Survey Reveals Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows

Jul 16, 2026

A new survey of 49 operationally relevant sources finds that research on LLMs for fraud detection often lacks public reporting on key operational metrics such as latency, cost, and calibration, while content moderation studies more frequently address these constraints. The authors introduce the FORTE framework to categorize LLM roles in these workflows and propose a minimum deployment-evidence checklist to guide future research. The study highlights the need for more comprehensive evidence before deploying LLMs in live fraud and trust-and-safety systems.

Why it matters: This work underscores that current public evidence is insufficient to justify deploying LLMs in critical fraud detection and trust-and-safety pipelines, impacting deployment and risk management decisions.

Full story at: arXiv Cryptography and Security ↗