The Hot Path Belongs to GBDTs, Agents Own the Cold Path: A Payment-Fraud Benchmark
Towards Data Science
This article presents a benchmark comparing GBDTs and agents in payment-fraud detection, focusing on latency, cost, and reproducibility. It argues that GBDTs excel on the 'hot path' (real-time decisions), while agents are better suited for the 'cold path' (complex, slower analysis). The findings highlight where each approach provides the most value in fraud prevention.
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