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Publications

 

Working paper

• Föhr, T. L., Schreyer, M., Moffitt, K., & Marten, K.-U. (2024). Deep learning meets risk-based auditing: A holistic framework for leveraging foundation and task-specific models in audit procedures. SSRN Working Paper 4488271.
• Föhr, T. L., Schreyer, M., Juppe, T. A., & Marten, K.-U. (2023). Assuring sustainable futures: Auditing sustainability reports using AI foundation models. SSRN Working Paper 4502549.

 

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International publications

• Föhr, T. L., Reichelt, V., Marten, K.-U., & Eulerich, M. (2025). A framework for the structured implementation of process mining for audit tasks. International Journal of Accounting information systems, 56, Article 100727.
• Seidenstein, T., Marten K.-U., Donaldson G., Föhr, T. L., Reichelt, V., & Jakoby, L. B. (2024). Innovation in audit and assurance: A global study of disruptive technologies. Journal of Emerging Technologies in Accounting, 21(1), 129-146.
• Föhr, T. L. (2024). A method to categorize and classify artificial intelligence applicable to the risk-based audit approach. Die Unternehmung, Vol. 78 (3), pp. 264-310. Swiss Journal of Business Research and Practice.

 

National publications

• Reuter, F., & Föhr, T. L., (2025): Generative AI as a co-pilot in the audit of financial statements, in: Die Wirtschaftsprüfung (WPg), Vol. 78 (2), pp. 59-66.
• Föhr, T. L., & Schreyer, M. (2024). Generative artificial intelligence for risk-oriented auditing. REthinking: Tax, 7(4), pp. 13-16.
• Reichelt, V., Mayer, H. M., Föhr, T. L., & Damjanovic, N. (2023). Reporting on Artificial Intelligence and Ethical Approaches, in: Journal of International and Capital Market Accounting (KoR IFRS), Vol. 23 (4), pp. 159-165.
• Föhr, T. L., Marten, K.-U., & Schreyer, M. (2023). Generative artificial intelligence and a risk-oriented audit approach, in: Der Betrieb, Vol. 76 (30), pp. 1681-1693.
• Bauckhage, C., Föhr, T. L., Loitz, R., & Marten, K.-U. (2023). Five theses on the importance of artificial intelligence in auditing, in: Der Betrieb, Vol. 76 (36), pp. 2065-2067.
• Reichelt, V., & Föhr, T. L. (2023). Artificial Intelligence and Robotic Process Automation in Accounting and Auditing Research. REthinking: Tax, 5(3), pp. 25-29.
• Marten, K.-U., Föhr, T. L., & McIntosh, S. (2022). AI-based data analyses and a risk-oriented audit approach, in: Die Wirtschaftsprüfung (WPg), Vol. 75 (16), pp. 898-908.
• Marten, K.-U., Föhr, T. L., Juppe, T. A., & Reichelt, V. (2022). Fraud detection using new technologies in financial statement audits? Implications from practice and research, in: Hossenfelder, J. (ed.) (2021), Lünendonk-Handbuch Wirtschaftsprüfung und Steuerberatung 2022 - 60 führende Partner für Ihr Unternehmen, Freiburg/München/Stuttgart 2021, pp. 69-95.