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The work's aim is to research a set of selected mathematical models and algorithms that examine the data of a single payment transaction to classify it as fraud or verified. Described models are implemented in the form of a computer code and algorithms, and therefore can be executed in real-time. The main objective is to apply different methods of machine learning to find the most accurate, in other words, the one in which the cross-validation score is maximal. Thus, the main problem to resolvedblp:conf/m3e2/ShpyrkoK19 fatcat:rnz3mlgmgjadlhqteml7igmpfe