AI Compliance & RegTech for Financial Services in Vietnam

The PDPL imposes penalties up to 5% of preceding-year revenue for cross-border transfer violations and up to 10x revenue from illegal data transactions, with a floor of VND 3 billion (approximately USD 120,000). For financial institutions handling large volumes of customer data, the revenue-based calculation can result in significant exposure.

The Cybersecurity Law requires 24-month local storage of Vietnamese user data. For banks using international core banking platforms, cloud-based analytics, or cross-border payment systems, this means implementing local data residency solutions or working with compliant local hosting providers. We design architectures that meet localisation requirements while maintaining AI functionality.

Vietnam's AI Law, effective March 2026, introduces a risk-based classification system (high, medium, low risk). High-risk AI systems require mandatory pre-market conformity assessments and human oversight. We help you assess which classification applies to your use case and prepare the necessary governance documentation before enforcement begins.

Vietnam's Personal Data Protection Law (effective January 2026) requires explicit prior consent for data processing, 72-hour breach notification to the Ministry of Public Security, and impact assessments for cross-border data transfers. The Cybersecurity Law also requires 24-month local data storage for Vietnamese user data. Our implementation includes compliance checkpoints for all these requirements.

Yes. Given that only 15-20% of Vietnam's workforce has business-level English, we deliver all training with Vietnamese-language materials and bilingual facilitators. Hands-on exercises use Vietnamese-language examples and locally relevant case studies.

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.