Building intelligent infrastructure for a truly connected economy
Cross-border payments have long carried the promise of something bigger than convenience. They imagine a more connected financial world—one where distance doesn’t delay progress, and borders don’t slow the movement of capital. As global commerce expands and digital economies accelerate, it becomes more urgent that we fully realize this vision and take advantage of the enormous benefits it affords.
But while we work towards this promise, we must manage complexities in getting there: fragmented systems, a patchwork of compliance requirements, and often, slow manual processes that can threaten to erode trust and efficiency.
It’s exactly here that agentic AI can have an impact. Not just by automating these manual processes, but by introducing intelligence and adaptability at the heart of payment infrastructure.
Co-founder & Chief Operating Officer, TerraPay.
Smarter Systems for a Faster, Fairer Flow of Funds
Agentic AI refers to systems capable of independent decision-making, learning, and acting within defined objectives. Unlike traditional automation, which follows predetermined rules, agentic AI can work autonomously, responding to new data or situations in real time. In the context of cross-border payments, that adaptability opens up a range of opportunities.
Consider the coordination involved in sending money between countries: a single transaction might pass through multiple partners, banking systems, currencies, and regulatory frameworks.
When everything works perfectly, the process feels seamless. But when something goes wrong—delays, failed compliance checks, technical errors—resolution typically requires human intervention. Logs must be pulled. Partners contacted. Systems checked.
Agentic AI has the potential to radically speed up that process.
Intelligent systems trained on payment corridors, transaction histories, and partner system behaviors can flag issues early, pinpoint the likely causes, and suggest fixes fast. Instead of starting every investigation from scratch, agents can work alongside AI models that have already done the legwork, making operations more responsive and far less dependent on time-consuming manual deep dives.
Integration Without the Bottleneck
Another long-standing friction point for cross-border payments enterprises is the challenge of integrating new partners. Every integration means studying APIs, aligning data structures, and ensuring compatibility. It’s a time-consuming process that slows down innovation and expansion.
Agentic AI can simplify this. By learning the patterns and structures behind common integration workflows, it can assist in parsing APIs, mapping connections, and reducing the manual overhead typically required. This results in faster partner onboarding, more agile ecosystems, and a much smoother path to scalability.
This also rebalances the cost-benefit analysis for smaller institutions or partners looking to join global networks. Lowering the technical barriers means broader access—and broader access strengthens the entire system.
Compliance That Moves at the Speed of AI
No discussion of payments, especially international ones – is complete without compliance. From sanctions screening to AML checks, compliance teams face growing pressure to review increasing volumes of alerts with limited time and resources. And in many cases, today’s systems still rely on rigid rulesets that generate large numbers of false positives, overwhelming reviewers.
Agentic AI offers a way to improve both speed and accuracy. These models can learn from human decisions over time, categorizing alerts more effectively, recognizing patterns that traditional systems miss, and escalating only when needed. Crucially, AI doesn’t need to act alone. A layered approach, where multiple AI agents validate each other’s conclusions – can build greater confidence and traceability into the decision-making process.
To be clear: this isn’t about removing humans from the loop. It’s about giving them better tools – augmenting expert judgment with analysis that is both faster and broader in scope.
Laying the Data Groundwork
Of course, none of this works without good data. Agentic AI, like any system, is only as strong as the information it’s trained on. And for many financial institutions, the data challenge is real: important insights are locked in silos, scattered across SaaS platforms, legacy systems, and poorly indexed databases.
To take full advantage of intelligent systems, businesses need to invest in the foundational work: structured, unified data repositories that make relevant information accessible and usable. That means not only cleaning the data, but also breaking down internal barriers to visibility, rethinking fragmented architectures in favor of shared intelligence layers.
This will also reshape how financial firms choose and deploy their tech stacks. Stitching together dozens of narrow SaaS platforms may no longer be sustainable in a world where AI needs a full picture to function effectively. The focus will likely move toward more integrated environments, purpose-built for intelligent orchestration.
Even in these environments, agentic AI isn’t a silver bullet, but it is a powerful lever. Used wisely, it can help build payment systems that are faster, more reliable, and more inclusive. It can reduce the time it takes to connect with a new market, resolve an issue, or adapt to a regulatory change. And as the technology matures, cost barriers will fall, accessibility will rise, and open-source alternatives will drive further innovation.
Ultimately, this isn’t just about smarter or faster transactions, it’s about making the financial infrastructure of the future more human in its outcomes: more responsive, more accessible, and more aligned with the needs of real people moving money across borders every day.
The infrastructure we build today will define the shape of tomorrow’s financial landscape. And with agentic AI in the mix, that landscape has the potential to be more open, more intelligent, and more connected than ever before.
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