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Rajib Kumar Dhali v Maybank Singapore Limited

Court
Magistrate's Court
Jurisdiction
Singapore
Decided
2025-10-14
AI tool
Implied
Outcome
Misconduct taken into account for adverse costs order
Monetary penalty
18947 SGD

What was hallucinated

Fabricated: Case Law | Claimant cited multiple case precedents that were fictitious or did not support the propositions cited; court found these to be AI-generated and erroneous. || Fabricated: Legal Norm | Claimant cited statutory provisions that were fictitious or wrongly attributed, described by the court as generated by artificial intelligence.

Sanction teardown · Magistrate's Court, Singapore · 2025-10-14

Rajib Kumar Dhali v Maybank Singapore Limited

What happened

In Magistrate's Court, Singapore, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:

  • Fabricated (Case Law)
    Claimant cited multiple case precedents that were fictitious or did not support the propositions cited; court found these to be AI-generated and erroneous.
  • Fabricated (Legal Norm)
    Claimant cited statutory provisions that were fictitious or wrongly attributed, described by the court as generated by artificial intelligence.

Which AI tool

an unnamed/unconfirmed AI tool. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.

Outcome

Misconduct taken into account for adverse costs order (monetary penalty: 18947 SGD.)

How Citation Safe would have caught this

Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.

Check a brief before you file it → · See our live false-verify rate

Source: https://www.damiencharlotin.com/documents/2466/Rajib_Kumar_Dhali_2025_SGMC_62.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

Source: https://www.damiencharlotin.com/documents/2466/Rajib_Kumar_Dhali_2025_SGMC_62.pdf

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