MTUCI experts used a dataset containing credit card transactions from the Kaggle website to train the model. They emphasized that the model they developed could effectively detect fraudulent activities, and that the model could generalize to unknown data and showed high accuracy.
The creation of this model was based on an already existing neural network, which contributed to more fundamental research in the field of fraudulent transaction recognition. The developers emphasized that the model takes into account various patterns, such as the type of bank card and the characteristics of the device used for transactions.
As Irina Yablochnikova, associate professor in the Intelligent Systems Department of Control and Automation at MTUCI, notes, the neural network model can be used as a first line of defense against Internet fraud. However, he emphasized that further research and testing of the model poses some difficulties due to the confidentiality of banking information.
Source: Ferra
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