What is MAS FEAT Principles?
MAS FEAT Principles (Fairness, Ethics, Accountability, Transparency) provide the foundation for responsible AI deployment in Singapore's financial sector. These principles guide financial institutions in developing AI systems that are fair in outcomes, ethically sound in design, clearly accountable in governance, and transparent in operation and decision-making.
This glossary term is currently being developed. Detailed content covering regulatory requirements, compliance obligations, implementation guidance, and business implications will be added soon. For immediate assistance with this regulation or compliance requirement, please contact Pertama Partners for advisory services.
MAS FEAT compliance is effectively mandatory for financial institutions operating in Singapore, with non-adherence flagged during routine supervisory reviews and potentially affecting licensing approvals and operational permissions. The principles-based framework costs substantially less to implement than prescriptive regulations, typically requiring USD 25K-60K for initial assessment, governance establishment, and documentation of ongoing monitoring practices. mid-market companies providing AI solutions to Singapore's financial sector must demonstrate credible FEAT alignment to pass vendor due diligence requirements that increasingly gate procurement decisions at banks, insurers, asset managers, and fintech companies operating under MAS supervision.
- Fairness addresses bias and discrimination in AI outcomes.
- Transparency requires explainability of AI decisions affecting customers.
- Implement FEAT self-assessment checklists across all AI models used in financial services including credit scoring, fraud detection, customer segmentation, and automated advisory applications.
- Document fairness metrics demonstrating equitable outcomes across demographic groups and present findings to board-level oversight committees on a quarterly review schedule for governance.
- Align explainability requirements with the complexity tier of each AI system because MAS expects proportionate transparency measures rather than uniform disclosure standards across all models.
- Use Veritas methodology toolkits published by MAS for structured fairness evaluation that satisfies regulatory expectations during routine supervisory examinations and special reviews.
Common Questions
What organizations does this regulation apply to?
Application scope varies by regulation. Typically includes organizations processing personal data, deploying AI systems, or operating in regulated sectors. Consult legal counsel for specific applicability.
What are the penalties for non-compliance?
Penalties vary by jurisdiction and violation severity, ranging from warnings to substantial fines and operational restrictions. Review specific regulation for penalty provisions.
More Questions
Implement comprehensive compliance program including policy development, technical controls, staff training, regular audits, and ongoing monitoring. Consider engaging compliance advisors for complex requirements.
References
- NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology (NIST) (2023). View source
- Stanford HAI AI Index Report 2025. Stanford Institute for Human-Centered AI (2025). View source
- EU AI Act — Regulatory Framework for Artificial Intelligence. European Commission (2024). View source
- NIST AI Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology (NIST) (2023). View source
- Singapore's Approach to AI Governance — Model AI Governance Framework. Personal Data Protection Commission (PDPC), Singapore (2024). View source
- AI Regulation: A Pro-Innovation Approach. UK Department for Science, Innovation and Technology (2023). View source
- Artificial Intelligence and Data Act (AIDA). Government of Canada (2024). View source
- Brazil AI Act: Senate Advances Bill to Regulate AI Use. Library of Congress / Brazilian Federal Senate (2024). View source
- Understanding AI Regulations in Japan: Current Status and Future Prospects. DLA Piper (2024). View source
- Global AI Governance Law and Policy: Japan. International Association of Privacy Professionals (IAPP) (2024). View source
Indonesia Presidential Regulation on AI establishes national framework for AI governance, development priorities, and ethical standards. The regulation promotes responsible AI innovation aligned with Pancasila values while supporting Indonesia's digital economy ambitions and national AI strategy implementation.
OJK (Otoritas Jasa Keuangan) AI Code of Ethics provides principles for Indonesian financial institutions deploying AI and advanced analytics, covering fairness, transparency, accountability, data privacy, and consumer protection. The code ensures AI deployment in Indonesia's financial sector maintains integrity and public trust.
Indonesia Data Protection Authority is the designated enforcement body for Indonesia's PDP Law, responsible for overseeing compliance, investigating violations, and protecting data subject rights. The authority will issue regulations, conduct audits, and impose penalties for data protection breaches.
POJK 22 (OJK Regulation 22) addresses consumer protection in Indonesian financial services, including provisions relevant to AI-driven decisions, algorithmic transparency, and automated customer interactions. The regulation ensures financial institutions maintain fair and transparent practices when deploying AI systems affecting consumers.
Philippines Data Privacy Act (DPA 2012) is the Philippines' comprehensive data protection law establishing principles for lawful personal data processing, data subject rights, and controller/processor obligations. The Act applies to AI systems processing Filipino personal data and requires organizations to implement security measures and accountability mechanisms.
Need help implementing MAS FEAT Principles?
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