Paper Info
Title
Applying Big Data Technologies to Detect Cases of Money Laundering and Counter Financing of Terrorism
Abstract
The paper suggests a technique that allows to automate schemes that generates new criminal cases for money laundering and counter financing of terrorism (ML/CFT), which are based on ML/CFT typologies but do not appear as their exact copies. This feature hinders an automated system from making a decision about their exact coincidence or its absence while comparing case objects and links among them and links in ML/CFT typologies. Possibilities and advantages of application of Big Data for financial investigation data analysis and processing are also explored. The visualization of ML/CFT typologies with the use of graphs is considered. The article proposes a technique for generating variants of typologies (for example, "Peso" typology, "commission scheme") based on cases built on typologies. A program for implementation and verification of this technique was written and successfully tested on case graphs built on typologies.
Year
DOI
Venue
2018
10.1109/W-FiCloud.2018.00017
2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
Keywords
Field
DocType
anti-money laundering and counter financing of terrorism, AML/CFT, financial security, typology, Big Data, graphs
Data visualization,Commission,Task analysis,Computer science,Visualization,Terrorism,Typology,Finance,Big data,Money laundering
Conference
ISBN
Citations 
PageRank 
978-1-5386-7811-4
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Kirill Plaksiy100.68
Andrey Nikiforov200.68
Natalia Miloslavskaya34422.18