The Monetary Authority of Singapore (MAS) has released a sweeping consultation paper outlining proposed Guidelines on Artificial Intelligence Risk Management, seeking public feedback as the city-state moves to strengthen oversight of AI deployment across the financial sector. The consultation runs from 13 November 2025 to 31 January 2026.
The draft guidelines set out MAS’ supervisory expectations for how banks, insurers, capital markets firms and other financial institutions should govern, test, monitor and manage risks arising from artificial intelligence, including generative AI and autonomous AI agents. According to the document, MAS aims to ensure that AI systems used in financial services remain safe, fair, transparent and accountable, and that institutions put in place “robust frameworks, policies, procedures, and controls” throughout the entire AI lifecycle.
The proposed rules would apply to all financial institutions operating in Singapore, though MAS emphasizes a proportionate approach based on each firm’s size, business model, and level of AI integration. All institutions would be required to maintain clear AI usage policies, designate responsible oversight personnel, and identify and inventory all AI systems used in their operations. Higher-risk AI applications — such as those involved in credit decisions, risk management, or customer-facing advice — would be subject to stricter controls, including independent validation, stress testing, transparency obligations and enhanced human oversight.
The draft also highlights emerging risks posed by generative AI, including hallucinations, data leakage, copyright and privacy concerns, and vulnerabilities to adversarial attacks. MAS notes that increasingly autonomous AI agents could introduce additional operational and security risks, requiring new safeguards.
MAS proposes a 12-month transition period once the guidelines are finalized, acknowledging varying levels of AI maturity across the sector. The regulator is seeking industry views on risk assessment methods, governance structures — including whether high-exposure firms should form dedicated cross-functional AI committees — and appropriate lifecycle controls.
Submissions will be published unless confidentiality is requested.
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