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Identification of non-typical international transactions on bank cards of individuals using machine learning methods

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dc.contributor.authorDomashova, J.
dc.contributor.authorKripak, E.
dc.contributor.authorДомашова, Дженни Владимировна
dc.date.accessioned2024-11-29T19:39:03Z
dc.date.available2024-11-29T19:39:03Z
dc.date.issued2021
dc.description.abstract© 2020 Elsevier B.V.. All rights reserved.The growing popularity of payment cards has led to the emergence of new types of illegal transactions with money. In particular, the widespread use of non-cash payments has allowed fraud to reach the international level. Therefore, financial institutions are interested in the development and implementation of new effective fraud monitoring systems that will minimize the risk of approving illegal transactions. The article presents the results of applying machine learning methods to detect fraudulent transactions with bank cards. The use of various classification methods in modeling the specified problem is investigated. Generalized algorithm for detecting fraudulent transactions has been developed, which makes it possible to detect atypical international money transfers in real time. Generalized algorithm for detecting atypical international transfers will allow timely detection of potential fraud cases, thereby reducing the total volume of losses from illegal transactions and minimizing the reputation damage caused to the organization.
dc.format.extentС. 178-183
dc.identifier.citationDomashova, J. Identification of non-typical international transactions on bank cards of individuals using machine learning methods / Domashova, J., Kripak, E. // Procedia Computer Science. - 2021. - 190. - P. 178-183. - 10.1016/j.procs.2021.06.023
dc.identifier.doi10.1016/j.procs.2021.06.023
dc.identifier.urihttps://www.doi.org/10.1016/j.procs.2021.06.023
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85112600399&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/24613
dc.relation.ispartofProcedia Computer Science
dc.titleIdentification of non-typical international transactions on bank cards of individuals using machine learning methods
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume190
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