With sudden tariff hikes one day and unexpected currency dips the next, traditional reconciliation systems are struggling to keep up with today’s relentless unpredictability. It’s time for AI to help.
As Eddie Wen, global head of digital markets at J.P. Morgan, put it, “What distinguishes this year is the somewhat unexpected timing of volatility,” and that’s exactly why AI needs to be part of the solution.
There was a time when market volatility was largely driven by scheduled events, such as general elections, interest rate announcements, or non-farm payroll releases. But today, we’re seeing things shift overnight with little warning.
Sharper, more sudden fluctuations are being sparked not by the things we know are coming, but by the latest news headlines – particularly around the rapidly changing U.S. trade policy – and this unpredictability is triggering knee-jerk reactions across the market.
Looking at the past few months alone, we’ve seen the Chinese yuan fall to its weakest level in two months following Trump’s announcement of a 50% tariff on U.S. imports from China. We’ve also seen the US dollar drop nearly 10%, fueled partly by uncertainty around U.S. policies – like big spending plans and possible new tariffs – making investors nervous and less confident in the dollar. And recently, we’ve heard the World Bank predict global trade growth will be the slowest since 2008 – excluding recessions – again due to the effects of the US-led trade war.
Meanwhile, a recent J.P. Morgan traders survey also found that over half (51%) cited tariffs and inflation as the top market drivers in 2025 (up from just 27% last year), showing us just how much geopolitics, not just economics, is now steering the direction of global markets.
Where Traditional Reconciliation Falls Short
Trying to stay ahead of these quick-paced shifts and respond at speed has put financial institutions under increasing pressure – especially when it comes to making sure all their records match up.
This is where traditional reconciliation systems – originally built for more stable market conditions to bring order – are not only struggling to keep up, but are also adding to the chaos.
The downsides of manual checks and static, rule-based processes include being error-prone, time-consuming and lacking scalability, while they also struggle with complex data and require constant maintenance and upgrades. And this doesn’t even factor in the complexity of modern cross-border transactions, whereby different currencies, regulations and formats can cause data mismatches within traditional systems – such as payments referencing only part of an invoice number or unexpected discounts being applied.
Even automated rule-based systems, which have rigid structures requiring continuous configuration updates as each tariff adjustment or regulatory shift occurs, are flagging due to a lack of foresight.
Why It’s Time for AI to Step In
While market volatility shows no sign of settling, AI, specifically ML, does offer a solution in terms of how financial institutions handle the chaos.
For trade finance, some of the main benefits of AI-powered reconciliation include:
● Ability to recognise patterns: One of the main capabilities of ML models is that they can identify complex relationships between different data elements, as opposed to relying on fixed rules. This means that when a buyer truncates an invoice reference or applies an unexpected discount, AI can still identify the correct match by recognising patterns in the remaining data points – a benefit proving invaluable when reconciling transactions affected by tariff-related adjustments or partial payments.
● Scalable automation: Because AI can process new information instantly, it can both maintain up-to-date records and allow institutions to handle higher transaction volumes without increasing headcount.
● Smoother customer experience: By allowing institutions to confirm payments quicker, clients gain a clearer picture of their cash flow; a huge benefit when they’re dealing with trade delays or stretched payment terms.
● Improved risk detection: AI can spot unusual payment patterns that might signal fraud or compliance problems; something that’s especially helpful when you’re dealing with transactions across different countries and sets of rules. It can also flag potential reconciliation issues before they become a real problem, giving teams a chance to step in early and fix things before they escalate.
● Accuracy that improves over time: In the current trade environment, where payment patterns and documentation requirements are constantly evolving, accuracy is vital. As well as being able to identify anomalies before they cause errors and accurately match diverse data sources using pattern recognition, this accuracy improves over time by learning from each transaction and exception it processes.
Despite the clear benefits, many institutions are still cautious about adopting AI in trade finance. Concerns around data security, integration complexity and cost continue to surface, especially in an industry handling large volumes of sensitive, cross-border transactions.
But implementation is now becoming more practical and cost-efficient. Cloud-based platforms, for example, allow financial institutions to bring in invoice, payment and remittance data from their customers and automate three-way reconciliation, without needing extensive IT infrastructure investments.
While today’s solutions are secure, scalable and relatively easy to integrate, successful adoption still depends on having access to reliable historical data for training and the right level of human oversight to guide the system as it learns. With those pieces in place, many institutions are finding that AI-powered reconciliation can be rolled out in weeks, not months, often with minimal disruption.
It’s this ability to deliver fast, tangible results – even in unpredictable conditions where the only real certainty is to expect the unexpected – that makes AI such a powerful tool for trade finance.
Right now, it’s not so much a question of whether to adopt AI anymore, but how quickly financial institutions can make it happen.