A Time-Frequency Based Suspicious Activity Detection for Anti-Money Laundering

Money laundering is the crucial mechanism utilized by criminals to inject proceeds of crime into the financial system. The primary responsibility of the detection of suspicious activity related to money laundering is with the financial institutions. Most of the current systems in these institutions...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.59957-59967
Hauptverfasser:	Ketenci, Utku Gorkem, Kurt, Tolga, Onal, Selim, Erbil, Cenk, Akturkoglu, Sinan, Ilhan, Hande Serban
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Anomaly detection anti-money laundering compliance Crime Customer relationship management Customer satisfaction Customer services Customers Data models Feature extraction Hidden Markov models Machine learning Money laundering Monitoring Monitoring systems random forest algorithm Simulated annealing Time-frequency analysis transaction monitoring Two dimensional analysis
Online-Zugang:	Volltext
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