The EU geographical summary in the following focuses on rising risks from geopolitical risks as well as climate-related, environmental and nature risks and the need for data and risk data capabilities, especially under consideration of the digitalization initiatives by the EU, ECB and ESMA.
Rising Risks, Resilience and Data Capabilities
Financial institutions are still affected by rising risks and increasingly from geopolitical risks1 and climate-related, environmental and nature risks. These risks are highly prioritized by ECB and the revised SREP guidelines2. These risks are cross-cutting risk drivers with impact on financial institutions’ traditional risk categories. The financial and operational resilience is key to be well prepared to manage the impact of these risk drivers. Therefore, these risks increase the following risks as well especially: AML and operational risks and needs to be considered in AMLD 6 (see EU 2024/1640) implementation or in ensuring DORA compliance. Geopolitical risks were also a key component of the 2025 EU wide stress test and have an impact on cyber risks, incl. AI driven attacks and identity fraud and AI-assisted phishing.
These rising risks from geopolitical risks as well as climate-related, environmental and nature risks are required to be considered in the institutions’ stress testing and its impact on multiple risk categories to derive the right measures for governance, compliance and risk-mitigation measures and increase the robustness. Thus, it is key to define the right institution specific scenarios with a forward-looking approach, to quantify the impact and to identify the risk drivers. To be able to do this, financial institutions needs to increase their efforts to remediate long-standing shortcomings in their risk data aggregation and risk reporting (RDARR) capabilities and to design and execute a robust implementation from governance, compliance, data and IT point of view (see also ECB GL on RDARR3). In a broader context the EU supervisory authorities follow different targets to foster digitalization and data capabilities by financial institutions as dealt with in the following section.
Digital Transformation
The European financial landscape is undergoing a profound digital transformation driven by a series of ambitious regulatory initiatives and the EU Data Act. Frameworks such as the Financial Data Access (FiDA) regulation, the Integrated Reporting Framework (iReF) with BIRD (Banks’ Integrated Reporting Dictionary), the European Single Access Point (ESAP) and the eIDAS (electronic IDentification, Authentication and trust Services) regulation on digital identity collectively aim to enhance transparency, data standardization, and secure data exchange across the financial ecosystem.
While these initiatives promise to create a more harmonized and efficient reporting environment, they also place significant new demands on financial institutions. Reporting obligations are growing not only in volume but also in complexity especially for the short-term access, requiring institutions to ensure data quality, consistency, and timeliness are upheld across multiple frameworks and jurisdictions. Manual processes are no longer sufficient to handle these requirements.
Automation of regulatory reporting and internal controls has therefore become an essential strategic priority. Through end-to-end automation, organizations can achieve and retain compliance more efficiently, ensure data integrity, and reduce operational risk—while enabling their teams to focus on analysis and decision-making rather than administrative burden (see also ECB GL on RDARR4).
Automation of regulatory reporting and internal controls will become an essential strategic priority.
Integrating data management and regulatory intelligence with technological innovation
Despite the clear benefits of digitalization initiatives driven by the EU, ECB and ESMA, financial institutions face several challenges when implementing it across FiDA, iReF/BIRD, ESAP, and eIDAS compliance domains as well as across the existing regulatory reporting and disclosure requirements (e.g. FinRep, CoRep, CSRD, EBA Pillar 3). Many institutions still rely on siloed systems where transactional, risk, and financial data are stored separately. This fragmentation makes it difficult to consolidate and reconcile data in line with the granular reporting and data access requirements.
Each regulatory initiative introduces specific data models, taxonomies, and reporting formats. iReF and BIRD aim to standardize banking reporting, ESAP focuses on public financial and sustainability disclosures, FiDA facilitates data sharing across the financial sector, and eIDAS governs digital identity and trust services. Keeping up with these evolving standards and ensuring alignment among them towards existing reporting and disclosure requirements needs dynamic and adaptable systems.
With regulators emphasizing data integrity and traceability, institutions must implement rigorous consistency, consolidation, and harmonization checks across their datasets to keep the consistency between finance, accounting and risk data as well as to have an integrated view between nominal and economic perspective. Manual reconciliations are slow and error-prone, increasing the risk of non-compliance. Automation should not only produce accurate reports but also embed automated internal controls that track data lineage, enforce validation rules, and provide a transparent audit trail. Ensuring these controls are robust and compliant with internal and external audit requirements remains a technical and organizational challenge. Replacing legacy reporting tools and manual workflows with automated systems requires investment, stakeholder buy-in, and process redesign. Institutions must carefully balance innovation with regulatory continuity and operational stability.
The foundation of effective automation is a centralized, harmonized data model that consolidates input across business lines and systems. Modern data platforms allow institutions to ensure traceability from initial source data to reported figures. Based on this, strengthening data lineage and quality controls across reporting entities is essential, with clear reporting ownership per regulation to ensure governance and validation of reported or disclosed data with continuously updated policies and internal procedures for reporting or publication frequency, access rights, and corrections.
A modern data management needs a data intelligence and data governance platform that helps to automate data quality management, creates data catalogues and enforces policies to make data usage trustworthy and transparent, incl. metadata management, business glossary definition, and data lineage monitoring. Institutions can integrate automated control layers that validate data accuracy, completeness, and consistency throughout the reporting lifecycle. Examples include automated reconciliation checks, variance analysis, and rule-based alerts for anomalies. These controls not only ensure compliance but also strengthen internal governance by providing real-time visibility into data quality and process performance. Automation should extend beyond data processing to include workflow orchestration, ensuring that reporting cycles—from data extraction to validation, submission, and archiving—follow standardized and auditable procedures. Intelligent workflow engines can assign tasks, track approvals, and generate auditable control evidence automatically. Finally, automated systems should include self-testing and monitoring capabilities that detect deviations from expected results. Embedding these checks ensures continuous assurance of compliance, even as data sources or regulatory definitions evolve.
Automation should not only produce accurate reports but also embed automated internal controls that track data lineage, enforce validation rules, and provide a transparent audit trail.
Conclusion
Financial institutions face mounting risks driven by geopolitical tensions and climate-related, environmental, and nature factors, which are central priorities for ECB – supported also by the revised SREP guidelines. These cross-cutting risks amplify traditional categories and should be fully integrated into AMLD 6 and DORA compliance frameworks. They were also embedded in the 2025 EU-wide stress tests, highlighting their impact on cyber resilience and emerging threats such as AI-enabled attacks and identity fraud. Strengthening financial and operational resilience requires addressing long-standing weaknesses in risk data aggregation and reporting (RDARR) and improving governance, compliance, data, and IT integration.
EU supervisory authorities are simultaneously driving digitalisation initiatives (FiDA, iReF/BIRD, ESAP, eIDAS) that redefine regulatory reporting and disclosure expectations.
By embracing automation and robust data frameworks, financial institutions can transform compliance into a strategic capability—enhancing transparency, trust, and adaptability in an increasingly data-driven regulatory landscape.
References
1 See addressing the impact of geopolitical risks by the ECB https://www.bankingsupervision.europa.eu/framework/priorities/html/geopolitical-risk.en.html (accessed Nov. 7, 2025)
2 See ECB priorities for 2025-27 and revised SREP GL (consultation) https://www.bankingsupervision.europa.eu/framework/priorities/html/ssm.supervisory_priorities202412~6f69ad032f.en.html; https://www.eba.europa.eu/publications-and-media/press-releases/eba-consults-revised-guidelines-supervisory-review-and-evaluation-process-and-supervisory-stress (accessed Nov. 7, 2025)
3 See https://www.bankingsupervision.europa.eu/ecb/pub/pdf/ssm.supervisory_guides240503_riskreporting.en.pdf (accessed on Nov. 7th 2025)
4 See https://www.bankingsupervision.europa.eu/ecb/pub/pdf/ssm.supervisory_guides240503_riskreporting.en.pdf (accessed on Nov. 7th 2025)