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Finding Suspicious Activities in Financial Transactions and Distributed Ledgers
Camino, Ramiro Daniel; State, Radu; Montero, Leandro et al.
2017In Proceedings of the 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017)
Peer reviewed
 

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Abstract :
[en] Banks and financial institutions around the world must comply with several policies for the prevention of money laundering and in order to combat the financing of terrorism. Nowadays, there is a raise in the popularity of novel financial technologies such as digital currencies, social trading platforms and distributed ledger payments, but there is a lack of approaches to enforce the aforementioned regulations accordingly. Software tools are developed to detect suspicious transactions usually based on knowledge from experts in the domain, but as new criminal tactics emerge, detection mechanisms must be updated. Suspicious activity examples are scarce or nonexistent, hindering the use of supervised machine learning methods. In this paper, we describe a methodology for analyzing financial information without the use of ground truth. A user suspicion ranking is generated in order to facilitate human expert validation using an ensemble of anomaly detection algorithms. We apply our procedure over two case studies: one related to bank fund movements from a private company and the other concerning Ripple network transactions. We illustrate how both examples share interesting similarities and that the resulting user ranking leads to suspicious findings, showing that anomaly detection is a must in both traditional and modern payment systems.
Disciplines :
Computer science
Author, co-author :
Camino, Ramiro Daniel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
State, Radu  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Montero, Leandro ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Valtchev, Petko ;  Université du Québec
External co-authors :
yes
Language :
English
Title :
Finding Suspicious Activities in Financial Transactions and Distributed Ledgers
Publication date :
2017
Event name :
17th IEEE International Conference on Data Mining Workshops (ICDMW 2017)
Event organizer :
IEEE
Event place :
New Orleans, United States
Event date :
18-11-2017
Audience :
International
Main work title :
Proceedings of the 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017)
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 17 December 2017

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