Digital Transformation of Payment Systems: Fraud Issues and Detection Prospects

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.

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Publication Details

Journal
Bulletin of Kemerovo State University Series Humanities and Social Sciences
Published
2025-09-30
DOI
https://doi.org/10.21603/2542-1840-2025-9-3-453-461
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Digital Transformation of Payment Systems: Fraud Issues and Detection Prospects

Tat'yana Abduragimova
Bulletin of Kemerovo State University Series Humanities and Social Sciences
Big Data and Business Intelligence
article

Digital Transformation of Payment Systems: Fraud Issues and Detection Prospects

Tat'yana Abduragimova
article en

Abstract

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.

Bulletin of Kemerovo State University Series Humanities and Social SciencesVol. 9(3)
Openalex Percentile: Top 57%
Big Data and Business Intelligence
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