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In a rapidly evolving landscape, the integration of Artificial Intelligence (AI) is transforming Vietnam’s banking and financial sectors, offering new avenues for efficiency and customer service. However, this paradigm shift faces challenges hindering its widespread implementation.

According to a 2020 survey by the World Economic Forum, 85% of financial organizations were already incorporating AI technologies into their operations. Dr. Võ Thị Hồng Diễm, a lecturer in blockchain-enabled business at RMIT University’s Business School, highlights the significant impact of diverse AI applications in the sector.

AI Applications in Finance

Intelligent chatbots and virtual assistants are leading the charge, understanding and addressing customer queries, providing personalized financial services, automating tasks, detecting fraudulent activities, assessing creditworthiness, and delivering automated customer support. This shift has witnessed remarkable growth, with 85% of financial organizations incorporating AI technologies in 2020, according to the World Economic Forum.

In line with global trends, prominent Vietnamese banks are investing in researching and implementing AI technologies. TPBank, for instance, has integrated face recognition into its LiveBank automatic banking channel, enhancing security and convenience. VietinBank utilizes kiosks with FaceID recognition to identify customers and forward requests to advisors.

Several other banks, including VietABank, Nam Á Bank, VPBank, Techcombank, VIB, and ACB, have embraced AI for functions such as customer support, asset management, security, fraud prevention, and analysis of peak season ATM withdrawals.

Challenges and Opportunities

Despite these advancements, most Vietnamese banks primarily deploy traditional rule-based AI, which excels in routine inquiries and simple transactions. Generative AI, a more adaptable next-generation technology, is less prevalent due to several challenges:

  1. Lack of AI Development Ecosystem: Vietnam is at an early stage compared to some other Asian countries, lacking a robust AI development ecosystem and supportive policies.
  2. High Cost and Skilled Labor Shortage: The high cost of AI and advanced machine learning, coupled with a shortage of skilled labor, hampers progress. The current supply of AI personnel in Vietnam only meets 10% of the domestic market’s demand.
  3. Data Challenges: Generative AI’s reliance on substantial amounts of high-quality data is impeded by data privacy and security regulations. Inaccuracies or biases in training data can lead to suboptimal outcomes.
  4. Infrastructure Limitations: Layered infrastructure poses a challenge, as generative AI heavily relies on databases. Limited access to bank data and confidential information hinders the performance of AI in crucial tasks.

The Path Forward

To unlock the full potential of AI in the banking sector, Vietnam must address these challenges. This includes the development of a large and high-quality data infrastructure, strategic investments in technology, and the nurturing of a supportive AI development ecosystem.

Dr. Diễm emphasizes that for AI integration to thrive, Vietnam needs substantial growth in its AI development ecosystem, supportive policies, and strategic investments. These steps will empower banks to stay competitive, prepared for emerging trends, and provide cutting-edge financial services to customers.

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