Published on: April 2026
AI-BASED FRAUD DETECTION IN BANKING: TECHNIQUES, CHALLENGES, AND BUSINESS IMPLICATIONS
MOHD ZULFQUAR
SHYAM DUBEY ,SIDDHANT MISHRA
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Abstract
Quick development of digital banking, online transactions, and card-based payments has proved to have a major convenience enhancement to customers, but has also heightened associated complexity and frequency of fraud in the banking sector. The conventional fraud detection techniques that mainly depend on predetermined and manual checks cannot sometimes match in detecting the dynamic and emerging fraud trends. Artificial Intelligence (AI) has become a disruption in the field of fraud prevention and risk management in banks, in this respect. Initiating machine learning, anomaly detection, predictive analytics, and real-time monitoring, AI-based fraud detection systems detect suspicious transactions with more precision and speed than traditional systems.
How to Cite this Paper
ZULFQUAR, M. (2026). AI-Based Fraud Detection in Banking: Techniques, Challenges, and Business Implications. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.298
ZULFQUAR, MOHD. "AI-Based Fraud Detection in Banking: Techniques, Challenges, and Business Implications." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.298.
ZULFQUAR, MOHD. "AI-Based Fraud Detection in Banking: Techniques, Challenges, and Business Implications." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.298.
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- •Published on: Apr 17 2026
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