Closing the Case for Taking the Open-Source Route at ASML

Identifying company-specific use cases for AI solutions, rather than trying to “reinvent ChatGPT”, is the cornerstone of a successful project that could save time and lower FX risks. Here, Rick Schreurs, Team Lead, Treasury Front Office, ASML, offers insight into the company’s award-winning FX exposure forecasting tool.

The rapid adoption of AI across finance is changing the game for organisations, not least for treasurers who are eagerly eyeing its potential for revolutionising activities such as cash and exposure forecasting, risk management, and fraud detection.

While it is still early days for this particular revolution, many organisations have started engaging with AI internally and through third parties such as their banks. As they do so, one of the most challenging topics for them will be how they formalise their processes for developing and implementing the technology more broadly in a coherent, controlled fashion across the organisation.

A successful AI-driven project undertaken by the treasury at ASML, one of the world’s leading suppliers of photolithography machines used to produce computer chips, illustrates the impact in-house expertise can have in implementing the technology. The project, the winner of the Dutch Association of Corporate Treasurers’ (DACT’s) 2023 Treasury Award, sought to improve the company’s FX exposure forecasting with the help of AI.

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