Dr. Christian Fieberg, Matthies Hesse, Prof. Dr. Thomas Loy and Daniel Metko have published a new working paper under the title "Machine Learning in Accounting Research". The authors present a compact overview of machine learning applications in financial accounting and audit research as well as management accounting research. Here, the application of machine learning has the potential to provide novel insights into empirical data and to improve predictive performance. The authors highlight the potential use of deep learning to process unstructured and structured data more efficiently and a greater focus on model interpretability as viable opportunities for future research.

The full article can be accessed here.