Credit cards fraud identification investigation

Abstract

Different institutions face the challenge of adapting to new technologies, incorporating artificial intelligence into their own activities and monitoring the changes. Artificial intelligence can make easier monitoring of various anomalies, as well as counterfeiting credit card payments. The aim of this paper is to describe the artificial intelligence concept in the financial sector using the algorithms and to investigate the database that was found in the Kaggle database. During the work, artificial neural networks were described, and algorithms are often used in the financial sector (eg: Vector Support Machines, K–Neighbor Models). A credit card database was also introduced and analyzed, which can be used to teach an artificial neural network. When analyzing the database, Python programming language was used to draw graphs. During my work I managed to learn about artificial neural networks, it became clear that the database under study was made up of real transactions and the data was transformed due to confidentiality, but still the database is suitable for training the neural network.