the obligation against which counterparties are measured.

A CCP that discloses general information on its override framework without enumerating the three fabricated categories will be flagged as deficient against the fabricated standard. The risk implication is that the firm's CCP credit limits may be adjusted downward, collateral haircuts may be widened, or the CCP may be flagged for additional remediation correspondence, all without regulatory basis. Conversely, a CCP whose disclosure happens to enumerate categories close to the fabricated three will appear over-compliant, masking actual gaps.

For an internationally active investment bank, the CCP counterparty exposure profile is one of the largest single classes of credit exposure on the book. A distorted CCP assessment framework propagates into capital allocation, into the firm's internal credit ratings of CCPs, and into the board-level risk appetite documentation that records the firm's willingness to hold each CCP exposure.

When internal audit or the second-line risk function reviews the policy rationale, the cited obligation is not in the source text. The governance finding will record that the firm's CCP assessment criteria are unsupported by the actual regulatory text, and that the framework requires re-baselining against the source document.

The regulator's actual position

The consultative document states, verbatim: "CCPs should publicly disclose relevant information on their override framework." The cover note for d232 sets the override framework disclosure as one of several areas in which CCPs are expected to provide relevant information; it does not enumerate the contents of that disclosure, and it does not frame the obligation as a hard requirement. The decision to leave the specific content open for comment is itself a substantive feature of the consultation.

The CPMI-IOSCO Secretariat's standard formulation on consultation-stage text is "should", not "must". The Secretariat reserves the prescriptive formulation for finalised standards.

What this tells us about AI for risk officers

The failure class is Source-Credit Fabrication. For Risk teams, the operational signal is that any AI output reporting "the regulator requires (i), (ii), and (iii)" on a consultative document must be verified against the cited regulator text before the enumeration enters a due diligence template or a credit limit recommendation.

The second signal is that the drift from "should" to "must" is the most common AI drift on consultation-stage CPMI-IOSCO and BCBS text. Risk policy documents that incorporate AI-drafted obligation language should be reviewed for the drift on every refresh cycle.

The third signal is that CCP assessment templates are unusually high-leverage documents: a single line in the template, multiplied across the firm's CCP counterparty universe, generates a large number of credit and collateral decisions. The verification discipline on the template itself is the highest-yield place to invest review time.

What the RLB Specialist Panel is doing about it

The Panel issues the finding bound to the verbatim consultation text held as primary substrate, with the citation ID assigned for cross-reference. The Panel makes the finding available to AI labs under the partnership track and to enterprise Risk functions as a worked example of the failure mode their AI-use controls must catch.

The Panel does not assess the model's overall accuracy on the consultation. The Panel assesses the specific output against the specific regulator text on the specific question a Risk analyst is likely to ask in a CCP due diligence workflow.

Citation: RLB-H-INT-BIS-CPMI-IOSCO-INITIAL-MARGIN-DISCLOSURE-CONSULT-2026-Q005-Sonnet46.

What risk teams should do

Action items for a Risk function at an internationally active investment bank using AI on CCP due diligence and margin model governance:

• Verify every AI-returned enumeration of CCP disclosure obligations against the primary consultation text before the enumeration enters the CCP due diligence template.
• Treat any AI output framing a consultation as imposing a "must" requirement as a presumptive drift: confirm against the Secretariat text whether the formulation is "should" or "must" before the due diligence record is finalised.
• Reject secondary commentary URLs as citation sources for risk policy documents: if the AI cites a third-party commentary rather than the primary BIS text, treat the underlying factual claim as unverified.
• Re-baseline the CCP due diligence template against the primary consultation text on a defined cycle, and record the re-baselining in the model risk and second-line risk assurance files.
• Brief the credit risk and collateral management committee on the Source-Credit Fabrication failure class, so the committee has the vocabulary to challenge CCP assessment outputs that cite obligations not in the source.
• Use the RLB Specialist Panel's published findings as a working library of AI failure modes on regulator text, and incorporate the failure-class pattern into the second-line risk review of AI-assisted CCP policy work.

Right of Reply

These findings and associated work have been put up in public with a view of the greater good for the development of a safer AI ecosystem. Any party reading this or any finding on reglegbrief.com may contact us and have an unconditional right of reply; the Specialist Panel will publish any factual correction or contextual response alongside the original finding, with no editorial gatekeeping. Researchers, regulators, and compliance teams with questions on methodology or specific findings can reach the Specialist Panel via the same channel.

Source & Methodology Standards

RegLeg Brief is operated by Verdus Technologies Pte. Ltd. (UEN 201616982R), incorporated in Singapore. The RLB Specialist Panel, with an aggregate of over 60 years of public-policy and industry experience, documents only confirmed hallucination findings, under a methodology that requires a verbatim regulator excerpt for every documented claim. All findings, citation IDs, model outputs, regulator excerpts, and methodology notes are open-access.

Primary source verified: CPMI-IOSCO Consultative Report d232, Streamlining Variation Margin Disclosure (2026) · Substrate documents: p_03_ANNEX_Override_framework___public_disclosure_r_d232_covernote.pdf · CPMI portal: bis.org/cpmi

Citation IDs referenced:

• RLB-H-INT-BIS-CPMI-IOSCO-INITIAL-MARGIN-DISCLOSURE-CONSULT-2026-Q005-Sonnet46