That’s the situation playing out across today’s uncertain times, as traditionally behind-the-scenes enablers like trade finance, supply chain security and payments automation are becoming growth engines for firms seeking to navigate the ongoing and volatile macro environment.
Once regarded as a set of complex, paper-laden processes handled by banks and back-office teams, trade finance in particular has become a frontline concern for global businesses navigating volatility. Access to liquidity and risk mitigation can tilt the scales for global businesses facing tight monetary policies, geopolitical tensions and tariff-induced supply chain fragilities.
Roughly 80-90% of world trade depends on some form of financing, whether through credit guarantees, export insurance or bank intermediation. Its essential purpose is straightforward: to bridge the trust gap between an exporter in one country and an importer in another. By guaranteeing payment and delivery, trade finance enables goods to move despite the uncertainty that defines cross-border transactions.
And while the narrative around trade finance transformation has long emphasized efficiency: reduce manual work, cut processing costs and free up staff for higher-value tasks; firms are unlocking incremental value by leveraging trade finance as a mechanism for both freeing liquidity and derisking global commerce.
They’re also getting a little help along the way from a distinctly 21st century innovation: artificial intelligence (AI).
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The Legacy of Paper and the Cost of Delay
For decades, trade finance has lagged behind other areas of financial innovation. Bills of lading passed through couriers, letters of credit crawled through manual approvals and invoice financing was riddled with delays and opaque fees. The persistence of these manual processes has long been tolerated as the cost of doing business across borders.
These shortcomings matter more than ever in today’s context, where companies can no longer afford the drag.
Delays in financing now risk derailing entire supply chains. Payment uncertainty erodes trust between buyers and suppliers. And manual processes leave companies exposed to fraud schemes that have become more sophisticated and global in scope. Automation has emerged as one of the most viable paths to keep pace with the speed and complexity of today’s trade flows.
“The reality is that the world is moving way faster than most companies can keep up pace with,” Wendy Tapia, head of product, receivables at FIS, told PYMNTS in an interview posted Sept. 10. “Because of legacy systems, there are still a lot of organizations that are stuck in heavily manual processes, very fragmented systems. Without realizing it, they are limiting their agility and ability to scale.”
The time to cash benchmark is especially acute for businesses selling internationally, where settlement cycles can extend by weeks and errors multiply across currencies and jurisdictions.
As PYMNTS Intelligence data in the 2025 Certainty Project reveals, escalating trade tensions marked by the recent imposition of tariffs have introduced a wave of uncertainty across various sectors, notably impacting mid-sized companies.
Read more: How CFOs Can Manage for Today’s Supply Chain Choke Points
Enter Artificial Intelligence
For much of modern economic history, growth has been orchestrated from the top down, with governments and central banks setting the conditions. Trade finance has been treated as plumbing: necessary, but not transformative.
The integration of AI challenges that logic. When liquidity can be unlocked through smarter risk models and digital guarantees, growth becomes more decentralized and adaptive. Instead of waiting for a stimulus package or interest rate cut, firms can tap into global capital flows on their own terms. This could prove especially valuable in an era of multipolar geopolitics, where coordination among major economies is weakening.
AI’s first impact is in risk assessment. Traditional models rely heavily on financial statements, trade histories and often subjective judgments by banks. AI-driven platforms, by contrast, can ingest vast streams of structured and unstructured data such as shipping manifests, satellite imagery, commodity price fluctuations and even news sentiment to assess the creditworthiness of a counterparty in real time.
This not only accelerates the decision-making process but also expands the pool of firms that can be evaluated, particularly smaller companies that lack conventional credit histories.
At the same time, process automation is finally attacking the paper-heavy nature of trade finance. Natural language processing and computer vision tools can extract, verify and reconcile information from bills of lading, letters of credit and customs filings. What once took weeks of manual handling can now be completed in hours, cutting costs and freeing up working capital faster.
And of course, AI has transformed fraud detection. Trade finance has historically been plagued by forged documents and duplicate financing, where the same shipment is used to secure multiple loans. Machine learning models trained on patterns of anomalies across billions of transactions can flag suspicious behavior instantly, reducing both losses for lenders and systemic risk for markets.
Still, this is not a linear transformation. Legacy systems remain entrenched, particularly among large banks wary of compliance risks. Paper-based documentation still dominates in many trade corridors. But momentum is shifting. The pandemic accelerated digitization, geopolitical fragmentation has underscored the need for resilience and advances in AI have lowered the technical barriers.
Click here to register for the upcoming PYMNTS 2025 B2B event, “B2B.AI: The Architecture of Intelligent Money Movement,” taking place Oct. 6-31.
