Challenges and opportunities for finance research in the era of large LLMs

As a side initiative of the 2026 Summer School on AI for Economics and Finance, organized by ESOMAS, this panel brings together leading researchers from academia and scientific publishing to discuss how recent advances in artificial intelligence are reshaping finance research.

From large language models and AI agents to broader machine learning techniques, AI is transforming the way researchers collect and analyze data, develop models, generate hypotheses, and communicate scientific findings. At the same time, these technologies raise important questions regarding reproducibility, transparency, scientific rigor, publication standards, and the evolving role of researchers in the scientific process.

The panel will explore both the opportunities and the challenges that AI presents for financial economics, offering perspectives from academic research, computational economics, scientific publishing, and AI applications in economics and finance.

• Markus Leippold (University of Zurich and Swiss Finance Institute), Professor of Financial Engineering whose research focuses on machine learning, artificial intelligence, and quantitative finance, with particular emphasis on AI-driven methods for asset pricing, portfolio management, and financial decision-making.
• Simon Scheidegger (University of Lausanne), Professor of Economics whose research combines computational economics, machine learning, scientific computing, and high-performance computing to solve large-scale dynamic economic models and develop novel computational methods for economics.
• Florian Oswald (University of Turin and Collegio Carlo Alberto; Data Editor, Journal of Political Economy), economist specializing in computational methods, spatial economics, and reproducible research, bringing the perspective of scientific publishing, data transparency, reproducibility, and evolving research standards in the age of AI.
• Fabio Trojani (University of Geneva, Swiss Finance Institute, and Collegio Carlo Alberto), Professor of Finance and Reale Foundation Chair in the Applications of AI for Economics and Finance at Collegio Carlo Alberto. His research spans financial econometrics, machine learning, robust statistics, and artificial intelligence, with applications to asset pricing, risk management, portfolio choice, and the integration of AI methods into financial economics.

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