The agent-oriented approach to the simulation of the processes of tracking the money laundering and the financing of terrorism
Reviews
Readers community rating
0.0 (0 votes)


Views
1366


Downloads
52
UDC
33 Экономика. Народное хозяйство. Экономические науки
308 Социология. Описательное изучение жизни общества
Date of publication
16.10.2018
Public year
2018
DOI
10.31857/S020736760000809-8
The agent-oriented approach to the simulation of the processes of tracking the money laundering and the financing of terrorism
Read   Download pdf
Annotation

The article provides an overview of some approaches to studying the problem of money laundering and the financing of terrorist organizations. The criterion for selecting the models for their further critical analysis is their belonging to a certain class of mathematical modeling tools (namely, agent-oriented, imitative, geoinformation models). 

About authors
Albert Bakhtizin
Director, CEMI RAS
Director of CEMI RAS. Head of laboratory of computer simulation of socio-economical processes, CEMI RAS
Valery Makarov
Scientific Director of the Central Economics and Mathematics Institute of the Russian Academy of Sciences
Central economic and mathematical Institute of the Russian Academy of Sciences
Maria Volkova
Central economic and mathematical Institute of the Russian Academy of Sciences
Elena Sushko
Leading Researcher
CEMI RAS
References

1. Financial Action Task Force. 2004. The 40 Recommendations. Retrieved June 20, 2011, from FATF: http://www.fatf.gafi.org/document/28/0,3343,en_32250379_32236930_33658140_1_1_1_1,00.html.

2. V.L. Makarov, A.R. Bakhtizin, E.D. Sushko, V.A. Vasenin, V.A. Borisov, V.A. Roganov. Agent-orientirovannye modeli: mirovoj opyt i tekhnicheskie vozmozhnosti rea- lizatsii na superkomp'yuterakh / Vestnik Rossijskoj akademii nauk. 2016. tom 86, №3. S. 252-262.

3. Valerij Makarov, Al'bert Bakhtizin, Elena Sushko. Modelirovanie demografiche- skikh protsessov s ispol'zovaniem agent-orientirovannogo podkhoda / Federa- lizm. 2014. №4. S. 37-46.

4. Wooldridge, M. (2002). An introduction to multiagent systems, Chichester, England, John Wiley & Sons. 2002.

5. Steve Kiser. Financing Terror // An Analysis and Simulation for Affecting Al Qaeda's Financial Infrastructure. 2004.

6. Charles Koech. A multi-agent based counter terrorism system through anti-money laundering // University of Nairobi. 2016.

7. Alexandre, Claudio and Balsa, Joao. “Client Profiling for an Anti-Money Laundering System”. arXiv:1510.00878v2 [cs.LG]. 2016.

8. Nhien-An Le-Khac, Sammer Markos and M-Tahar Kechadi. A Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank. International Science Index, Computer and Information Engineering Vol:3. No:12. 2009. R. 2742-2746.

9. Nhien-An Le-Khac, Sammer Markos and M-Tahar Kechadi. A Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank. International Science Index, Computer and Information Engineering Vol:3. No:12. 2009. R. 2742-2746.

10. Andrew J Park, Herbert H Tsang, Mengting Sun and Uwe Glasser. An agent-based model and computational framework for counter-terrorism and public safety based on swarm intelligence. Security Informatics. 2012. 1:23.

11. Gao, S. and Xu, D. (2006). Conceptual Modelling and Development of an Intelligent Agent-Assisted Decision Support System for Anti-Money Laundering. In: The 11th Annual Conference of Asia Pacific Decision Sciences Institute (APDSI 2006). Kowloon. Hong Kong. (241-244). 14-18 June. 2006.

12. Z. M. Zhang, J. J. Salerno, and P. S. Yu. “Applying data mining in investigating money laundering crimes,” in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ser. KDD ’03. New York, NY, USA: ACM, 2003. R. 747–752.

13. Aakash Negandhi, Soham Gawas, Prem Bhatt, Priya Porwal. Detect Online Spread of Terrorism Using Data Mining. IOSR Journal of Engineering (IOSRJEN). 2016. R. 17-19.

14. Matthew Koehler, Brian Tivnan, and Eric Bloedorn. Generating Fraud: Agent Based Financial Network Modeling (http://www.academia.edu/20634179/Generating_fraud_Agent_based_financial_network_ modeling.)

15. Hamed Tofangsaz "Rethinking terrorist financing; where does all this lead?", Journal of Money Laundering Control, 2015. Vol. 18 Issue: 1, R. 112-130, https://doi.org/10.1108/JMLC-12- 2013-0049.

16. Nhien-An Le Khac, Sammer Markos, Michael O'Neill, Anthony Brabazon and M-Tahar Kechadi. An efficient Search Tool for an Anti-Money Laundering Application of Multinational Bank's Dataset. https://arxiv.org/abs/1609.02031

17. D.A. Novikov et al 2018 J. Phys.: Conf. Ser. 973 012041. Mathematical model of information process of protection of the social sector. doi :10.1088/1742-6596/973/1/012041. 2018. R. 1-9.

18. S.Ya. Suschij, G.A. Ugol'nitskij, V.K. D'yachenko. Imitatsionnoe modelirovanie bor'by s ehkstremizmom na Severnom Kavkaze // Sotsiologiya: 4M. 2013. № 37. S. 126-150.

19. Teresa H. K., Berry N.M. Agent-Based Modeling with Social Networks for Terrorist Recruitment. Proceedings of the 19th national conference on Artificial intelligence. AAAI Press / The MIT Press, 2004.

20. Bulleit W.M., Drewek M.W. An Agent-Based Model of Terrorist Activity. North American Association for Computational Social and Organizational Science Conference 2005 Proceedings, 2005.

21. Epstein J.M. Modeling civil violence: An agent-based computational approach. PNAS, May 14, 2002, vol. 99, suppl. 3. R. 7243–7250.

22. Weaver R., Silverman B.G., Shin H., Dubois R. Modeling and Simulating Terrorist Decision- making: A “Performance Moderator Function” Approach to Generating Virtual Opponents Center for Human Modeling and Simulation. 2001.

23. Genkin M., Gutfraind A. How Do Terrorist Cells Self-Assemble? / Insights from an Agent-Based Model. Annual meeting of the American Sociological Association, Sheraton Boston and the Boston Marriott Copley Place. Boston, MA, Jul 31. 2008.

24. Tsvetovat M. Artificial Intelligence Based Simulation of Human Systems // The Case of Terrorist Networks. The quarterly Internet-journal «Artificial societies» Volume 2, No 2, Quarter II 2007, Laboratory for artificial societies, www.artsoc.ru, 2007.

Полная версия доступна только подписчикам
Подпишитесь прямо сейчас