Singapore is testing a new model for fighting financial crime, one that moves beyond isolated bank defences to a coordinated, AI-driven network. By enabling secure data sharing across institutions, the initiative aims to detect scams earlier, act faster, and stop fraudulent transactions before customers are impacted.
The Monetary Authority of Singapore (MAS) has announced a landmark collaboration with the banking industry, the Government Technology Agency of Singapore, and the Singapore Police Force to harness artificial intelligence and machine learning (AI/ML) to fight financial crime. The initiative centres on a Proof-of-Value (POV) designed to explore pre-emptive scam detection. By aggregating data from five major banks, the project aims to build more accurate models that can identify high-risk accounts and transactions in real time, enabling rapid intervention to minimise customer losses.
A critical component of the POV is establishing a secure data-sharing environment. MAS has implemented strict protocols and cryptographic techniques to safeguard customer information, ensuring that data is used responsibly. For instance, bank account numbers are hashed so that only the contributing institution can identify the actual account. Access is restricted to authorised personnel in a continuously monitored setting, and all data used during the pilot will be deleted upon the pilot’s conclusion to maintain confidentiality.
This initiative is intended to complement the existing anti-fraud efforts of individual financial institutions by providing a broader, industry-wide perspective on criminal patterns. While the initial focus is on scam detection, MAS has indicated that the scope and sophistication of these AI/ML models may be expanded in the future. Potential next steps include incorporating more diverse datasets and a wider array of use cases to further strengthen the defences of Singapore’s financial system against evolving criminal tactics.
The collaboration marks a significant step in Singapore’s proactive approach to financial security, utilising advanced technology to stay ahead of increasingly complex scam operations. Encouraging deeper industry-wide cooperation and sharing intelligence through a secure, regulated framework helps build a more resilient financial ecosystem. Throughout 2026, the outcomes of this POV will serve as a blueprint for how national regulators can leverage collaborative AI to protect citizens and maintain the integrity of the global digital economy.
What this means for the industry
- Fraud detection shifts from siloed to network-wide intelligence
Instead of banks acting independently, this model creates a collective defence system where patterns across multiple institutions can be identified in real time. - AI becomes central to pre-emptive fraud prevention
The focus is no longer just on reacting to scams, but predicting and stopping them before funds are lost, using advanced machine learning models. - Data sharing without compromising privacy is now viable
With techniques like hashing and controlled environments, regulators like Monetary Authority of Singapore are proving that collaboration can happen without exposing sensitive customer data. - Regulators are taking a more active operational role
This is not just policy oversight. MAS is directly enabling infrastructure and frameworks that shape how banks fight fraud on the ground. - A blueprint for national fraud defence systems
If successful, this model could be replicated globally, especially in markets facing rising scam volumes and fragmented banking systems. - Pressure on banks to integrate into shared ecosystems
Institutions that operate in isolation may become weaker links, pushing the industry toward more standardised collaboration frameworks. - Expansion beyond scams is likely
The same infrastructure could be extended to anti-money laundering, cyber threat detection, and broader financial crime use cases. - Customer trust becomes a competitive differentiator
As scams rise globally, banks that can demonstrate proactive, AI-driven protection will gain an edge in retaining and attracting customers.
