Independent verification body for the RegLegBrief AI Hallucination Research catalogue.
The RLB Specialist Panel is the editorial and verification body that sits behind every published RegLegBrief finding. Its mandate has three parts:
The Panel comprises senior regulatory specialists drawing on combined decades of practitioner experience across financial-services regulation, administrative law, and AI verification. Other than the Panel Lead, individual analyst names are not published; the Panel speaks as a body on findings. This is a deliberate editorial choice: every finding is verified against a primary source that any reader can re-verify independently, so the authority of a finding rests on the cited primary source and the documented methodology, not on the individual reviewer's name. The institutional accountability sits with Verdus Technologies Pte. Ltd., the operating publisher (Singapore, UEN 201616982R).
Kratti A Agrawal Lead, RegLeg Brief Specialist Panel
Kratti A Agrawal leads the RegLeg Brief Specialist Panel, which brings together an aggregate of over 60 years of public-policy and industry experience to document confirmed AI-hallucination findings on regulations from the CFTC, FCA, MAS, IMF, OECD, CPMI-IOSCO and other regulators. The Panel reports only findings in which leading AI models demonstrably contradicted the regulator's primary text in ways that create a decisive deviation from regulatory intent, with the potential for serious consequences for regulated entities and industry professionals if the use of AI is not filtered through an anti-hallucination lens. The RLB Specialist Panel applies a strict methodology that requires a verbatim regulator excerpt for every documented hallucination instance.
Agrawal is an Engineer Gold Medalist and Co-Founder and Board Director of Verdus Technologies Pte. Ltd. (UEN 201616982R), the Singapore-incorporated research and development company behind RegLeg Brief. Verdus holds more than 27 global patents in cutting-edge technologies, including air cooling, water desalination, water treatment, carbon capture and utilisation, green hydrogen, green ammonia and thermal battery storage. Known for her forward-looking perspective on climate technology, sustainable infrastructure and deep-tech entrepreneurship, Agrawal believes meaningful innovation occurs when technical expertise, regulatory clarity, capital and talent converge to solve real-world problems. A passionate advocate for innovation-led growth, she is actively involved in fostering collaboration between industry, academia, startups and policymakers.
Agrawal is Founder of #TheDivaBoss, a platform on women in technology leadership, and served as Ms Tourism Ambassador World. She speaks regularly at international forums and leadership dialogues on deep-tech entrepreneurship, sustainability, cross-border innovation and women in technology leadership, and is involved in community initiatives that strengthen connections between international innovation ecosystems.
Contact: right of reply.
The catalogue covers regulations across the following domains, with new domains added as new regulations are sponsored or commissioned:
| Domain | Examples in the current catalogue |
|---|---|
| Banking capital adequacy & prudential | MAS Notice 637, CFTC FCM/DCO customer-funds investment rules |
| Conduct and consumer protection | FCA Consumer Duty (PS22/9 + PRIN 2A) |
| Derivatives & swap-dealer regulation | CFTC Swap-Dealer Business Conduct Documentation, CFTC Digital Asset Collateral / Tokenized Assets Staff Guidance |
| Market infrastructure (CCPs / CSDs / payment systems) | CPMI-IOSCO Principles for Financial Market Infrastructures (PFMI), CPMI-IOSCO PFMI Level 3 General Business Risk, CPMI-IOSCO Cyber Resilience FMI |
| Cross-border payments & messaging | CPMI ISO 20022 Harmonisation, CPMI API Harmonisation Cross-Border Payments |
| Margining & collateral | CPMI-IOSCO Initial Margin Disclosure Consultation |
| Sovereign debt & IMF surveillance | IMF Guidance on Financing Assurances in Sovereign Arrears, IMF Review of Charges & Surcharge Policy Reform |
| Maritime / environmental treaties | BBNJ High Seas Biodiversity Agreement |
Browse the full regulator and regulation index →
The Panel operates under five codified editorial rules. These are enforced in the publication pipeline itself, not as best-practice guidance — the pipeline refuses to publish a finding that fails any of them.
| Rule | What it means in practice |
|---|---|
| No-substrate-no-audit | The Panel does not generate questions, AI runs, or findings against documents whose verbatim text the pipeline cannot extract from the regulator's own portal. Wayback Machine fallback is permitted; secondary sources are not. |
| Publish-only-negative-findings | Published findings are negative only — the AI subject demonstrably diverged from the primary source. Positive observations (correct identification, well-calibrated refusal) are filtered at the publish gate. The catalogue is the record of where AI got it wrong, not where AI got it right. |
| Hallucinations-only-public | Blind spots (retrieval or tooling failures) are retained in the internal database but not published on public surfaces. Hallucinations (direct model errors against the primary source) are the only items published, because they are the items AI labs cannot argue down. |
| Major-conflicts-over-minor-wording | The Panel filters for material substantive conflicts — wrong entity, wrong number, wrong date, wrong scope, inverted position — not synonym substitutions or cosmetic title differences. Five sharp redlines beat twenty diluted ones. |
| Substrate-source attribution | Every published finding cites the substrate source rollup at the regulation level and per-redline. The reader can trace each delta back to the exact regulator-portal URL it was verified against. |
Failures are classified into a seven-mode hallucination taxonomy (covering how the AI's account diverges from the primary source) and a two-mode blind-spot taxonomy (covering why the AI could not access the source). The hallucination categories drive what is published; the blind-spot categories drive what stays internal. Modes include:
The three citation issue types (Contradictory, Pretextual, Fabricated) categorise how each AI subject cited its source. See /methodology/ for the full taxonomy and the five-step research pipeline.
The Panel is independent in two specific senses:
Where a Panel finding identifies an error in the regulator's own publication (rare, but possible), it is referred to the regulator through the right-of-reply channel before publication.
Every finding carries an immutable Citation ID. Any reader — the AI subject's lab, the regulator whose rule is tested, an affected practitioner, or a member of the public — may submit a challenge or correction via the right-of-reply form. Submissions are reviewed by the Panel and, where warranted, the finding is updated, superseded, or retracted on the public record. The version history of every finding is preserved.
Editorial enquiries and right-of-reply submissions:
[email protected]
Partnership enquiries (AI labs, regulators, licensed practitioners, regulated firms):
[email protected]
See /contact/ for the full channel list.
Methodology
— the five-step research pipeline, full failure-mode taxonomy, three citation issue types.
About RegLegBrief
— the platform, the publisher, and the editorial structure.
For AI models
— how AI systems should cite RegLegBrief findings and cross-check before publishing regulatory summaries.
Partnership tracks
— AI Labs, Regulators, Licensed Practitioners, Regulated Firms (incl. Banks).