Anti-money laundering (AML) defenses might begin at the point of onboarding.
The needs are for all manner of firms — and especially banks and investment management companies — to embrace technology in the service of beefing up their onboarding processes and automating them too.
Media sites including The Wall Street Journal (WSJ) reported Thursday that U.S. regulators are examining Morgan Stanley’s anti-money laundering efforts.
The scrutiny comes from a broad range of regulators, ranging from the Securities and Exchange Commission to the Office of the Comptroller of the Currency.
Specifically, the agencies are reportedly looking for information on some clients based outside the U.S. — and in some cases, business done with Morgan Stanley even after those customers had been reportedly cut off by E*Trade, the digital-trading platform the company acquired by Morgan Stanley.
The OCC has reportedly sent Morgan Stanley a “matter requiring attention” notice regarding its controls and procedures. And per the report from WSJ, Morgan Stanley has responded to regulators’ concerns by compliance, technology and artificial intelligence (AI).
News of the Morgan Stanley examination comes in the wake of reports at the end of last month that the Financial Crimes Enforcement Network (FinCEN) requested comments on its Customer Identification Program (CIP) requirements for banks.
Comments submitted in response to the request will also help FinCEN identify regulations and guidance that may be outdated. And as reported, over a 14-month period in 2021 and 2022, FinCEN imposed more than $600 million in fines for AML violations.
Earlier this year, the Financial Action Task Force (FATF) added new countries to its “increased monitoring” list. The recent revisions included Kenya and Namibia on that list while removing Barbados, Gibraltar, Uganda and the United Arab Emirates (UAE).
PYMNTS Intelligence has found that more than 40% of financial institutions are seeing increasing volumes of fraud and financial crime. Research done in collaboration with Hawk AI finds that 7 in 10 told us they now are using AI and machine learning to battle bad actors. Uncovering whether someone is who they say they are is critical. Separate data show that 4.6% of transactions were classified as synthetic identity fraud.
And, per the Fed’s FraudClassifier model, synthetic IDs accounted for a commensurate percentage of dollar losses experienced by FIs.
As detailed here, in joint efforts between PYMNTS and Featurespace, 200 executives from a range of FIs with assets of at least $5 billion revealed heightened awareness about money laundering and other financial fraud — and the need for innovation to detect and prevent it. Ninety-five percent of AML executives said they consider it a “high priority” to use advanced technologies in those efforts.
AI is increasingly at the forefront of those efforts. In one example, Oracle Financial Services introduced an AI-powered cloud service that helps banks mitigate AML risks. The new Oracle Financial Services Compliance Agent “identifies and remediates vulnerabilities,” the company said in its announcement.