Singapore’s Project MindForge is entering a more mature phase, as the city-state shifts from isolated AI pilots to the harder work of enterprise-wide governance in financial services.
That change mirrors the broader market: AI adoption across finance functions has accelerated quickly, with institutions increasingly looking beyond experimentation to operational deployments that can deliver measurable efficiency while standing up to regulatory scrutiny.
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.
Launched in June 2023, Project MindForge has now widened its remit beyond generative AI to cover the full AI stack, including traditional machine learning and the emerging category of agentic AI. The expansion reflects a reality many compliance and technology leaders already see internally: financial institutions are deploying multiple AI approaches in parallel, and governance programmes need to apply consistently across them all, rather than being designed for a single model type, it said.
A key milestone arrived in November 2025 with the release of the AI Risk Management Executive Handbook, described as the first of three parts in the wider MindForge AI Risk Management Handbook. The executive edition is positioned as a board- and leadership-facing resource, offering considerations and implementation practices for governing AI, while two further components are planned: an operationalisation handbook with more detailed guidance, and implementation examples with case studies from individual institutions.
MindForge’s materials are intended to work alongside the MAS Guidelines on AI Risk Management, pairing regulatory expectations across the AI lifecycle with more hands-on guidance for implementation.
Singapore is also backing the framework with initiatives designed to support firms at different levels of maturity, it explained. Among the late-2025 announcements are BuildFin.ai, a MAS Financial AI Builder Programme focused on co-development between financial institutions, research bodies, and technology providers; Pathfin.ai, a MAS Pathfinder Programme intended to share industry-validated solutions and implementation practices; and a strategic UK–Singapore partnership on AI-in-Finance, aimed at helping solution providers and innovators operate across both markets.
For financial crime compliance teams, the implications are direct. AI is often pitched as a route to fewer false positives, faster investigations, and more adaptive detection compared with static, rules-based systems. But the direction of travel in MindForge puts equal weight on explainability, human oversight, and continuous monitoring—controls that matter most when regulators and auditors expect decisions to be defensible and outcomes to be reproducible.
Ultimately, the message from Singapore is that scaling AI is no longer just a technology programme, Napier said. Governance is becoming the foundation that enables adoption, and institutions that invest early in controls for transparency, fairness, and auditability may be better positioned as both AI capabilities and supervisory expectations evolve through 2026.
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