Founded in 1984 and employing over 42,000 people across more than 60 locations, ASML Holding N.V. develops, produces, markets, sells and services advanced semiconductor equipment systems for chipmakers.
The challenge
ASML sources components for its chip manufacturing equipment from a sprawling worldwide network of suppliers. Some components are sourced from the United States and paid in US dollars, yet ASML sells its systems in euros and is exposed to EUR/USD exchange rate fluctuations. To mitigate the effect on its P&L, the company runs a purchase hedging programme but was struggling to accurately forecast US dollar inflows. Manual and labour-intensive, excel heavy processes were prone to error and the accuracy of the forecast was low at 70%.
The solution
ASML implemented a new AI powered material intake forecast model to increase the effectiveness and efficiency of its purchase hedging programme. The cornerstone of the programme is the forecast of expected US dollar material intake.
The internally developed new forecast is based on a fully automated AI machine learning model that recognises patterns and trends in historic actuals and uses those to predict future intake. With every new month the model becomes smarter and improves the forecast accuracy even further. As a result, the forecast accuracy increased from 70% to 96% making the hedging programme much more effective.
The AI solution provides the forecasted USD intake without manual interference. It recognises patterns and trends, learns every month and is scalable vertically and horizontally.
“Winning the award for Best Foreign Exchange Solution is an absolute honour and we hope it will inspire others to think about practical use cases for AI in their work.”
Best practice and innovation
The project is also an example of close collaboration between the two ASML teams – treasury and data science.
This particular AI model is based on a free open-source Python algorithm that was further optimised to ASML’s use case. That makes AI solutions easily accessible, scalable and widely usable for people and companies. The algorithm drew data insights, allowing ASML treasury to spend less time on manual data processing and increase time spent on value adding activities.
“We decided to share this solution with the broader community to show that AI applications are not only for the happy few,” explains Daria Severina, Director Treasury.
Key benefits
Cost savings.
Headcount savings.
Process efficiencies.
Increased automation.
Risk mitigated.
Improved visibility.
Errors reduced.
Manual intervention reduced.
Future-proof solution.
Exceptional implementation (budget/time).
Improved key performance indicator (KPI) metrics.
The Adam Smith Awards are the industry benchmark for best practice and innovation in corporate treasury. The 2024 awards attracted 389 nominations. To find out more please visit treasurytoday.com/adam-smith-awards
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