The financial industry is moving quickly from generative AI experimentation toward autonomous agents that can execute tasks, make recommendations, and eventually transact on behalf of customers. In a panel discussion titled “Autonomous Finance: From Generative AI to AI Agents in Banking,” moderator Anndy Lian, bestselling author of Web4: The Age of Autonomous Intelligence, led panelists David B. Wang of HeyMax, Adriel Wong of TRM Labs, and Ankit Lathigara of Nasdaq through the opportunities, bottlenecks, and human questions shaping this transition.
Lian opened with the core question: “What is the single biggest opportunity that AI agents create for banking in the next three to five years?” For Wang, the answer is hyper-personalization. Banks have long talked about customer segments, but AI can finally deliver at the individual level. “Where AI becomes incredibly powerful is to actually bring that to the actual individualized level… and truly responding to each individual’s needs based on their pattern behavior,” Wang said. He argued that banks sit on “a ton of user data” — lifestyle, purchasing behavior, and loyalty patterns — that can be turned into far more tailored engagement.
Wong approached the opportunity from the compliance and operations side. While much attention goes to front-end customer experience, he sees the greatest near-term value in back-end efficiency. “A lot of that value capture actually is in the back end,” Wong said. He pointed to DBS’s reported $1 billion in economic value generated largely through AI-driven process improvements, such as automating credit memo workflows for relationship managers. For Wong, AI’s ability to compress timelines and reduce friction is where banks can generate immediate economic value.
Lathigara agreed, noting that 70–80% of banking costs sit in operations. He described AI as a way to clean up fragmented legacy systems and make every channel more intelligent. “AI is going to be a big enabler or I would say accelerator in the next 12 to 18 months,” he said. Beyond cost reduction, he sees AI helping banks rethink how they use human capital and how they deliver experience, much like Apple stores deliver a differentiated customer journey.
But the panel was equally clear about the barriers. Lathigara identified trust as the fundamental bottleneck. “The trust is a backbone of how you’re going to automate,” he said, explaining that humans must be able to trust automated outcomes without double- or triple-checking every decision. That requires explainability, step-by-step reasoning, and comprehensive compliance functions built into AI systems.
Wong doubled down on the compliance challenge. “Many of these operational as well as compliance decisions have to be very stringently audited,” he said. In regulated environments, black-box AI is not enough. He also stressed that accountability cannot be delegated to a machine. “I don’t think there’s any jurisdiction today in the world that allows you to designate an AI agent as your MLR,” Wong said, referring to the money laundering reporting officer. For banks and fintechs, the human must remain accountable for regulatory reporting and legal liability.
Wang added that internal culture and interoperability remain practical obstacles. Many banks are still intimidated by AI, and adoption often depends on top-down guidance. He also noted that while blockchain and GenAI adoption are growing, interoperability between systems is still weak. His advice was not to avoid AI, but to find partners and test solutions in sandbox environments. “Don’t let that be a hindrance to innovation,” he urged.
On the role of humans, Wang was pragmatic. “AI is not the be all and end all,” he said. “It is at the end of the day a tool.” His advice to bankers: “Don’t let AI run you. You should run the AI.” Wong agreed but warned that “human in the loop” can become a slippery slope if it reintroduces all the friction AI was meant to remove. The real question is which tasks can be safely delegated and which must retain human accountability.
Lathigara offered a four-quadrant view of the financial ecosystem: technology firms, fintechs, large regulated institutions, and regulators. Each will move at a different speed. High-risk compliance and finance functions will still require human oversight, while lower-risk, high-touch tasks can be automated.
Finally, Lian asked how cryptocurrency and stablecoins fit into the autonomous finance era. Wang sees stablecoins primarily as an interbank or internal bank solution. “I personally see cryptocurrency more as an interbank solution… less so of a consumer adoption side,” he said. Wong sees stronger retail use cases in cross-border payments and remittances, especially where fiat rails are slow. “The agent is the orchestration layer but you still fundamentally need a payment rail,” Wong said, noting that blockchains already support atomic settlement. Lathigara added that crypto has pushed traditional exchanges toward 24/7 operations and that AI could turn crypto into “programmable money.” But he cautioned: “Too much of transparency is also not healthy at a point in time.”
Lian closed by looking ahead: “Autonomous intelligence is going to change everything from programmable money, crypto, stablecoin to the traditional finance routes.” The panel’s message was clear: the future of banking will be AI-driven, but it must be built on trust, explainability, and human accountability.
Anndy Lian is an early blockchain adopter and experienced serial entrepreneur who is known for his work in the government sector. He is a best selling book author- “NFT: From Zero to Hero” and “Blockchain Revolution 2030”.
Currently, he is appointed as the Chief Digital Advisor at Mongolia Productivity Organization, championing national digitization. Prior to his current appointments, he was the Chairman of BigONE Exchange, a global top 30 ranked crypto spot exchange and was also the Advisory Board Member for Hyundai DAC, the blockchain arm of South Korea’s largest car manufacturer Hyundai Motor Group. Lian played a pivotal role as the Blockchain Advisor for Asian Productivity Organisation (APO), an intergovernmental organization committed to improving productivity in the Asia-Pacific region.
An avid supporter of incubating start-ups, Anndy has also been a private investor for the past eight years. With a growth investment mindset, Anndy strategically demonstrates this in the companies he chooses to be involved with. He believes that what he is doing through blockchain technology currently will revolutionise and redefine traditional businesses. He also believes that the blockchain industry has to be “redecentralised”.
