Under the theme “Shaping the next era of banking through AI, customer trust and digital resilience”, discussions focused on three closely interconnected priorities: harnessing AI to deliver tangible value, transforming governance and operations, and safeguarding system security while maintaining customer trust.
Dr. Dao Minh Tu, Vice Chairman and Secretary General of VNBA
From process digitisation to data-driven intelligent banking
Speaking at the Banking Leadership Dialogue on 21 October, Dr. Dao Minh Tu, Vice Chairman and Secretary General of VNBA, emphasised that the banking sector was moving beyond the digitisation of individual processes and services towards leveraging data and AI to redesign operating models, strengthen risk management and improve customer experience. AI is no longer merely a technical tool; it is becoming a core strategic capability that shapes decision-making and value creation across credit institutions.
The rapid expansion of digital payments is providing a foundation for this transition. Figures presented at the event showed that, in the first eight months of 2026, cashless payment transactions increased by 46.57% in volume and 21.77% in value year on year. QR-code payments alone accounted for more than 311 million transactions, with a total value exceeding VND 274 trillion. As of 22 October 2026, the banking system was processing approximately 100 million payment transactions a day, with a combined value of around VND 1.2 quadrillion.
In his address at the conference on 22 October, SBV Deputy Governor Pham Tien Dung stressed that AI must address concrete business challenges, improve service quality, enhance operational efficiency and enable earlier risk detection. Technology investment should be driven by practical needs and business objectives, rather than by technology trends or experimentation alone.
Experience from commercial banks illustrates AI’s potential to improve productivity and customer experience. TPBank reported that it had deployed more than 60 AI applications across 13 business divisions. The use of AI throughout the software development lifecycle had reduced processing time by approximately 50% and increased productivity by two to three times. At Techcombank, AI applications in selected technology development activities had delivered productivity gains of around 20–30%.
However, these benefits cannot be achieved simply by automating individual tasks. Banks need to reassess end-to-end processes, prioritise the right business challenges and evaluate initiatives against multiple criteria, including revenue generation, cost savings, customer experience, risk reduction, and long-term implementation and operating costs. AI adoption must also be accompanied by clear accountability, acceptable error thresholds and appropriate safeguards.
AI governance must keep pace with adoption
To realise AI’s potential across their organisations, credit institutions need to develop their capabilities in data management, technology infrastructure, human resources, regulatory compliance and risk governance in a coordinated manner.
According to Doan Thanh Hai, Deputy Director General of the SBV’s Information Technology Department, banks need complete, accurate and regularly updated data that can be shared across systems. Their technology infrastructure must support large-scale data processing, scalability and the integration of AI into business processes. As AI agents become increasingly capable of carrying out tasks autonomously, banks must establish clear boundaries for their activities, define their authority, and put in place appropriate oversight and accountability mechanisms.
For AI investment decisions, Vietcombank shared its use of the DVF framework, which assesses initiatives against three criteria: Desirability, or the value and relevance to users; Viability, or business effectiveness and value creation; and Feasibility, or practical implementability. This approach helps banks prioritise initiatives that address genuine needs, deliver economic benefits and can be implemented effectively.
Beyond technology, human capabilities and collaboration between business and technology teams are critical. AI transformation is not simply a matter of introducing new tools into existing processes; it requires changes in how work is organised, decisions are made and operations are governed. Regulators, banks and technology providers also need to strengthen cooperation to support responsible innovation, ensure compliance and manage risks effectively.
Strengthening customer trust and digital resilience
Alongside the opportunities created by AI, growing dependence on technology and digital ecosystem partners is increasing exposure to cybersecurity threats, fraud and operational disruption. With approximately 100 million payment transactions processed daily, an incident at a single point of connection could have wider systemic implications if it is not detected and addressed promptly.
At Smart Banking 2026, SBV Deputy Governor Pham Tien Dung called on banks to move beyond traditional defensive approaches towards proactive threat detection, incident response and operational recovery. Cybersecurity cannot be treated solely as the responsibility of information technology departments. Business units must also be able to recognise unusual activity, coordinate investigations and respond promptly to suspicious transactions.
According to figures presented at the event, by 15 October 2026 the SBV’s SIMO early-warning system had issued alerts to more than 5.8 million customer instances. Alongside enhanced monitoring, the banking sector continues to strengthen data cleansing and customer authentication, while introducing tools that help customers take a more active role in protecting their accounts. These measures are intended to reduce fraud and the risk of financial loss.
Digital resilience therefore extends beyond preventing cyberattacks. It also encompasses early threat detection, coordinated incident response, the continuity of essential services and safe operational recovery. Achieving this requires continuous monitoring, behavioural anomaly detection, stronger incident-response capabilities and effective coordination with relevant authorities and technology partners.
Smart Banking 2026 underscored that the future of intelligent banking will not be determined solely by the sophistication of technology or the number of AI applications deployed. Sustainable competitive advantage will depend on banks’ ability to translate technology into business value and tangible customer benefits, while maintaining effective governance, protecting data, controlling risks and ensuring operational continuity. AI, customer trust and digital resilience must therefore be developed as mutually reinforcing pillars of each bank’s transformation strategy.
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