Lívia is head of the Digitalisation Technology Department of the Central Bank of Hungary. She holds a M.S. in Data Science Methodology from University Pompeu Fabra, and a B.S. and M.S. in Economic Analysis from Corvinus University of Budapest. She is currently a PhD candidate in AI at the Computer Science Doctoral School at the Budapest University of Technology and Economics.

Central Bank of Hungary

AI-Driven Initiatives at the Central Bank of Hungary (MNB)

The presentation explores the opportunities and research areas in AI for enhancing central bank operations, from economic analysis to real-time data insight, with a focus on the innovative solutions implemented by the MNB. There will be 2 projects presented: the first part delves into NLP-driven sentiment analysis of the Hungarian economy, showcasing a method to extract timely signals from online news text and to use them for macroeconomic nowcasting. The second part discusses and analysis of the online cash register data using NLP and deep learning techniques.