Abstract

Purpose: This research aims to investigate the intersection of Artificial Intelligence (AI) and banking fraud detection within the framework of banking and finance law. It seeks to explore how AI technologies can be effectively utilized to detect and prevent fraudulent activities in banking operations while ensuring compliance with relevant legal regulations and standards. Research Implications: The study holds significant implications for academia and the banking industry, particularly in understanding how AI can enhance fraud detection capabilities while adhering to banking and finance law. It provides valuable insights for policymakers, regulators, and banking professionals on the legal and regulatory challenges associated with the implementation of AI in fraud prevention strategies. Findings: The findings underscore the potential of AI algorithms to bolster the accuracy and efficiency of fraud detection systems in banking, aligning with the requirements set forth by banking and finance law. By analysing vast datasets and identifying suspicious patterns, AI systems can aid in the timely detection and mitigation of fraudulent transactions, thereby promoting regulatory compliance and safeguarding financial integrity. Originality/Value: This research offers original contributions by examining the synergy between AI technologies, banking fraud detection, and the legal framework of banking and finance law. It highlights the importance of integrating technological advancements with legal requirements to foster a secure and compliant banking environment. By emphasizing the significance of regulatory alignment, the study underscores the value of ethical and lawful AI deployment in combating financial fraud.

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