AI Agents Are Entering Finance — UOB Sees Autonomous Banking Taking Shape

SINGAPORE — Artificial intelligence agents are expected to play an increasingly important role in finance, but their adoption will happen gradually, beginning with simple and tightly controlled tasks before moving into more complex financial decisions, according to a new report by United Overseas Bank (UOB).

Released in October 2026, the report gathered insights from eight respondents across the payments, infrastructure and digital asset sectors, representing organisations including Bluwhale, Eigenteam, Kasu Finance, NetMind.AI, OKX, Polyhedra Network, Transak and Velo Labs.

Experts expect agentic finance to develop in stages as financial institutions address major concerns surrounding identity, accountability, interoperability and governance.

Machine-to-Machine Payments Could Lead

Over the next three years, AI agents are expected to gain traction first in financial activities where rules are clearly defined and outcomes can be easily measured. Machine-to-machine payments are viewed as one of the strongest early use cases. AI agents could automatically pay for computing resources, data services, APIs and other digital services without requiring human intervention for every transaction.

These payments are considered suitable for automation because they tend to be repetitive, structured and governed by predetermined rules. Enterprise applications could follow.

By around 2027, AI agents could increasingly support areas such as treasury management, procurement, invoice processing, reconciliation and recurring cross-border payments.

Consumer adoption, however, is expected to take longer.

Experts believe consumer-facing AI agents could begin handling tightly controlled, relatively low-risk activities from around 2029, including budgeting, cash-flow management and predefined savings or investment mandates.

More sensitive applications such as autonomous credit decision-making may not begin emerging until around 2031, reflecting concerns over liability, governance and responsibility for financial losses.

Three Major Barriers Remain

Despite growing interest, three major challenges continue to stand in the way of large-scale agentic finance adoption. The first is liability. If an autonomous AI agent makes a payment that causes a financial loss, responsibility could potentially fall on the customer, financial institution, AI software provider or payment platform.

The second challenge is agent identity. Banks have established systems for verifying people and companies, but there is still no widely accepted framework for verifying autonomous software acting across different financial institutions and jurisdictions.

The third issue is interoperability. AI agents will need to operate across different payment systems, asset classes, regulatory environments and liquidity pools while ensuring transactions are compliant and properly settled. Until these challenges are resolved, adoption is expected to remain largely within controlled environments.

Southeast Asia Shows Growing Confidence in AI

Consumer attitudes suggest Southeast Asia could nevertheless become an important market for agentic AI. According to figures cited in the report, 69% of Southeast Asian shoppers use AI when comparing complex purchases such as electronics, while 93% trust AI somewhere in their purchasing journey.

More significantly, 75% of consumers are willing to allow AI agents to autonomously search for the best prices and complete purchases on their behalf.

Meanwhile, 62% said they trust AI tools more today than they did a year ago.

AI is already being deployed across digital financial services for customer acquisition, credit assessment and fraud detection, including efforts to reach first-time and unbanked borrowers.

UOB's report suggests the next phase will not involve handing complete control of people's finances to AI overnight. Instead, financial autonomy is expected to expand gradually — starting with predictable payments and enterprise workflows before moving towards consumer finance and, eventually, higher-risk financial decisions.