The MAS AIRG Readiness Score,Know Your AI Risk Before Regulators Do
The Samta MAS AIRG Readiness Score is a free, 10-minute self-assessment that benchmarks your institution's AI governance maturity against MAS's incoming AI Risk Management Guidelines (AIRG), MAS FEAT, MAS Veritas, and IMDA's Model AI Governance Framework and hands you a board-ready remediation roadmap the moment you finish.
Chosen by Singapore Enterprise Leaders for AI and Data Excellence
From Score to Audit-Ready in Four Steps
No implementation. No migration. No 18-month timeline. Start now, in your browser zero technical setup required.
Assess
- Rate your institution across five AI model risk domains.
- No technical expertise required this is a leadership-level exercise, not an engineering one.
Score
- Get your MAS AIRG Readiness Score across all five domains, benchmarked against where MAS expects institutions to stand once AIRG takes effect.
- Maturity levels run from Foundational through Experimental and Operational to Transformational and AI-Native.
Diagnose
- See your domain-by-domain breakdown and a risk heatmap.
- Including exactly where your AI governance would hold up under regulatory scrutiny today, and where it wouldn't.
Roadmap
- Get a prioritised 90-day roadmap with next steps.
- Specific enough to present directly to your board or CRO, not a generic maturity-model slide.
Get Your MAS AIRG Readiness Score
Benchmark your AI governance maturity across five critical domains, mapped to the MAS FEAT principles, the incoming MAS AIRG guidelines, MAS Veritas, and IMDA's Model AI Governance Framework with NIST AI RMF and the EU AI Act referenced as international baselines, not the primary standard.
Start Your Readiness Score
Enter your work email to receive your comprehensive MAS AIRG Readiness Score and personalised recommendations.
Contact Information
Governance & Ownership
Data & Third-Party Exposure
Model Transparency & Control
Operations & Assurance
Email Address
Full Name
MAS AIRG vs. FEAT vs. Veritas vs. SAFR vs. IMDA
How the Frameworks Relate
| Framework | What it is | Status | Applies to |
|---|---|---|---|
MAS FEAT | Foundational principles: Fairness, Ethics, Accountability, Transparency | In place since 2018 | All AI/data-analytics use in Singapore financial services |
MAS AIRG | Full risk-management lifecycle guidance for AI, extending FEAT | Consultation closed early 2026; finalisation expected later this year, with a transition period after | Financial institutions, including generative AI, autonomous agents, and third-party/vendor AI tools |
MAS Veritas | Industry-developed methodologies for assessing FEAT in practice | Ongoing industry initiative | Financial institutions applying FEAT operationally |
SAFR | Runtime-level technical safeguards for agentic AI systems | Sits underneath AIRG for agentic use cases | Institutions running or piloting autonomous AI agents |
IMDA Model AI Governance Framework | Singapore's cross-sector AI governance reference, incl. agentic AI guidance | National, sector-agnostic | All Singapore organisations deploying AI, complementing MAS's sector-specific rules |
Which Singapore AI Governance Frameworks Does This Map To?
MAS AIRG — Guidelines on AI Risk Management
The proposed MAS AIRG extends AI risk management across the AI lifecycle, including generative AI, autonomous AI agents and third-party AI. This Readiness Score is structured around the direction of AIRG.
MAS FEAT — Fairness, Ethics, Accountability & Transparency
The MAS FEAT principles form a foundation for responsible AI in Singapore financial services. Your score assesses practical governance across fairness, accountability, ethics and transparency.
MAS Veritas — Responsible AI Assessment Methodologies
MAS Veritas helps financial institutions assess responsible AI practices against FEAT principles. Your report highlights relevant Veritas-aligned governance practices and gaps.
SAFR — Safeguards for Agentic Finance at Runtime
SAFR addresses runtime safeguards for agentic AI and autonomous AI agents in financial services. Agentic AI responses trigger relevant SAFR considerations in your roadmap.
IMDA Model AI Governance Framework — Singapore's Cross-Sector AI Governance Reference
IMDA's Model AI Governance Framework provides broader guidance for responsible AI, including agentic AI. It complements MAS's financial-sector-specific AI governance expectations.
A boardroom-ready report. In 5 minutes. Free.
Your AI Model Risk Exposure Scorecard includes domain scores, a risk radar chart, gap analysis, and a prioritised roadmap structured for executive communication.
Strategy & AI Governance
Data Risk & Infrastructure
Model Transparency & Control
Monitoring, Drift & Lifecycle
Compliance & External Exposure
Know your AI risk before
your board or regulators do.
10 minutes. 5 domains. One clear picture of where your AI governance stands and exactly what to fix next.