The Thai financial services industry stands at a crossroads where rapid technological advancements are reshaping customer expectations, regulatory landscapes and competitive pressures. Banks must embrace innovation, not as an option but as an imperative, to remain relevant and resilient. At the TAB Global Thailand CXO Dialogue 2025, senior banking leaders, technology experts, and industry specialists convened to explore how financial institutions can overcome inertia and drive meaningful transformation. Discussions revolved around four key themes: the art of speed and adaptability, reinventing collaboration, creating a seamless boundary-less experience and overcoming inertia. Through candid exchanges and real-world case studies, participants shared insights on the role of artificial intelligence (AI), cloud computing and agile transformation in future-proofing banking operations. The art of speed and adaptability as a competitive differentiator Speed and adaptability define success in the digital era, and AI is proving to be a key enabler. Prawit Wongpanngam, head of data management at Ascend Money explained how AI is embedded across the operations of financial platforms, from fraud detection and credit scoring to customer service automation. Every interaction—from clicks on the app to customer service chat responses—is powered by AI, enabling real-time responsiveness and giving such fintech players an agility edge over traditional banks. Pratheep Kamath, business analytics head at UOB Thailand, noted that UOB’s Citi acquisition required them to rapidly deploy AI-powered personalisation engines. This enabled the bank to seamlessly onboard millions of new customers while also enhancing fraud detection and customer service automation. Thanavadee Rewatbawornwong, business investment head at Kasikorn Vision, highlighted how KBank’s overseas expansion into Vietnam required rapid adaptation to biometric authentication regulations. The urgency of compliance forced the bank to accelerate AI-driven identity verification solutions—a testament to how external pressures can drive AI adoption. Cloud as an enabler of speed Cloud technology has become a cornerstone of digital transformation, allowing banks to scale rapidly and innovate faster. Niall Reilly, strategic sales lead, ASEAN, AWS shared how Techcombank Securities in Vietnam implemented AI-powered stock analysis models in just eight weeks by leveraging AWS’s Bedrock platform. The result? Higher engagement and retention rates. This demonstrated how cloud platforms reduce development cycles, enabling rapid AI deployment across financial institutions. However, Apinya Chainapong, assistant managing director at Kasikorn Business Technology Group (KBTG), responded to a question from Chaiyarit Anuchitworawong, senior executive vice president, and group head of human resources at Bangkok Bank, about the explainability of AI, urging caution. She warned that not all AI models are suited for banking, and reliance on generative AI (GenAI) without proper safeguards could expose banks to compliance and ethical risks. She advocated for responsible use of AI, which guides decision-making through structured questioning rather than simply providing automated answers. Reinventing collaboration between business and technology One of the biggest roadblocks to innovation is the separation of business and technology teams. Esarawadee Chivasiripalungkorn, head of strategy at Bangkok Bank, explained how this division results in misaligned priorities: technology teams focus on stability and efficiency, while business teams push for growth and revenue. The result? Slow decision-making and fragmented innovation efforts. Piyadanai Arntong, senior lead manager of data scientist manager at Ascend Money shared how AI can bridge this divide. Its AI-powered customer decisioning engine enables real-time recommendations across multiple channels, bringing business and technology closer by automating customer interaction workflows. Accelerating application development and modernising legacy systems A significant breakthrough in banking transformation is the use of AI-powered workflows to streamline development and replace legacy systems. Jonathan Tanner,senior director, industry principal financial services and insurance, Asia Pacific at Pegasystems highlighted how Pega’s GenAI blueprint capability is transforming application development cycles by allowing teams to describe a problem, generate a workflow blueprint and move seamlessly into development. He shared an example from ANZ Bank in Australia, which leveraged this AI-powered approach to build and deploy a fraud and scam management application in just three months. "The ability to describe the problem, input a few parameters and have an AI-generated blueprint that can go straight into development is a game-changer," he explained. Meanwhile, Commonwealth Bank of Australia (CBA) implemented Pega’s customer decision hub across its customer engagement channels, initially piloting it in a single branch before scaling it nationwide. CBA also built an AI Factory with AWS to deploy large language models, optimise operational costs and accelerate product development cycles. Creating a seamless, boundary-less experience The future of banking lies in frictionless experiences that unify customer, employee and partner interactions. Manita Tantipetcharaporn, head of analytics at Ascend Money, emphasised that a seamless experience requires AI-driven personalisation at every touchpoint. Anjul Ray, FSI partner leader at AWS, highlighted how Krungthai Bank built a centralised data platform, boosting cash management efficiency by 60%. DBS, meanwhile, leveraged AWS and GenAI to create hyper-personalised small and medium-sized enterprise (SME) banking services that integrate tokenised SME data, buyer-seller interactions and marketing insights, delivering more tailored recommendations. Overcoming inertia from incremental change to bold transformation During the final phase of the discussion, Tanner challenged the assumption that speed alone is the key to AI adoption. He argued that while many banks rush toward large-scale AI transformations, a gradual, trust-building approach is often more effective. "Speed alone is not the answer. Trust takes time to build, and AI implementation should be an iterative process rather than a one-time revolution," he said. Tanner who had earlier introduced "Socratic AI", explained that AI should guide decision-making through critical questioning rather than simply providing outputs. He referenced Pega’s internal training courses, which use AI-driven Socratic questioning to improve learning outcomes. Chainapong reinforced this point, warning against blind adoption of GenAI and stressing the importance of explainability and human oversight in AI deployment. AI literacy as the future of banking One of the biggest challenges banks face is ensuring employees have the right skills to work alongside AI. Euquin Tan, associate director of Accenture stressed that AI adoption is not just about automation but about equipping employees with AI literacy, enabling them to interpret AI-generated insights responsibly. The TAB Global Thailand CXO Dialogue 2025 made one thing clear: the future of banking will be defined by those who move fast, break down silos and reimagine customer engagement. Tanner summarised that AI implementation is not about speed alone, but about sustainable transformation. Trust takes time, and banks that approach AI adoption incrementally yet boldly will ultimately win the race. The journey ahead requires bold action. Speed is no longer a differentiator—it is a prerequisite for survival.
