Integration of Big Data, RegTech, and Artificial Intelligence in Modern Architectures for Bank Fraud Prevention
Caprian Iurie

Caprian, Iurie. (2026) “Integration of Big Data, RegTech, and Artificial Intelligence in Modern Architectures for Bank Fraud Prevention.” The Problems of Economy 1:223–228.
https://doi.org/10.32983/2222-0712-2026-1-223-228

Section: Finance and banking

UDC 336.71:343.359.3

Abstract:
Bank fraud has increased markedly over the past decade in both complexity and scale, compelling financial institutions to adopt advanced technological frameworks to maintain operational resilience and financial stability. This article examines the integration of Big Data, Regulatory Technology (RegTech), and Artificial Intelligence (AI) into a unified architecture for bank fraud prevention, capable of processing large volumes of transactional data, automating compliance activities, and enabling real-time predictive detection of fraudulent behavior. The analysis is grounded in a review of recent academic literature, regulatory reports, and case studies from leading global financial institutions that have implemented technology-driven anti-fraud solutions. The study highlights how Big Data technologies support scalable data collection and processing, RegTech facilitates automated compliance with AML and KYC requirements, and AI enhances predictive analytics through machine learning and pattern recognition. The findings indicate that the synergy among these technologies significantly reduces fraud response times, improves anomaly detection accuracy, and increases operational efficiency while lowering compliance costs. Despite these advantages, several challenges persist, including risks of algorithmic bias, data quality and interoperability issues, cybersecurity concerns, and the need for transparent and explainable AI models. Additionally, differences in national regulatory frameworks hinder seamless cross-border implementation. The study concludes that an integrated Big Data–RegTech–AI architecture represents an efficient and sustainable strategy for modern bank fraud prevention, provided it is supported by robust data governance, ethical AI principles, regulatory alignment, and inter-institutional collaboration.

Keywords: bank fraud prevention, Big Data analytics, RegTech, Artificial Intelligence, AML/KYC, anomaly detection, financial security.

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Caprian Iurie – Postgraduate Student, State University of Moldova (60 Alexei Mateevici Str., Chisinau, Moldova)
Email: iuriecaprian@gmail.com

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