Current Volume 9
Abstract
With the advancement towards immediate payments, mobile account opening, cloud-based systems, open banking and data-driven customer journeys in financial services, fraud in digital banking will become increasingly adaptive. This review paper builds a fraud detection and financial security framework using artificial intelligence (AI) for the banking systems of Saudi Arabia in alignment with Vision 2030. The paper asserts that AI can enhance fraud prevention only by incorporating a coordinated approach to machine learning, data management, human-in-the-loop, regulatory compliance and organizational assurances. By following a structured approach to literature review adopted from some Springer-style and systematic review papers published within the last few years, the paper synthesizes scholarly articles related to the use of AI in fraud detection, anomaly detection, privacy-preserving analytics, model management, and cybersecurity of banking institutions. Based on a comprehensive literature analysis conducted during the period 2020 to 2025, five connected capabilities emerge in terms of developing an effective financial security strategy based on AI: trusted data foundation, fraud intelligence modeling, real-time decision controls, investigation, and escalation, and continuous assurance. Through its literature synthesis process, the paper shows how AI helps detect anomalies through several techniques including graph analytics, behavioral biometrics, NLP, ensemble learning, and XAI. The role of fairness testing, model transparency, privacy control in line with the PDPL, and accountability becomes crucial for achieving success.
Keywords
Artificial Intelligence, Fraud Detection, Banking Security, Saudi Banking, Vision 2030, Explainable AI, Financial Crime, Model Governance.
Citations
IRE Journals:
Malik Ashfaq Ur Rahman "AI-Driven Fraud Detection and Financial Security Framework for Saudi Banking Systems" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1652-1662 https://doi.org/10.64388/IREV9I11-1717703
IEEE:
Malik Ashfaq Ur Rahman
"AI-Driven Fraud Detection and Financial Security Framework for Saudi Banking Systems" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717703
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