Page 496 - ISC PROCEEDINGS 21.4

MBBank – The "Digital Ecosystem Giant"
MBBank has undergone a robust transition from a traditional commercial bank to a
digital financial group, aggressively integrating AI across multiple operational facets. The
institution consistently ranks among the elite group of banks generating billion-dollar
profits. AI enables MB to manage a massive customer base of approximately 33 million
individuals while maintaining minimal operational overhead (MB, 2025). By integrating AI
into the MBBank App, the bank has sustained a Current Account Savings Account (CASA)
ratio among the market's highest—at approximately 37-40%—providing a substantial
source of low-cost funding (MB, 2024). Furthermore, its AI-driven credit scoring system
facilitates instant overdraft approvals within a single minute, acting as a powerful catalyst
for the rapid growth of its consumer lending segment."Techcombank – "Data as an Asset.
Techcombank prioritizes a data-centric strategy to optimize value from its premium
customer segments. AI facilitates the precise analysis of investment patterns, driving
significant growth in bancassurance and securities revenue (via TCBS). Advanced AI
frameworks enable the bank to maintain a remarkably low non-performing loan (NPL)
ratio—typically below 1%—despite substantial exposure to real estate and corporate
bonds. Additionally, the transition to cloud-based infrastructure empowers real-time data
analytics, resulting in a two-to-threefold increase in cross-selling efficiency.
Vietnam International Bank (VIB) – "The King of Retail and Credit Cards"
VIB serves as a prime example of leveraging AI to dominate a niche market segment.
The bank leads the market in credit card growth rates. Its 100% online AI-powered card
approval technology has triggered a surge in new card issuances. Remarkably, over 90%
of VIB's profit is derived from the retail segment—the highest ratio in the market (VIB,
2023).
VPBank – "Dominating Consumer Credit"
VPBank utilizes Artificial Intelligence to address the dual challenges of scale and risk
within the mass-market segment. AI enables both VPBank and its subsidiary, FE Credit, to
process tens of thousands of loan applications daily without necessitating a massive
workforce. Furthermore, AI facilitates automated debt classification and determines the
most effective collection strategies, thereby optimizing debt management costs. The
prevalence of automated approval systems in retail lending has been instrumental in
helping VPBank maintain its leadership position in the private credit market.
Summary: The adoption of AI has created a "competitive barrier" in terms of
efficiency for the aforementioned banks compared to their slower-moving peers. The
business results clearly demonstrate that while operating costs decrease, profit margins
and customer experience consistently improve.
3.2.2. Challenges for AI-driven banks in Vietnam
The implementation of AI at banks such as TPBank, MB, Techcombank, VIB, and
VPBank has not only yielded "sweet fruit" in terms of revenue but has also confronted
them with existential challenges. These barriers are far more rigorous than those
encountered during conventional digital transformation.
Data Challenges: Despite possessing vast data repositories, ensuring data quality
and synchronization remains a significant hurdle for financial institutions. Customer
information is often fragmented across disparate legacy systems, preventing AI from
achieving the holistic view necessary for accurate forecasting. Banks must allocate
substantial budgets for data cleansing; to mitigate the risk of biased AI decision-making—
such as erroneous loan rejections—institutions face immense costs in cleaning and

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