AML pipeline for training an XGBoost model on financial data using graph features.
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Updated
Jul 6, 2026 - Python
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amlworld
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Alert-budget-aware evaluation methodology for AML transaction monitoring, on IBM's synthetic AMLworld benchmark. Account-day alert units, random-ranker nulls, attainable ceilings, and a publication gate that refuses any number no archived artifact supports.
benchmarking machine-learning provenance reproducibility anti-money-laundering evaluation-methodology amlworld alert-budget
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Updated
Sep 24, 2026 - Python
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