Summary
Fintech executives across Asia-Pacific are highlighting three converging trends that represent a structural shift in fintech infrastructure: agentic commerce (AI agents initiating and completing transactions), cross-border payment interoperability (connecting fragmented real-time payment systems), and AI cost governance (managing AI as a material operating expense). These trends together suggest that the next phase of fintech innovation will be about infrastructure that is intelligent, interoperable, and cost-governable.
Key Points
- Agentic commerce: AI agents are moving from assisting consumers (recommendations, discovery) to taking actions on their behalf (initiating transactions, completing purchases). This requires financial infrastructure that can handle machine-to-machine payments — fundamentally different from human-centric checkout flows. Authentication, authorization, and transparency requirements change when the "customer" is an AI agent.
- APAC fragmentation challenge: The region has some of the world's most advanced real-time payment systems (UPI in India, PayNow in Singapore, PromptPay in Thailand, DuitNow in Malaysia) but they operate in silos. Agentic commerce requires interoperability across these systems — an AI agent needs to pay a Thai merchant from an Indian account seamlessly.
- Cross-border interoperability: Arun Kini (Finastra): "APAC's payment future will not be defined by uniformity, but by interoperability." The opportunity is connecting fragmented real-time systems across borders. As real-time payments and atomic settlement become the norm, legacy infrastructure must modernize.
- AI cost governance: Damien Passavent (Aspire): AI has shifted from experimental spend to a material operating cost. Businesses are adopting multiple AI models for different tasks, creating cost complexity. Unlike traditional software, AI costs fluctuate with usage, making forecasting difficult.
- Three CFO priorities for AI: (1) Build visibility before reducing costs — understand which teams, workflows, or agents drive AI spend. (2) Define value before measuring ROI — productivity gains alone aren't enough; the real return comes from AI capabilities that can be trusted, scaled, and reused. (3) Protect an experimentation budget — demanding immediate returns risks discouraging the learning needed to identify high-value use cases.
- Infrastructure implications: The fintech companies that solve the agentic commerce infrastructure challenge — connecting global capabilities with deep local payment infrastructure — will play a critical role in determining how quickly agentic commerce moves from emerging trend to trusted, scalable reality.