From boardrooms to markets, deepfake-enabled crimes are increasingly interconnected — spanning impersonation fraud, romance scams, and market-moving misinformation.
Deepfake : Regulatory Context
The Monetary Authority of Singapore (MAS) has reinforced the importance of addressing emerging deepfake and AI risks through multiple frameworks.
The Technology Risk Management (TRM) Guidelines requires continuous monitoring, anomaly detection, and multi-layered authentication to counter evolving attack vectors (paras. 8.1.3 and 8.3.2). Additionally, MAS’ AML/CFT Notices mandate additional measures which may include enhanced due diligence and suspicious-transaction reporting for synthetic or impersonation-linked activity – particularly where such risks are likelier to occur (e.g. remote onboarding of customers).
Complementing this, FATF’s Guidance on Digital Identity (2020) highlights that remote onboarding processes relying on digital ID systems must account for vulnerabilities such as the use of synthetic or manipulated media. The guidance urges FIs to implement strong biometric verification and anti-spoofing liveness detection to mitigate these risks (Sections III, paras. 64–68, 80–83).
PSN01 and PSN02 (for Payments services) and SFA04-N02 (for Capital Markets services) – and their supplementary guidelines, similarly mandate robust customer due diligence, independent verification, and immediate escalation when red flag indicators are suspected.
Recognising the Red Flags
Before implementing defence mechanisms, FIs must first recognise the early warning signs of deepfake-enabled financial crime. These indicators often emerge subtly through communication tone, visual inconsistencies, or unusual transaction behaviour, and can offer the first clues that a fake identity or impersonation attempt is in progress.
RED FLAGS & DETECTION INDICATORS
COMMON WARNING SIGNS OF DEEPFAKE-ENABLED FINANCIAL CRIME
COMMUNICATION
ANOMALIES
Unusual tone, urgency, or phrasing in messages; requests to bypass normal verification procedures.
VISUAL / AUDIO
MISMATCHES
Lip-sync errors, inconsistent eye blinking, distorted background or unusual audio patterns.
SUSPICIOUS
ACTIVITY PATTERN
Calls outside normal work hours; emotional manipulation; refusal to verify identity or instructions.
TRANSACTION
TRIGGERS
Changed bank details, new or unfamiliar payees, or requests for rushed fund transfers.
Defensive Measures Against Deepfake Risks
Once potential warning signs are identified, financial institutions should strengthen their defences across technology, processes, people, and collaboration.
1. Implementation of Technology Controls
- Liveness detection with multi-modal biometric analysis (motion, thermal imaging, 3D depth analysis).
- Digital watermarking and media fingerprinting to identify synthetic media.
- Real-time AI-based deepfake detection in video or voice calls.
- Endpoint security safeguarding authentication hardware and software.
2. Policy and Process Enhancements
- Multi-factor authentication for high-risk transactions.
- Separation of duties and dual authorization for fund transfers.
- Implementation of dynamic verification protocols, possibly utilising government databases.
- Integrating deepfake attack scenarios in incident response playbooks.
3. Human Factors
- Comprehensive employee training to identify tell-tale signs (unnatural facial movements, audio distortions).
- Simulation programs for impersonation and phishing.
- Customer awareness initiatives on emerging scams.
4. Collaboration
- Active intelligence sharing between market participants, enforcement authorities, regulators and industry peers.
- Sector-wide synthetic media threat monitoring response coordination.
The following areas illustrate the core layers of protection that help firms build resilience against deepfake-enabled threats.
Deploy advanced tools such as liveness detection, watermarking and AI-driven detection to identify manipulated media.
Technological
Controls
Implement multi-factor authentication, dual approvals, and incident response protocols to reduce exploitation risks.
Process
Controls
Train employees and customers to recognise deepfake artefacts, phishing attempts, and impersonation cues.
Human
Factors
Share intelligence with regulators and industry peers to strengthen collective defences against synthetic media threats.
Collaboration
Conclusion
Deepfakes represent a new class of cyber-enabled financial crime — one that exploits trust in both technology and human relationships. For FIs, the challenge is not only to defend against fraudulent transactions but also to preserve confidence in digital interactions.
Deepfakes are not a future threat; they are a present risk. Institutions that fail to adapt will find themselves vulnerable to the next incident.
Managing Deepfake Risks and Operational Resilience
As deepfake risks Singapore continue to evolve, RFIs will need to strengthen governance, monitoring and fraud detection capabilities.
Curia Regis works with RFIs across the market to build and implement regulatory compliance frameworks that are focused on cyber-resilience, addressing AML/CFT concerns arising from such new technology. Anchored in Singapore’s regulatory landscape, we combine deep expertise to help firms stay ahead of evolving risks.
Our collaborative approach delivers:
- A clear policy basis and methodology to address regulatory requirements.
- Early identification and assessment of potential risks.
- Practical implementation of technology and process safeguards.
- Ongoing staff training and readiness simulations.
- Comprehensive incident response coordination aligned with the prescribed guidelines.
By aligning operational practices with regulatory expectations, we enable FIs to protect their businesses, preserve client trust, and demonstrate resilience in the face of this new reality.
If you need guidance on translating your organisation’s exposure to the risks presented by emerging technology into practical safeguards that strengthen your compliance and cyber-resilience, contact us here or email us at admin@curiaregis.com
