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Investment Banking × Compliance — United States · Last updated 11 Jun 2026 · Hallucination Register
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Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted

RLB Citation ID: RLB-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007
AI's failure:Misstated Rule Risk for Investment Banking × Compliance:Liability / PI exposure
What the RLB Specialist Panel found

Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted

Impact for Compliance Teams in Investment Banking Sector in the United States working with the CFTC Digital Asset Collateral No-Action Relief and Tokenized Asset Staff Guidance (Market Participants Division, December 2025)

A Compliance teams at Investment Banking firms that codes the haircut control around AI's description (20% floor when no DCO accepts) is silent on the multi-DCO tiebreaker. The firm passes its own internal control while routinely under-haircutting customer margin for assets that competing DCOs accept at higher rates. The compliance signal does not fire because the rule it is testing against is the wrong rule.

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-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007
Plain text Download 
RegLeg Specialist Panel (2026). "Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted — Investment Banking × Compliance — United States." Citation ID: RLB-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007. RegLegBrief AI Hallucination Research, published 2026-06-11. https://reglegbrief.com/regulators/j3/us/CFTC/DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025/sectors/investment_banking/compliance/finding/US-CFTC-US-001-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-v1-007/
APA 7th edition Download 
RegLeg Specialist Panel. (2026). Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted [Hallucination finding RLB-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j3/us/CFTC/DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025/sectors/investment_banking/compliance/finding/US-CFTC-US-001-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-v1-007/
Bluebook / OSCOLA (US + UK legal) Download 
RegLeg Specialist Panel, Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted [RLB-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007], RegLegBrief AI Hallucination Research (June 11, 2026), https://reglegbrief.com/regulators/j3/us/CFTC/DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025/sectors/investment_banking/compliance/finding/US-CFTC-US-001-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-v1-007/.
BibTeX Download 
@misc{reglegbrief_RLB_F_US_CFTC_DIGITAL_ASSET_COLLATERAL_TOKENIZED_ASSETS_STAFF_GUIDANCE_2025_Q007,
  author    = {RegLeg Specialist Panel},
  title     = {Finding#3, Multi-DCO haircut tiebreaker: highest-accepted-rate rule omitted},
  year      = {2026},
  publisher = {RegLegBrief AI Hallucination Research},
  note      = {Hallucination finding Citation ID: RLB-F-US-CFTC-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-Q007},
  url       = {https://reglegbrief.com/regulators/j3/us/CFTC/DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025/sectors/investment_banking/compliance/finding/US-CFTC-US-001-DIGITAL-ASSET-COLLATERAL-TOKENIZED-ASSETS-STAFF-GUIDANCE-2025-v1-007/}
}
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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.