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Development of a Model for Identifying High-Risk Operations for AML/CFT Purposes

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dc.contributor.authorSuyts, V. P.
dc.contributor.authorLeonov, P. Y.
dc.contributor.authorKotelyanets, O. S.
dc.contributor.authorIvanov, N. V.
dc.contributor.authorЛеонов, Павел Юрьевич
dc.date.accessioned2024-11-21T15:44:50Z
dc.date.available2024-11-21T15:44:50Z
dc.date.issued2019
dc.description.abstract© 2019, Springer Nature Switzerland AG.The article has a high practical significance, which is that the described model of processing and clustering data on banking operations has significantly accelerated the process of identifying suspicious (high risk) among them and creating a portrait of a client of a credit institution based on its cashless payments (including his counterparties).
dc.format.extentС. 179-192
dc.identifier.citationDevelopment of a Model for Identifying High-Risk Operations for AML/CFT Purposes / Suyts, V.P. [et al.] // Communications in Computer and Information Science. - 2019. - 1054. - P. 179-192. - 10.1007/978-3-030-27355-2_14
dc.identifier.doi10.1007/978-3-030-27355-2_14
dc.identifier.urihttps://www.doi.org/10.1007/978-3-030-27355-2_14
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85077127484&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/19087
dc.relation.ispartofCommunications in Computer and Information Science
dc.titleDevelopment of a Model for Identifying High-Risk Operations for AML/CFT Purposes
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume1054
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relation.isAuthorOfPublication.latestForDiscovery64455ade-e9d6-4a18-99e7-8bfeb0c30e7b
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