Abstract
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).
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APA
Leonov, P. Y., Suyts, V. P., Kotelyanets, O. S., & Ivanov, N. V. (2019). Development of a Model for Identifying High-Risk Operations for AML/CFT Purposes. In Communications in Computer and Information Science (Vol. 1054, pp. 179–192). Springer. https://doi.org/10.1007/978-3-030-27355-2_14
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