I completed my PhD in economics with a focus on the usage of natural language processing in economic research (Radboud University Nijmegen, Netherlands). My teaching and research interests lie at the intercept of finance, governance, and machine learning. I am teaching at CBS in both finance, governance, and risk-related courses. Besides EGB, I am a research member at the center for corporate governance and work for the Software firm 2021.AI. I am currently working on the application of machine learning in economics and especially the governance aspect of it, which becomes more and more relevant in business and research.
I have been a guest lecturer at the Legal Department at Lund University and have lectured at the Dr. Werner Jackstädt Centre for Entrepreneurship and SMEs Flensburg. I have previously worked at CBS as an external lecturer teaching corporate finance and governance.
Primary research areas
Corporate finance
Corporate Governance with a focus on AI governance
Quantitative methods and their application in economics
I offer supervision at all levels (BA, MA) on the following subjects: Finance, Corporate Finance, Risk Management, Corporate Governance, Machine Learning, Quantitative methods and Strategy.
Selected publications
Preuß, B. (2021). Contemporary Approaches for AI Governance in Financial Institutions. Available at SSRN 3773581.
Preuß, B. (2021). Natural Language Processing - to Analyze Corporate Culture. Ph.D. Dissertation Radboud University Nijmegen.
Preuß, B. (2019). Equity fund managements promise and action: A comparative study of Nordic and US fund’s. Journal of Behavioral and Experimental Finance, 23, 84-89.
Preuß, A., & Preuß, B. (2017). Corporate tax payments and corporate social responsibility: complements or substitutes? Empirical evidence from Europe. Working paper
Björn Preuss / Natural Language Processing : To Analyze Corporate Culture. Radboud : Radboud University Nijmegen 2021, 242 p.
PhD thesis
2019
Bjørn Preuss / Equity Fund Managements Promise and Action : A Comparative Study of Nordic and US Fund's. In: Journal of Behavioral and Experimental Finance, Vol. 23, 9.2019, p. 84-89