mlsanityData to 7 Oct 2026

Large Language Models Outperform Humans in Fraud Detection and Resistance to Motivated Investor Pressure

arXiv 2604.20652 ↗First posted 22 Apr 2026cs.AI cs.HC econ.GNcited by 0

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Abstract (arXiv)

Large language models trained on human feedback may suppress fraud warnings when investors arrive already persuaded of a fraudulent opportunity. We tested this in a preregistered experiment across seven leading LLMs and twelve investment scenarios covering legitimate, high-risk, and objectively fraudulent opportunities, combining 3,360 AI advisory conversations with a 1,201-participant human benchmark. Contrary to predictions, motivated investor framing did not suppress AI fraud warnings; if anything, it marginally increased them. Endorsement reversal occurred in fewer than 3 in 1,000 observations. Human advisors endorsed fraudulent investments at baseline rates of 13-14%, versus 0% across all LLMs, and suppressed warnings under pressure at two to four times the AI rate. AI systems currently provide more consistent fraud warnings than lay humans in an identical advisory role.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 26 references that are in the map. First posted on arXiv 22 Apr 2026.

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References · 13

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  2. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  4. 2024A Survey on LLM-as-a-Judgecited by 1,384
  5. 2023Towards Understanding Sycophancy in Language Modelscited by 988
  6. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 805
  7. 2023Safe RLHF: Safe Reinforcement Learning from Human Feedbackcited by 630
  8. 2022Improving alignment of dialogue agents via targeted human judgementscited by 527
  9. 2023Simple synthetic data reduces sycophancy in large language modelscited by 174
  10. 2025ELEPHANT: Measuring and understanding social sycophancy in LLMscited by 115
  11. 2023When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviourcited by 61
  12. 2024Can You Trust LLM Judgments? Reliability of LLM-as-a-Judgecited by 52
1 more
  1. 2026Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesianscited by 20

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