AI agents could help Southeast Asian firms untangle cross-border payment costs

Many Southeast Asian businesses face challenges when selling and getting paid across borders. Merchants in Singapore source products from Vietnam, sell to Indonesian customers, work with logistics partners in Thailand, and settle invoices with a US-based platform. However, these transactions pass through a complex network of banks, card networks, payment providers, foreign exchange desks, and local clearing systems that rarely communicate smoothly.

This results in unpredictable fees, fluctuating exchange rates, varying settlement timelines, and a lack of real-time visibility into cash flow, making treasury management difficult for both large corporations and small to medium-sized enterprises.

The Sunrate and Mastercard report "Beyond Automation: Defining Agentic Global Payments" suggests that the future of payment technology will involve AI agents that can analyze changing conditions, weigh options, and recommend or execute the best course of action within predefined limits. Traditional automation relies on fixed rules, while agentic AI takes a more flexible and adaptive approach.

For instance, AI agents could identify the most cost-effective payment route, decide the best time to convert currencies, spot discrepancies between invoices and receipts, and flag exceptions that need human intervention.

One significant issue highlighted in the report is the "liquidity blind spot," which refers to the limited visibility finance teams have into where cash is located, its currency, and when it's needed. For large corporations, this can be a significant treasury challenge, while for startups and SMEs, it can be a critical factor in their survival.

A Southeast Asian e-commerce exporter, for example, may receive payments in US dollars, pay suppliers in Chinese yuan, settle logistics costs in Thai baht, and handle payroll in Indonesian rupiah. If the company converts currencies too early, it risks losing out if exchange rates move favorably. Conversely, delaying conversions can lead to higher spreads or cash shortages.

Traditional methods like end-of-day reports and manual spreadsheets often provide outdated information, forcing finance teams to react rather than proactively manage risk. AI agents could help address this issue by continuously monitoring foreign exchange trends and liquidity needs, optimizing conversion timing based on real-time data, and reducing the lag in managing cash flow.

The Asia Pacific region offers an ideal testing ground for this AI-powered payment model due to its rapidly growing trade and payment flows and complex, fragmented payment networks. Commercial card transaction volumes in sectors like travel are expected to grow by 28% annually from 2023 to 2025. Travel agencies, hotel operators, airlines, and corporate travel platforms often operate across multiple markets, currencies, and settlement arrangements, making cross-border payments particularly challenging.

The same complexity is seen in other sectors crucial to Southeast Asia's startup economy, such as B2B marketplaces, logistics, SaaS, gaming, creator platforms, and cross-border e-commerce. As these businesses expand to new markets, their finance operations become increasingly complex, and static payment setups become less effective due to frequent changes in fees, failure rates, exchange rates, and local payment systems.