The Dutch Association of Corporate Treasurers (DACT) is excited to announce the first edition of its contest to reward the best student dissertation (essay or thesis) on corporate finance and treasury topics. This contest aims to promote the treasury profession by encouraging academic interest and showcasing the excellence of future talents.

Eligibility and Requirements

Dissertations must be an original personal contribution and completed before submission. A jury will award the prize based on the criteria outlined below.

Thesis Topic

The thesis must relate to corporate finance or treasury. Examples include, but are not limited to:
Environmental externalities in WACC and investment projects
• Value creation by Corporate Venture Capital
• Managing electricity price volatility
• Net investments hedge for multinational companies
• Transfer Pricing models post-base erosion and Profit Shifting (BEPS)
• Counterparty risk in derivatives valuation
• Organizing a Group treasury

Submission Requirements

Submissions must include:
• A detailed plan
• A summary (800 to 1600 words)
• The thesis (50 to 150 pages, excluding annexes)
• Theses should preferably be in English, but Dutch is also acceptable.

Register by emailing management@dact.nl with the following:
• First name, last name
• Title and outline of the dissertation
• Academic institution and program description
• Certificate of attendance or student card for the 2023 – 2024 academic year
• Statement confirming the thesis is completed and graduated
• Deadline: September 30th, 2024. Late submissions will not be considered.

Jury

A jury consisting of DACT Board members, DACT members, and finance professionals will evaluate the dissertations.

Deliberations will be held in October 2024. Winners will be notified by the first week of November. Award recipients agree to present their dissertations at the DACT Academy on November 14th and 15th if requested.

The jury will assess theses based on structure, problem definition, clear conclusions, excellence, interest, originality, and professional impact. The jury’s decisions are final and may not be contested. No prize will be awarded if submissions do not meet the required standard. DACT reserves the right to postpone or cancel the contest without incurring any liability.

Dissertation Ownership

Authors authorize DACT and its partners to use their dissertations in publications, with proper credit to the author and education program. Submission of a thesis implies acceptance of these regulations.

Prizes

• Financial award of 2024 EUR
• Annual subscription to DACT Young Treasurers agenda
• Media attention
• Presentation at DACT Academy in November’2024
Details on prizes will also be available on the DACT website.

For more information, please visit the DACT website or contact us at management@dact.nl.

We look forward to your submissions and wish you the best of luck in the contest!

For the fourth time, DACT has organised a competition to identify the most outstanding treasury project in 2023. Following an exciting competition, we are delighted to unveil the recipient of the DACT Treasury Award 2023. With four noteworthy nominations this year, the ASML project ‘Improved FX Exposure Forecasting with Artificial Intelligence’ emerged as the winner, securing the highest number of votes from DACT members. If you’re intrigued to learn more about the winning project, the ASML team is set to present it at the Treasury Targets Meeting scheduled for 7 February 2024 at van der Valk Breukelen.

About the project

In 2023, ASML implemented a new AI powered material intake forecast model to increase the effectiveness and efficiency of its purchase FX hedging program.

ASML sources components for its chip machines from a large worldwide network of suppliers. The vast majority is sourced in Europe but some of them are sourced from the United States and paid in US dollars. ASML sells its systems in euros and is therefore exposed to EUR/USD exchange rate fluctuations. To mitigate the effect on its P&L, there is a purchase FX hedging program in place.

The fundament of this hedging program is the forecast of expected US dollar-denominated material intake. Prior to implementing the AI-powered forecast, the accuracy of the forecast was low (70%), it was manual and labor intensive, Excel-heavy, time-consuming and prone to error. Therefore, this project was launched to find a better solution.

The new forecast is generated by a fully automated AI Machine Learning model which was developed internally. The AI model recognizes 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 went up from 70% to 96%, making the hedging program more effective.

The project is a notable example of a close collaboration between two ASML teams – Treasury and Data Science. The expertise of both teams was required to create a working solution.

ASML decided to share this solution with the broader Treasury community to show that AI applications can be used and developed broadly in any company, big or small.  This particular AI model is based on a free open-source Python algorithm that was further optimized to ASML’s use case. This approach makes AI solutions easily accessible, scalable, and widely usable for any person or company. AI also helps to improve ASML’s understanding of the data while decreasing time spent on manual data gathering and processing, thereby freeing up time for more value-adding activities.

Key business benefits

• Improved exposure forecast accuracy (from 70% to 96%).
• More effective hedging, further reducing the impact of EUR/USD movements on ASML’s P&L.
• More efficient input for hedging without waiting time and manual effort/errors.
• The AI solution is learning every month, ensuring adaptability to business developments.
• Resources are freed up for more value-adding activities instead of data processing.
• Increased insights into the underlying data.
• The experience gained in this project will be applied to many more use cases within ASML.

Award ceremony

Award ceremony will take place during the ‘DACT Treasury Targets Meeting 2024’ on Wednesday, February 7th. DACT members and management representing the winning Treasury projects will be invited to attend.

About DACT

DACT, the Dutch Association of Corporate Treasurers, is the association for corporate treasurers and treasury professionals in the Netherlands. The association has more than 730 members, working at multinationals and large and medium-sized companies as well as government and non-profit organisations. DACT promotes the professional development of its members and the treasury profession, both within and outside the association.