Money laundering is the process by which the illegal origin of wealth is disguised to avoid suspicion and to wipe the trail of incriminating evidence.
In response to the growth in money laundering and terrorist financing activities worldwide, regulators have stepped up compliance mandates. As a result, financial institutions have experienced dramatic increases in fines for regulatory violat...ions imposed by a growing array of authorities. In 2012, the US Office of the Comptroller of the Currency (OCC) began applying its Supervisory Guidance on Model Risk Management (OCC 2011-12) to Bank Secrecy Act (BSA) and Anti-Money Laundering (AML) compliance practices. Since then, financial institutions have increased their adoption of more rigorous analytics use to improve their BSA/AML monitoring and Know-Your-Customer (KYC) programs.
With the rise of online and mobile transactions, financial institutions face new challenges in preventing fraud and theft directed at them and their clients. It is imperative for these organizations to find new ways to optimize AML transaction monitoring processes. The problem is that criminal organizations are using increasingly sophisticated and hard-to–detect approaches, and they are getting more effective at obscuring their activities behind the growing complexity of the global financial infrastructure.