AI Application In Banking

AI is reshaping traditional banking services, making them more efficient, secure, and customer-centric. As we move toward 2025 and beyond, the role of AI in banking is set to expand even further, driving innovation and ensuring the industry’s competitive edge in an increasingly digital landscape.

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Leading the digital transformation era with key technology trends in banking

Blockchain

This technology allows transactions to be recorded in a distributed ledger, significantly reducing the risks of fraud and human error. Thanks to blockchain’s immutable and transparent nature, banks can accurately and swiftly verify and track transactions. Juniper Research has found that blockchain deployments will enable banks to save more than $27 billion by the end of 2030. This underscores blockchain as a critical technological trend for the banking sector to consider during digital transformation.

Cloud computing

The capabilities of cloud computing, particularly its ability to store and process large volumes of data, enable banks to access, manage, and analyze customer information quickly and efficiently. This technological advancement enhances operational efficiency and allows banks to deliver personalized services to customers, improving overall customer satisfaction.

A report from IDC (International Data Corporation) reveals that by 2020, 57% of the banking sector had successfully implemented digital banking and transitioned to the cloud. Additionally, 40% of banks indicated plans to shift to a hybrid cloud environment within the next 12 to 24 months. This shows the trends in applying cloud computing within banking businesses.

AI & machine learning

AI in mobile app

One major development in banking is the rapid adoption of cashless payment services nationwide. Cashless payments are growing over 50% annually, with mobile transactions rising by more than 100% each year and online banking via the Internet increasing at a similar pace (Binhphuoc.gov). As customers demand seamless access to financial services on their smartphones, banks are investing in AI to enhance mobile app experiences. AI enables personalized services, streamlines onboarding through facial and voice recognition, and improves the experience. In the future, AI-driven mobile apps will be central to banking, making cashless payments the new standard in finance (Financial IT).

AI for financial security

With the rise of cyberattacks like phishing, malware, and DDoS attacks, hackers increasingly exploit vulnerabilities in banking systems to steal customer assets. AI’s machine learning algorithms are crucial in identifying unusual transaction patterns, such as large transactions from unfamiliar locations or multiple small transactions in quick succession. Furthermore, AI analyzes natural language in customer service calls, detecting fraudulent interactions. By automating fraud detection processes, AI enables banks to respond swiftly to protect customer assets, significantly reducing the time required to investigate threats and minimizing disruptions for genuine customers.

Use case of AI in banking

With the increasing trends in AI, let’s delve deeper into specific use cases to illustrate how these technologies are being implemented in the banking sector:

Facial and voice recognition: AI can identify customers’ faces or voices and verify their identities, making transactions and consultations more convenient and secure.

Analysis of big and complex data: AI analyzes large and complex datasets to predict customer behavior, needs, and risks, helping to provide more suitable and optimized products and services.

Text summarization: AI can summarize texts related to banking, such as reports, contracts, regulations, etc., highlighting key information to save time and enhance efficiency.

Process management support for banks: AI can automate banking operations, such as complaint management, risk management, customer management, database management, etc., leading to cost reduction, increased productivity, and accuracy.

CRM, marketing & customer support: AI can enhance customer interaction and engagement using tools like chatbots, virtual assistants, smart emails, etc., providing timely and personalized information, advice, and solutions.

Advice from professionals in banking AI application

Define goals

According to the State Bank of Vietnam (SBV)’s Deputy Governor Nguyen Kim Anh, to successfully adapt to the “new normal,” banks must prioritize digital transformation by adopting new technologies and flexible business models. For these transformation efforts to be practical and produce positive results that benefit the entire industry, it is essential to define goals clearly. This clarity allows for developing a roadmap that outlines appropriate solutions and tasks, ensuring smooth coordination and unified implementation among relevant units within the banking sector.

Adoption with people

Yoky Matsuoka, recognized as one of the top 20 AI experts, entrepreneurs, and scientists in Forbes’ annual 50 Over 50 list, emphasizes the importance of human involvement in technology implementation: “AI sounds great, but we need to involve people in implementing this technology. We build these tools for people to use.” The success of AI applications depends significantly on active engagement from both employees and customers. Users are less likely to utilize these tools if they feel uncomfortable with the technology or are unaware of its limitations.

To increase successful AI adoption, banks must prioritize user-centric design, provide comprehensive training, and cultivate a culture of innovation and feedback. Ultimately, the effectiveness of AI in banking hinges on how well individuals adapt to and engage with these innovations, enhancing operational efficiency and improving customer experiences.

Collaborating with a technology company

To keep pace with technological trends, banks should pursue strategic partnerships with major tech firms to optimize the integration of AI into their operations. According to Nguyen Gia Vu, the Director of Digital & Technology, businesses should not simply chase AI trends. Instead, they must focus on specific challenges and identify targeted solutions where AI can provide support. He advises that companies should not attempt to navigate this landscape alone; rather, they should seek partnerships with organizations that have successfully implemented similar solutions.

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Conclusion

AI’s integration into banking is truly transformative. Banks must focus on clear goal-setting, user-centered design, and strategic partnerships with technology firms to fully harness its benefits. Ultimately, effectively implementing AI will enhance operational excellence while building greater customer trust and satisfaction.

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