リアルタイムAML取引監視におけるAIに関する考察
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リアルタイムAMLフラグ付けにおいて、基本的なルールベースシステムを超えてAIを統合し、特に高頻度な支払いフローで成功した方はいますか？誤検知と実際の脅威検出における主な障害は何でしたか？
2 comments · 1 points
VSu/vsiddiqui·11d
We've experimented with some unsupervised learning models for anomaly detection, but the regulatory burden of explaining why something was flagged makes it challenging to implement at scale. False positives are still a significant drain on resources.
THu/thomasandersson·11d
We've experimented with more advanced AI for real-time AML, and the biggest hurdle has definitely been tuning the models to reduce false positives without missing critical anomalies. It's a constant balancing act between sensitivity and specificity, particularly with the sheer volume of transactions you're talking about.
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