A new BearingPoint study of 50 European financial institutions finds that 76% of banks cite supervisory feedback as a key trigger for identifying and correcting reporting errors, revealing data quality and governance gaps that automation and centralization alone cannot solve.
Management and technology consultancy BearingPoint has released a new study on regulatory reporting in European banks, finding that three in four banks cite supervisory feedback as a key trigger for identifying and correcting errors in their reports, a sign that internal data quality and governance controls have yet to keep pace with rising regulatory demands.
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When three in four banks still depend on supervisory feedback to trigger corrections, rather than consistently identifying issues before submission, that is a governance problem, not a technology problem.
Based on a survey spanning nine European countries, the study finds that while banks have established a broad set of data quality controls with 90% of participants having a minimum of three data quality controls in place and 66% have centralized their data architecture, fundamental governance gaps persist. Only 18% of institutions report full implementation of BCBS 239 principles, and just 24% have extensive data lineage documentation across their reporting processes.
“When three in four banks still depend on supervisory feedback to trigger corrections, rather than consistently identifying issues before submission, that is a governance problem, not a technology problem. Banks have made real progress on automation and centralization, but those investments only deliver if the underlying data is right. That starts with ownership, lineage, and controls that go all the way back to the source,” said Stefan Kauerauf, Partner at BearingPoint.
Key findings
- 42% of banks identify data quality as the biggest challenge in regulatory reporting
- Only 18% of institutions report full implementation of BCBS 239 principles, while just 24% have extensive data lineage documentation
- 76% of banks cite supervisory feedback as a primary trigger for report resubmissions, indicating that errors are still not consistently identified before submission
- 66% of institutions rely on centralized data warehouses as the foundation of their regulatory reporting architecture
- 50% of banks expect to implement AI use cases in regulatory reporting
Data quality gaps run deeper than controls suggest
The study shows that data quality issues continue to affect nearly every stage of the regulatory reporting process. Missing or incorrect data in source systems remains the leading cause of reporting errors, cited by 56%, respectively 50% of banks, while insufficient level of granularity, fragmented system landscapes and disconnected data flows add further complexity.
Although many banks have strengthened controls in recent years, significant governance gaps remain. Only 18% of institutions report full implementation of BCBS 239 and just 24% have extensive data lineage documentation across their reporting processes. The scale of the problem is further reflected in resubmission rates: only one third of institutions currently maintain resubmission rates below 5%.
As regulatory requirements become more granular and data-intensive, banks are increasingly recognizing that improving data quality is not merely a compliance necessity but a strategic prerequisite for scalable, efficient reporting.
Banks accelerate automation and centralized data strategies
To improve reporting quality and operational resilience, banks are increasingly investing in centralized data architectures, automation, and enhanced governance frameworks. The study shows that 66% of institutions already rely on centralized data warehouses as the foundation of their regulatory reporting infrastructure.
Automation is also becoming more deeply embedded across reporting processes. Most institutions now use automated validation checks, reconciliation mechanisms, and centralized controls to reduce manual interventions and improve consistency. Yet the pace of change has its limits: 90% of banks still rely on spreadsheets and other manual tools in their reporting processes, underscoring that truly straight-through reporting remains a distant goal for most institutions.
Banks are moving away from fragmented reporting structures toward more integrated and standardized operating models. Emerging technologies are expected to further accelerate this transformation. While the use of artificial intelligence in regulatory reporting is still at an early stage, 50% of surveyed institutions expect to implement AI use cases, particularly in areas such as anomaly detection, testing, and knowledge management.
“The banks pulling ahead are not necessarily those with the most advanced technology. They are the ones that have gotten serious about data ownership, lineage, and governance at every level of the organization,” said Holger May, Partner at BearingPoint. “Regulatory reporting will only become more demanding, and the institutions that treat it as a strategic capability now will be the ones navigating that complexity with confidence rather than scrambling to satisfy their supervisors.”
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