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Big Data Analytics for Financial Crime Typologies

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dc.contributor.authorPlaksiy, K.
dc.contributor.authorNikiforov, A.
dc.contributor.authorMiloslavskaya, N.
dc.contributor.authorПлаксий, Кирилл Валерьевич
dc.contributor.authorНикифоров, Андрей Александрович
dc.contributor.authorМилославская, Наталья Георгиевна
dc.date.accessioned2024-11-21T15:44:17Z
dc.date.available2024-11-21T15:44:17Z
dc.date.issued2019
dc.description.abstract© 2019, Springer Nature Switzerland AG.The paper proposes a technique to automate the generation of new criminal cases for money laundering from crime and financing terrorism (ML/FT), which are based on ML/FT typologies. At the same time, the paper is focused not on the existing methods, but offer its own implemented on the basis of creating various versions of case typologies and further filtering them by the derived criteria. For this purpose, it is supposed to use Big Data tools. The successful application of the developed technique is shown on examples of the commission and VAT carousel schemes. To implement and verify this technique a program was written that successfully passed the test on case graphs built on ML/FT typologies.
dc.format.extentС. 165-178
dc.identifier.citationPlaksiy, K. Big Data Analytics for Financial Crime Typologies / Plaksiy, K., Nikiforov, A., Miloslavskaya, N. // Communications in Computer and Information Science. - 2019. - 1054. - P. 165-178. - 10.1007/978-3-030-27355-2_13
dc.identifier.doi10.1007/978-3-030-27355-2_13
dc.identifier.urihttps://www.doi.org/10.1007/978-3-030-27355-2_13
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85077113587&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/19085
dc.relation.ispartofCommunications in Computer and Information Science
dc.titleBig Data Analytics for Financial Crime Typologies
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume1054
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