Anomaly Detection in Graphs of Bank Transactions for Anti Money Laundering Applications
Author:
Affiliation:
1. Department of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania
2. Tremend Software Consulting, Bucharest, Romania
Funder
Grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI-UEFISCDI, through the PNCDI III
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762926.pdf?arnumber=9762926
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3. Fraud detection: A systematic literature review of graph-based anomaly detection approaches
4. Fraud Detection in Networks
5. Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review
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