🤖AI Summary
Researchers have released Tide, an open-source synthetic dataset generator for Anti-Money Laundering (AML) research that creates graph-based financial networks with both structural and temporal money laundering patterns. The tool addresses the lack of accessible transactional data for machine learning research due to privacy constraints, and includes two reference datasets with different illicit ratios for benchmarking detection models.
Key Takeaways
- →Tide is an open-source tool that generates synthetic financial transaction datasets for AML research, addressing privacy concerns with real financial data.
- →The generator incorporates both structural and temporal characteristics of money laundering schemes, unlike existing tools that focus only on simple patterns.
- →Two reference datasets were released with different illicit ratios (0.10% and 0.19%) for benchmarking purposes.
- →Testing revealed that LightGBM performed best on low illicit ratio datasets while XGBoost excelled with higher fraud prevalence.
- →The tool enables reproducible and customizable dataset generation tailored to specific research requirements.
#aml#anti-money-laundering#machine-learning#synthetic-data#financial-crime#dataset-generator#open-source#research-tools#fraud-detection
Read Original →via arXiv – CS AI
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