Exploring the data governance role in accounting fraud prevention in German Banking

Accounting fraud remains a persistent challenge in the banking sector, despite extensive regulatory frameworks and advances in digitalisation. Recent cases such as Wirecard highlight that fraud can still thrive when data flows are opaque, governance responsibilities are unclear, and Accounting Information Systems (AIS) allow manual intervention and unverifiable evidence. Against this backdrop, this study explores the role of Data Governance (DG) in accounting-fraud prevention within the German banking sector, examining how DG can be embedded into AIS to reduce vulnerabilities in reporting processes. A qualitative research approach was adopted, combining a narrative–systematic literature review, semi-structured expert interviews with banking, auditing, compliance, and DG specialists, and a focused analysis of the Wirecard fraud case. The thematic analysis revealed recurring weaknesses in data ownership, reconciliation processes, lineage documentation, access control, and system integration—points at which fraud opportunities typically accumulate. These findings align with contemporary research emphasising the importance of data-centric and system-centric controls in preventing fraudulent financial reporting. The study identifies three core DG functions that support fraud-preventive AIS design: enhancing DG awareness (through clear roles, training, and cognitive transparency); mitigating fraud risks (via automated validation, reconciliation engines, lineage requirements, and real-time monitoring); and fostering organisational accountability (through stewardship structures, cross-functional coordination, and strengthened oversight). Drawing on these insights, the study proposes a DG-enhanced AIS model and a practical 34-point checklist translating DG principles into actionable system architecture and operational routines. The results underscore that fraud-prevention effectiveness increases when DG mechanisms are embedded directly into AIS workflows and supported by supervisory expectations—including DG-oriented reviews of AIS design and financial-reporting applications.