AI Compliance & RegTech for Financial Services in Singapore

The programme is designed to align with MAS's 2025 proposed Guidelines on AI Risk Management, covering risk oversight, life cycle controls, and responsible AI use expectations. We integrate MAS FEAT (Fairness, Ethics, Accountability, Transparency) principles throughout all practical exercises and governance frameworks.

Yes. The programme is eligible for SFEC (S$10,000 per employer at up to 90% offset) and ETSS for qualifying SMEs. Additionally, MAS allocated S$100 million under the National AI Strategy 2.0 specifically for AI and quantum capabilities in the financial sector, which may support qualifying AI transformation initiatives.

Our programme covers multi-jurisdiction compliance including MAS (Singapore), OJK (Indonesia), BNM (Malaysia), and BSP (Philippines) requirements. Singapore-based institutions operating across ASEAN learn to build AI governance frameworks that satisfy the most stringent regulator while being adaptable to each jurisdiction.

All AI workflows covered in this programme comply with PDPA obligations. The Personal Data Protection Act (PDPA) imposes financial penalties of up to 10% of an organisation's annual turnover in Singapore for organisations with annual local turnover exceeding S$10 million. The PDPA requires mandatory data breach notification to the PDPC within 3 calendar days of assessing that a notifiable breach has occurred. We build PDPA-compliant data handling, consent management, and audit trails into every practical exercise.

This programme is eligible for the SkillsFuture Enterprise Credit (SFEC) providing S$10,000 per employer at up to 90% offset, and the Enhanced Training Support for SMEs (ETSS) offering up to 90% course fee subsidies. The Productivity Solutions Grant (PSG) may also cover pre-approved AI solutions at up to 50% funding.

It depends on your jurisdiction and use case. MAS encourages AI in RegTech but expects institutions to have robust governance. OJK requires notification for material AI deployments. BNM expects AI systems to align with RMiT principles. We'll help you navigate regulatory engagement strategies during the training programme.

No. AI automates routine tasks (document verification, sanctions screening, data processing) but human judgment remains critical for complex risk assessments, regulatory interpretation, and customer relationship decisions. The training focuses on augmenting compliance teams, not replacing them.

We teach explainability frameworks including decision audit trails, model documentation, feature importance analysis, and human oversight controls. You'll learn to build regulatory submission materials demonstrating that AI systems are transparent, auditable, and aligned with supervisory expectations.

The programme is designed for compliance professionals, not data scientists. We focus on using AI tools, interpreting outputs, validating decisions, and managing vendors — not building models from scratch. Technical depth is adjusted to match your team's background.

Yes. We cover MAS FEAT principles, OJK POJK AI governance requirements, BNM RMiT, and BSP consumer protection guidelines. You'll learn to build AI validation frameworks, audit documentation, and governance controls that demonstrate regulatory alignment.