The Role of Artificial Intelligence in Detecting Money Laundering and Its Impact on the Confidentiality of Bank Customers’ Accounts

Abstract

Banking secrecy is one of the essential principles of the banking system, as banks are obliged to safeguard their customers’ information and refrain from disclosing it except in cases explicitly stipulated by law. The adoption of modern digital technologies in banking services has rendered banks an attractive environment for money launderers, who seek to exploit these features to conceal funds derived from illegal activities, so that after laundering they appear to originate from legitimate sources. As a result, traditional methods used to monitor and detect money laundering activities have become inadequate to keep pace with increasingly sophisticated and evolving techniques. This has prompted competent authorities to adopt new strategies that correspond to the nature of emerging risks, leading many states to rely on artificial intelligence systems as part of their efforts to combat money laundering. However, the effectiveness of these systems depends on their integration with human expertise to ensure genuine efficiency in identifying suspicious activities. This study aims to examine the role of artificial intelligence in combating money laundering and to assess its impact on the privacy of customers’ data, through an analysis of the traditional legal framework and the artificial intelligence mechanisms employed in this field.