The COVID-19 pandemic boosted digitalization in all areas of human activity, including finances. As a result, the problem of credit card fraud is particularly relevant today. This comprehensive analysis highlights the latest and most relevant developments in the detection of credit card fraud, e.g., artificial intelligence, big data processing, and cloud computing methods. It focuses on the evolution of payment systems, including the shift from traditional methods to innovative solutions based on IoT devices and biometric data. The existing security systems remain vulnerable and require novel fraud detection tools and methods. The modern approaches to transaction data processing include distributed computing and machine learning, which proved effective in the context of dynamically changing users’ behavior patterns. Diverse data sources are needed to improve the accuracy of fraud detection. Cloud technologies can create systems capable of prompt response to new types of fraud in real time. Promising research directions include hybrid models based on data from IoT devices and biometric indicators.
Tat'yana Abduragimova (2025) studied this question.