The surge in Anti-Money Laundering (AML) efforts compared with declining detection rates prompts a need for continuous monitoring of intricate customer behaviors. Beyond transaction rules, traditional clustering, employing KYC data and behavioral patterns, aids in predicting potential money laundering instances. As customers exhibit intricate dynamics, ongoing vigilance becomes essential in identifying anomalous activities.
