Our candidates have been chosen. We are proud to present our three nominates for the fifth GDBC Thesis Award.

"Hi, my name is Sydney Perdon, and I am honored to be nominated as one of the three finalists for the GDBC Thesis Award in Digital Business.

I have always loved technology and gadgets, and I naturally grew into the role of “early adopter” among friends. I am the person who wants to try every new feature, app or device as soon as they come out. Over time that curiosity shifted from just enjoying new tools to wondering what they could actually change in how we work. That feeling only intensified in recent years when AI tools became part of my everyday life. First as something I experimented with out of curiosity and later as a serious way to explore text and data.

When I started my studies in Accountancy and Controlling at the University of Groningen, I realised how much potential AI offers for improving digital business, but I also saw another side of the story. Corporate disclosures, such as annual reports and earnings call transcripts, can be extremely dense and technical, even for analysts and investors who read them for a living. That made me curious whether AI really understands this type of complex language and whether it could help close the gap between what companies communicate and what users actually take away from it.

All of this came together in my thesis, titled “Language Complexity and AI’s Ability to Predict Analyst Questions”, where I looked at how language complexity affects AI models in generating financial analyst questions. With the help of AI tools, I learned to build Python scripts to automate and scale the data gathering process. I then used text similarity and language complexity measures to compare AI generated, analyst style questions with those asked by human financial analysts. The results suggest that AI can be a useful tool when disclosures are clear, but it has difficulty matching the depth of human experts when the language becomes more complex. For me, this shows both the promise and the current limits of AI in financial communication.

I am excited to share my findings at the GDBC Thesis Award and to connect with others who are exploring how technology and data can improve transparency and decision making."