Fraud analysis ยท Research seed
Fraud Conversation Analysis with RAG
A research-led case study on retrieval-augmented fraud conversation analysis designed to keep LLM outputs grounded in transcript evidence.
Problem
Fraud conversations contain intent, persuasion patterns, role shifts, and evidence cues that fluent summaries can flatten or overstate.
System response
Grounded retrieval surfaces relevant transcript segments before reasoning, so generated answers remain tied to recoverable dialogue evidence.
Evidence surface
- Transcript indexing
- Evidence-bearing dialogue retrieval
- Grounding and hallucination-control evaluation
Toolkit
Next validation layer
Add explicit retrieval-quality and evidence-support evaluation artifacts.