The challenge is scaling from individual AI applications to bank-wide deployment while preserving security and customer trust, which requires robust data governance, open data considerations, and clear AI authority with human oversight.

The aim is a resilient operating environment that supports modernization while maintaining control over mission-critical processes.

Banking data from transactions enables needs analysis, personalized services, and timely support; QR code payments surged, with more than 311 million transactions totaling over 274 trillion VND in the first eight months of 2026.

Regulators and industry leaders outline five strategic pillars for 2030: Agent AI over GenAI, open data/identity/finance, next-gen digital payments and assets, real-time and sustainable operations, and responsible AI governance.

Regulatory frameworks such as Texas TRAIGA and Colorado Automated Decision-Making Technology Act require ongoing monitoring, documentation, explainability, and oversight of AI systems, including model drift considerations.

International perspectives include Australian banks prioritizing risk control alongside efficiency and ASEAN Banking Association discussions on technologies aligned with Vietnam’s legal framework and deployment capabilities.

Compliance-by-design is recommended: map AI usage, classify risks by use case, implement controls, and build an audit trail to stay ahead of regulations and ensure clear customer communications.

Islands of automation and disparate schedulers pose risk; end-to-end workflow mapping and clear handoffs across legacy, cloud, and third-party systems are needed.

State Bank of Vietnam Circular No. 53/2026/TT-NHNN will regulate AI safety, risk management, and deployment conditions in banking, effective mid-November 2026, with mandatory human supervision and lifecycle risk controls.

A cloud-first, AI-powered orchestration approach offers benefits for modeling dependencies and coordinating cutovers, but requires visibility, governance, and strong data foundations.

Smart Banking 2026 featured a roundtable on integrating AI into practical operations, marking a shift from digitalization to data-driven operational redesign and enhanced customer experience.

Governance should require explainability of data inputs, rationale for actions, human overrides, and monitoring across customer groups, with attention to third-party vendor risk and documentation.