Singapore is pushing financial services firms beyond AI pilots and into enterprise-wide governance, as Project MindForge enters its next phase. Across Asia Pacific, artificial intelligence has moved quickly from experimentation to deployment, with institutions trying to unlock efficiency while managing risk, accountability, and regulatory expectations.
Napier AI, a provider of next generation AML and financial crime compliance software, recently delved into what firms need to know about Phase 2 of Singapore’s Project MindForge.
Project MindForge, launched in June 2023 as an industry collaboration, has now broadened its scope beyond generative AI. The initiative is positioned to cover the full AI landscape—traditional AI, generative models, and the emerging area of agentic AI—reflecting how financial institutions are adopting multiple AI approaches at the same time.
A key milestone in this journey was the publication of the AI Risk Management Executive Handbook in November 2025. This is the first instalment of a three-part MindForge AI Risk Management Handbook. The executive edition is intended for senior leadership and focuses on considerations and implementation practices for governing AI. Two additional components are planned: an operationalisation handbook offering detailed guidance on embedding practices into day-to-day processes, and implementation examples featuring case studies from financial institutions.
The MindForge handbook is designed to complement the Monetary Authority of Singapore (MAS) Guidelines on AI Risk Management. In effect, the guidelines set expectations across the AI lifecycle, while the handbook aims to translate those expectations into practical steps for implementation, it said.
Singapore is also pairing frameworks with programmes intended to help firms progress through different stages of AI maturity. Three initiatives announced in late 2025 include BuildFin.ai, supporting co-development partnerships between technology providers, research institutes, and financial institutions; Pathfin.ai, designed to share industry-validated AI solutions and implementation practices; and a strategic UK–Singapore partnership on AI-in-Finance, aimed at helping solution providers scale across both markets.
For financial crime compliance teams, the emphasis on governance is particularly significant. AI can help reduce false positives, speed up investigations, and augment rules-based monitoring—yet these gains are difficult to realise without explainability, human oversight, and continuous monitoring. Those controls become even more important as the industry looks at agentic AI, where systems may take decisions or actions with greater autonomy.
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