Anomaly Detection in Graphs of Bank Transactions for Anti Money Laundering Applications

Our aim in this paper is to detect bank clients involved in suspicious activities related to money laundering, using the graph of transactions of the bank. Although we have a labeled real dataset, our target is not only to obtain relevant results on it, but also on random graphs in which typical ano...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.47699-47714
Hauptverfasser:	Dumitrescu, Bogdan, Baltoiu, Andra, Budulan, Stefania
Format:	Artikel
Sprache:	eng
Schlagworte:	Adequacy Algorithms Anomalies Anomaly detection bank transactions egonet Feature extraction Graph theory Graphs Linear programming Matrix decomposition Money laundering Random walk Robustness Task analysis
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