Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows
LLMs are now proposed for fraud detection, scam investigation, content moderation, and other trust-and-safety workflows. Much of the public literature still evaluates them as models, with less attention to their behavior as components in operational pipelines. This creates a practical evidence question: what would justify placing an LLM inside a live workflow with latency, cost, escalation, human-review, and adversarial-risk constraints? We address this question through a fraud-first survey of deployment evidence. We code 49 operationally relevant sources on LLM use in fraud detection, investigation support, content moderation, and cross-cutting robustness (18 fraud, 14 moderation, 17 cro...
| Authors | Keyur Gabani |
|---|---|
| Primary category | cs.CR |
| Published | 12 July 2026 |
| Last updated at source | 12 July 2026 |
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