The particulars of using machine learning to detect banking fraud

Fraud remains a classic problem for the global banking industry, which has a general trend of permanent amplification and qualitative change. Along with this, modern banking is related to the use of an increasing volume of data related to the activity of financial markets, banking institutions and their customers. In these conditions, the implementation of new artificial intelligence technologies and, in particular, machine learning, for the timely detection of existing anomalies related to the potential existence of fraud, becomes relevant. Machine learning is about building computer systems capable of learning from data and improving their performance over time. This article presents the essence, basic features and benefits of machine learning, as well as the specifics of its application for the purpose of combating bank frauds.