Einsatz von KI zur Automatisierung von Rechnungslegungs- und Meldewesenprozessen in Banken – Chancen, Herausforderungen sowie Implikationen

This paper examines how artificial intelligence (AI) can drive the automation of accounting and regulatory reporting in banks. The objective is to provide practical guidance for the compliant and effective adoption of AI in a highly regulated environment, while assessing related opportunities and risks. Documented banking case studies are analysed to derive a technology-levels model and transferable best practices. In addition, a SWOT analysis identifies the key strengths, weaknesses, opportunities, and threats influencing AI integration. Combining both approaches, the study develops practical recommendations, highlighting that AI is particularly effective in standardised, data-driven processes such as regulatory reporting. At the same time, organisational readiness and regulatory compliance prove to be decisive success factors. Building on these insights, a ten-step roadmap is proposed as a hands-on guidance tool for banks. The findings contribute to the strategic evolution of regulatory reporting and illustrate how even highly regulated institutions can prepare for and benefit from AI-driven transformation.

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Publication Details

Journal
IU Discussion Papers Human Resources
Published
2025-09-29
DOI
https://doi.org/10.56250/4082
Primary Topic
Corporate Governance and Management
Type
article
Field-Weighted Citation Impact
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article

Einsatz von KI zur Automatisierung von Rechnungslegungs- und Meldewesenprozessen in Banken – Chancen, Herausforderungen sowie Implikationen

Constantin Schubart, Marcel Dulgeridis, Felix Berndt
IU Discussion Papers Human Resources
Corporate Governance and Management
article

Einsatz von KI zur Automatisierung von Rechnungslegungs- und Meldewesenprozessen in Banken – Chancen, Herausforderungen sowie Implikationen

Constantin Schubart, Marcel Dulgeridis, Felix Berndt
article en

Abstract

This paper examines how artificial intelligence (AI) can drive the automation of accounting and regulatory reporting in banks. The objective is to provide practical guidance for the compliant and effective adoption of AI in a highly regulated environment, while assessing related opportunities and risks. Documented banking case studies are analysed to derive a technology-levels model and transferable best practices. In addition, a SWOT analysis identifies the key strengths, weaknesses, opportunities, and threats influencing AI integration. Combining both approaches, the study develops practical recommendations, highlighting that AI is particularly effective in standardised, data-driven processes such as regulatory reporting. At the same time, organisational readiness and regulatory compliance prove to be decisive success factors. Building on these insights, a ten-step roadmap is proposed as a hands-on guidance tool for banks. The findings contribute to the strategic evolution of regulatory reporting and illustrate how even highly regulated institutions can prepare for and benefit from AI-driven transformation.

IU Discussion Papers Human ResourcesVol. 6(13)
IU International University of Applied Sciences (DE)
Openalex Percentile: Top 61%
Corporate Governance and Management
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