Vitaly Krokhalev, Siberian State University of Telecommunication and Information Science, Russian Federation

Nowadays, one of the most important problems for financial companies is fraud related to online transactions. It is becoming increasingly sophisticated and advanced, leading to financial losses on the part of both customers and companies. Based on this, my company was tasked with creating a fraud detection system that is scalable and adaptable to change. This research aims to create a solution that can be used to identify differences in customer behavior patterns and detect fraud. The artificial immune system model proposed in this article, combined with certain informative features, is simple to implement and can describe customer behavior patterns.

Fraud Detection, Artificial Immune System, Informative Features, Machine Learning, Information Security.