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Anti-Money Laundering Prototype Utilising AI and Machine Learning in Singapore

Combatting money laundering is compounded in a digital age as perpetrators employ increasingly sophisticated ways to misuse the financial system and launder illegal proceeds. With the increase in transaction volumes and data, the tasks of detecting anomalous transactions and financial crimes indicia are even more challenging. It is therefore imperative to develop the necessary defence systems and ever more sophisticated tools to detect money laundering activities

Nanyang Technological University Singapore (NTU Singapore) 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 AI 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.

The research 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 with the technological tools necessary to widen their surveillance.

The financial sector has made much progress to deepen Anti-Money Laundering (AML) competencies and to strengthen understanding of emerging AML risks and typologies. To stay ahead of the criminals, the research project has shown that collaborative efforts amongst industry players and public-private sector engagement leveraging artificial intelligence and machine learning technologies, can significantly enhance our collective fight against money laundering.

The research project team expresses the deepest gratitude for the support provided by the Artificial Intelligence and Data Analytics (AIDA) scheme, which provides funding support to strengthen the AIDA ecosystem in the Singapore financial sector. The AIDA scheme is part of the Financial Sector Technology and Innovation (FSTI) scheme under the Financial Sector Development Fund administered by the Monetary Authority of Singapore (MAS).

NTU’s Senior Vice President (Research) Professor stated that the research is another example of the University’s strong links with the private sector. With its globally renowned strength in AI, Machine Learning and Data Science, NTU partnered with financial institutions to launch this important Anti-money Laundering (AML) initiative with industry to provide a safeguard for the public sector, specifically the financial industry. The collaboration also reflects the University’s commitment to be at the epicentre of pioneering research, as part of the NTU 2025 strategic plan.

NTU has built the building blocks for an AI-based anti-money laundering system with a modular architecture that allows financial institutions to customise the building blocks for their compliance needs. This modular approach is critical to creating the client-centric, intelligent robot-AML system of the future when financial institutions will be taking an ex-ante approach towards AML compliance versus the current ex-post approach.

The fruits of this research project are exceptionally useful contributions to the industry through the benefits of using AI and machine learning to improve transaction monitoring, which we are confident will help to combat financial crime for organisations that adopt this tool and screening methods.

Singapore has been deploying research projects to combat money laundering. As reported by OpenGov Asia, the Asian Institute of Digital Finance (AIDF) pursued foundational and inter-disciplinary research projects covering fundamental digital infrastructure, performance optimisation of business processes, and advanced application development research on cyber, fraud and anti-money laundering challenges. The institute also developed financial services to meet sustainability and resiliency needs.

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