From AI Pilots to AI Success: Building Governed AI Factories for Financial Services in Singapore

Singapore’s financial institutions are among the most advanced in AI adoption across Asia, with AI already embedded in areas such as fraud detection, AML investigations, credit risk modelling, and customer analytics.

Yet, as adoption scales, a critical challenge is emerging: moving from fragmented AI pilots to governed, enterprise-wide systems that are trusted, auditable, and production-ready.

Across leading banks in Singapore, common pain points are becoming clear:

• AML & Financial Crime
  High volumes of alerts with limited investigator capacity, fragmented workflows, and difficulty operationalising AI for alert prioritisation, case summarisation, and SAR generation in a governed manner

• Fraud Detection
  Real-time detection models exist, but institutions struggle to balance model accuracy, explainability, and false positives, especially under increasing regulatory scrutiny

• Risk & Credit Modelling
  Challenges in managing model lifecycle, validation, documentation, and audit trails, particularly when introducing GenAI or advanced ML techniques

• MAS Audits & Compliance
  Increasing need to demonstrate AI transparency, lineage, controls, and human oversight, with many institutions still relying on manual or fragmented governance processes

The Regulatory Reality in Singapore

With evolving guidance from the Monetary Authority of Singapore (MAS), including AI risk management frameworks and Project MindForge, institutions are now expected to:

• Maintain clear AI inventories and model lineage

• Demonstrate robust governance, validation, and approval workflows

• Ensure data sovereignty and secure deployment architectures

• Operationalise AI responsibly across traditional, generative, and agentic use cases

This creates what many leaders describe as the “Formula 1 problem”: the technology is ready, but operating it safely, compliantly, and at scale is not trivial.

The Shift Toward Governed AI Factories

To address this, leading institutions are moving toward a Governed AI Factory model, combining:

• NVIDIA: AI Infrastructure and AI software powering the foundation of the AI Factory

• Dell Technologies: secure, enterprise-grade infrastructure for hybrid and sovereign deployments

• Dataiku: orchestration, governance, and lifecycle management across AI, GenAI, and AI agents

This enables banks to:

• scale AI across multiple use cases

• maintain end-to-end governance and auditability

• reduce operational risk while increasing business impact

What to Expect

This private CXO roundtable will focus on the practical realities of scaling AI in Singapore’s regulated banking environment, including:

• Moving from AI pilots to production in AML, fraud, and risk use cases

• Aligning with MAS expectations on governance, explainability, and auditability

• Deploying sovereign and hybrid AI infrastructure within Singapore

• Governing Generative and Agentic AI (e.g., investigator copilots, risk assistants)

• Building the operating model and internal capabilities required for sustainable AI at scale

Why Attend

This is a closed-door, peer-level discussion for senior financial services leaders in Singapore facing similar challenges.

The session brings together:

• NVIDIA: Enterprise AI Factory validated design and AI Infrastructure

• Dell Technologies: infrastructure for secure, compliant AI deployment

• Dataiku: enterprise AI orchestration, governance, and agent management

The focus is clear: how to operationalise AI in a way that satisfies MAS requirements while delivering measurable business outcomes.