Real-Time Transaction Monitoring Using AI: Detecting Suspicious Activities and Money Laundering in Banking

Abstract

This research paper explores the application of Artificial Intelligence (AI) in real-time transaction monitoring for detecting suspicious activities and combating money laundering in the banking sector. Money laundering poses significant threats to financial institutions and regulatory authorities globally. Traditional methods of transaction monitoring often fall short in identifying complex illicit activities due to their inability to handle large volumes of data and evolving tactics of money launderers. AI, particularly machine learning algorithms, offers promising solutions by enhancing the detection capabilities through automated analysis of vast datasets and pattern recognition. This paper discusses various AI techniques, challenges, and future prospects in the realm of real-time transaction monitoring for ensuring financial integrity and regulatory compliance in banking.