AI in Treasury: A Smarter Way to Forecast, Not a Magic Fix
Published: January 07, 2025
AI enhances treasury forecasting by reducing errors and saving time, but it’s the expertise of treasury teams that turns data into actionable insights. Learn how to leverage AI for smarter FX strategies.
AI is often celebrated as a transformative technology, but it’s no replacement for critical thinking. For treasurers, AI’s real value lies in its ability to amplify human expertise, providing more precise forecasts while enabling strategic decision-making.
Treasury teams face a dual challenge: navigating volatile markets while managing limited resources. Outdated forecasting methods – from time-series analysis to reliance on subjective judgment – often fall short in delivering the accuracy treasurers require. These methods struggle to adapt to subtle trends, leading to costly errors and wasted time.
One common scenario involves forecasters being overly reliant on historical trends. This approach often misses emerging risks or opportunities that can impact strategic decisions. It also forces treasurers to spend valuable time compensating for systemic inaccuracies, diverting their focus from broader organisational goals.
AI as a partner, not a panacea
AI doesn’t replace human insight – it enhances it. By integrating diverse data sources, from within the company and outside economic indicators, AI equips treasury teams with forecasts that are dynamic and precise.
Even so, the forecast is only as good as the treasurer interpreting it.
Here’s what trained AI brings to the table:
- Dynamic Learning. AI continuously adapts to evolving market conditions, identifying patterns and trends that static models overlook.
- Efficiency Gains. Automation of repetitive tasks such as data aggregation frees up time for high-value activities.
- Strategic Alignment. By providing granular forecasts broken down by entity, currency, business units, trading partners – and any other level at which data is available – AI supports more informed hedging and risk-management decisions.
This granularity enables treasurers to anticipate risks and opportunities with greater accuracy, ensuring decisions are made with the most comprehensive insights at hand.
A salutary tale
Picture a global retail giant operating across 30-plus countries. With thin treasury resources, they’re forced to hire interns to consolidate data across spreadsheets extracting sales figures, procurement costs, and market trends. Each month, the team spends hundreds of hours manually adjusting forecasts, hoping to anticipate currency fluctuations.
When a geopolitical event causes unexpected currency volatility, their hedging strategy is disrupted by delays and discrepancies in the forecast. The interns scramble to update spreadsheets, but the lack of real-time insights leads to higher costs and exposure.
However, by adopting AI-driven forecasting the company can automate data consolidation and integrate external factors including market trends and policy changes. This reduces manual intervention and improves the accuracy of their projections. The treasury team can now focus on developing proactive strategies, aligning resources with their growth objectives instead of constant troubleshooting.
No substitute for human expertise
Our extensive research across multiple companies shows that AI consistently delivers more accurate forecasts. On average, AI reduces forecast errors by 50%. In some instances, companies saw their forecast errors drop from 90% to as low as 12%.
However, AI is not perfect. There were cases where AI forecasts performed similarly to manual methods over a full year. Even in these instances, the key advantage was the significant time savings achieved by automating tedious processes.
Crucially, when AI does not outperform manual forecasting, human expertise plays a vital role in bridging the gap. Treasury teams that pair AI insights with their market knowledge can refine outputs, ensuring more precise and actionable forecasts.
A balanced future for treasury
In summary, AI works best when paired with human intelligence. It eliminates inefficiencies and empowers treasurers to shift from reactive adjustments to proactive planning. Teams that embrace this balance can navigate complexity with confidence.
In conclusion, AI in treasury management isn’t about surrendering decision-making; it’s about enabling smarter decisions. As the technology evolves, its role as a partner to treasurers will only increase.