According to a McKinsey report, GenAI has the potential to generate up to $340 billion annually for the banking industry, thanks to its ability to create new data and analyze information for more accurate predictions compared to traditional AI. This opens up numerous opportunities for banks to integrate this technology into their operations.
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Real-world applications of AI & GenAI in banking industry
Global
GenAI is being widely applied in advanced banking solutions such as customer experience personalization, risk management, and process optimization. Here are some notable applications:
- Personalizing customer service: Major banks like JPMorgan Chase and Citigroup are leveraging GenAI to tailor customer experiences, from product recommendations to financial advice (GuruFocus). This personalization helps build stronger customer relationships and improve service delivery.
- Personalized product recommendations: By analyzing customer behavior and transaction history, banks can offer customized financial products. KPMG reports that 68% of banking executives are planning to use GenAI to create personalized product recommendations and cross-selling opportunities, driving higher engagement and sales
- Intelligent automation: By integrating AI, intelligent automation systems efficiently handle repetitive tasks. For example, the Bank of New York Mellon, with over 230 years of history, has implemented 220+ bots to automate tasks, boosting efficiency and cutting operational costs. This shift enables the bank to focus on more strategic and customer-focused operations
- Risk management and security: GenAI is revolutionizing fraud detection. A European bank reported a 30% increase in fraud detection accuracy with AI-driven tools. Another regional bank saw a 40% reduction in compliance-related incidents thanks to automated transaction analysis. HSBC has also explored using GenAI to simulate various anti-money laundering (AML) strategies, enhancing its efforts to prevent financial crimes (Revvence).
Vietnam
Vietnamese banks have adopted AI in key areas, focusing on customer-centric services, banking operations, transactions, investment portfolio management, and regulatory compliance (Tap Chi Cong Thuong). Here are some notable applications:
- Chatbots: AI-powered chatbots are being widely used in Vietnamese banks to automate repetitive tasks like customer support and data collection. These bots handle routine inquiries, assist with transaction details, and guide customers through various banking processes. Notable implementations include:
- Vietcombank (VCB Digibot)
- VietinBank (supports iPay, eFAST)
- ACB (AI BOT)
- Intelligent Automation: Automating tasks such as account opening, transaction processing, and data verification. Key applications include:
- VietinBank: Reduced pledge loan processing time by 65%.
- HDBank: Increased transaction processing speed by 30 times.
- TPBank: Cut loan disbursement time by 60%.
- Risk analysis and management: AI is increasingly used by banks in Vietnam to analyze customer data, predict behavior, detect fraud, and optimize services. By leveraging machine learning and facial recognition technology, these banks are enhancing security and improving decision-making. Leading examples include:
- TPBank: Using facial recognition technology.
- Nam Á Bank: Employing smart trading robots.
Typical use cases of applying GenAI to banking operations
In addition to the applications mentioned above, GenAI has vast potential. Let’s explore other notable use cases that could shape the future.
Customer-Facing Use Cases:
- Virtual assistance: GenAI-powered chatbots provide human-like interactions, answering complex queries and personalizing recommendations for financial products while supporting customers 24/7
- Personalized services: AI enhances customer experiences by tailoring products and messages based on individual needs, boosting engagement and loyalty
Middle-Office Applications:
- Credit scoring and risk assessment: GenAI leverages historical and real-time data for precise credit evaluations and risk profiling, speeding up traditionally manual processes
- Fraud detection: AI algorithms continuously analyze transaction patterns, identify anomalies, and prevent fraud in real time
- Regulatory compliance: Automating compliance monitoring and reporting minimizes errors and enhances accuracy
Back-Office Applications:
- Document processing: GenAI automates tasks such as classification and data extraction from documents, improving efficiency and accuracy
- Loan management: Predictive analytics optimize loan servicing, reducing risks and streamlining routine tasks like payment reminders
- Dynamic contract generation: Automating contract creation and updates ensures compliance with the latest standards and reduces manual errors
Preparing for the integration of GenAI in banking operations in Vietnam
With the tremendous potential of GenAI, what do banks need to prepare in order to lead this digital transformation journey? Let’s explore!
Technology infrastructure
Mr. Doan Huu Hau, Director of Transformation and AI Services at FPT Digital, emphasizes: “For successful AI deployment, banks need to choose IT infrastructure that aligns with their financial capacity and level of AI adoption.” This infrastructure, particularly for tasks requiring high computing power like GPUs, is critical. Banks should also consider scalable and secure cloud platforms to manage large datasets and complex AI models. Ensuring compatibility with existing systems is crucial to avoid disruptions during integration.
HR & talent development
A significant challenge for banks adopting GenAI is the shortage of skilled personnel capable of effectively managing and operating these systems. According to EY, 55% of banking decision-makers report that insufficient internal expertise is a significant barrier to establishing dedicated GenAI teams in their organizations. To overcome this, banks must invest in training programs that equip their workforce with the necessary skills in AI technologies and data analysis, ensuring they can effectively deploy and manage AI systems.
Clear roadmap
Ms. Truong Minh Trang, FPT Digital consultant, recommends a six-step roadmap for effectively applying AI in banking. The first step is understanding AI and assessing the organization’s readiness in terms of technology infrastructure and human resources. Next, banks should identify key business areas, evaluate the potential for AI applications, and generate ideas. The following steps include assessing the value and feasibility of these ideas, executing the plans, and continuously monitoring AI models to ensure they are updated and refined.
Ms. Trang emphasizes that following this structured approach enables banks to focus on high-impact applications that offer quick results, which is essential in an environment full of opportunities and challenges. Given resource constraints, it is almost impossible for banks to implement everything at once.
Conclusion
GenAI offers immense potential for banks to enhance operations, improve customer experiences, and drive smarter decision-making. By investing in AI-driven solutions such as chatbots, intelligent automation, and risk management tools, banks can stay ahead in the digital transformation journey. With the right planning, they can capitalize on GenAI to shape the future of banking.
akaBot (FPT) is the operation optimization solution for enterprises based on the RPA (Robotic Process Automation) platform combined with Artificial Intelligence, Process Mining, OCR, Intelligent Document Processing, Machine Learning, Conversational AI, etc. Serving clients in 21+ countries, across 08 domains such as Banking & Finances, Retail, IT Services, Manufacturing, and Logistics…, akaBot is featured in “Voice of the Customer” for Robotics Process Automation” by Gartner Peer Insights, G2, and ranked as Top 6 Global RPA Platform by Software Reviews. akaBot also won the prestigious Stevie Award, The Asian Banker Award 2021, Everest Group’s RPA Products PEAK Matrix® 2023, etc.
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