The Wealth Management Institute (WMI) in collaboration with Nanyang Technological University Singapore (NTU Singapore), UBS and leading financial institutions in Singapore, embarked on a research project to develop new capabilities utilising artificial intelligence (AI) and machine learning to improve detection of money laundering.

The research focused on the use of artificial intelligence and machine learning to augment the capability of existing systems and human intelligence, ascertain patterns in data and complex transactions to enable financial institutions to better detect unusual money flows and transactions that may be signs of money laundering.

It also showcased the use of secure privacy preserving architecture where underlying data stays with individual banks while data models are extracted, enabling cross-bank AML analytics and intelligence. The deployment of such technologies with powerful data analytics capabilities can help provide financial crime teams across financial institutions the technological tools necessary to widen their surveillance.

Previous SMU Academy Launches New Course On Decentralised Finance (DeFi), Enabling Finance Professionals To Thrive Amid Tech Disruption
Next SGX Receives Long-Term Aa2 Rating, The Highest Assigned To Any Exchange Group By Moody’s

Suggested Posts

NUS Researchers Develop New Microsensor Implants For 24/7 Health Monitoring

UOB Launches U-Energy, Asia’s First Integrated Financing Platform To Drive Energy Efficiency

DBS Aims To Fill Over 140 Engineering Jobs In Second Edition Of Women-Focused Virtual Career Fair For Technologists In Singapore

Grab Launches GrabAssist Plus, Expanding Its Suite Of Transport Services For Persons With Disabilities In Singapore