The European Banking Authority (EBA), European Central Bank (ECB) and European Insurance and Occupational Pensions Authority (EIOPA) have opened a consultation on DPM 2.1, an update that could change how financial institutions structure, manage and reuse data for supervisory reporting across the EU.
According to a Regnology analysis of the proposals, the consultation is focused on updating the Data Point Model (DPM), moving regulatory reporting away from static templates and towards a shared, machine-readable data architecture. The analysis argues the evolution could redefine the reporting lifecycle, shifting institutions from cyclical, template-driven compliance towards continuous data governance built around a centralised data foundation. Stakeholders have until 30 September 2026 to submit feedback, with a final version of DPM 2.1 expected in the fourth quarter of 2026.
The proposed standard builds on the DPM Refit project and DPM 2.0, which established a common metamodel for structuring regulatory reporting requirements across different modelling approaches. DPM 2.1 is not intended to represent a disruptive migration, but rather an extension of the existing framework based on practical experience and the requirements of broader cross-domain reporting.
A key driver has been the ECB’s Integrated Reporting Framework (IReF), which is being built on DPM 2.0. Its development exposed additional requirements for the metamodel, which are now being incorporated into DPM 2.1 to support greater convergence between statistical and supervisory reporting.
One of the proposed changes is the introduction of explicit JSON taxonomies. By standardising metadata exchange in a machine-readable format, the update is intended to make it easier for systems to exchange regulatory information and reduce processing overhead when handling complex data transfers.
DPM 2.1 also introduces more structured versioning and historisation of metadata. Rather than treating regulatory changes as isolated updates, the model is designed to track changes chronologically within a unified database structure, preserving relationships between reporting requirements over time.
Another significant change is the separation of physical reporting templates from the underlying logical concepts. This would allow a data point, such as a specific exposure value, to be defined once and reused across different reporting modules rather than recreated for each individual framework.
The draft also proposes further changes covering the identification of physical and logical frameworks, version control for item names and descriptions, data domains and hierarchical structures, compound properties and standardised regular expressions for property validation.
The changes form part of a wider governance initiative led by the DPM Alliance, established in 2024 by the EBA, ECB and EIOPA, with the involvement of the Single Resolution Board. The alliance is intended to provide a common governance structure for the DPM standard and reduce duplicated modelling work across prudential, statistical and insurance reporting.
Alongside the metamodel, the Common Data Dictionary is intended to provide a single authoritative source for regulatory concepts. The goal is to reduce ambiguity and the manual reconciliation between risk, finance and compliance teams when the same underlying information is represented differently across reporting frameworks.
For financial institutions, the changes could have implications beyond the way regulatory reports are produced. A more connected data model would allow requirements to be traced from their legal source through to reporting definitions, data points and technical reporting artefacts, creating a more structured audit trail.
Regnology director of product management Erik Becker said, “The metamodel explicitly separates physical reporting templates from underlying logical concepts, allowing the same data… to be defined once and reused across completely different reporting modules.”
The architecture could also provide a stronger foundation for artificial intelligence across the regulatory reporting lifecycle. Regnology identifies potential applications including regulatory change management, automated impact analysis, semantic mapping and AI-assisted regulatory queries.
For example, AI systems could use structured links between legal provisions, regulatory concepts and data requirements to identify potentially affected reporting areas following a regulatory change. They could also help map terminology between new requirements and existing data structures or provide answers to internal regulatory queries with links back to the relevant source data.
However, the move towards machine-readable regulatory data does not remove the need for human oversight. Legal interpretation remains dependent on context and supervisory objectives, while AI-generated mappings and impact assessments would still require review by regulatory experts.
For financial institutions, this could mean a gradual shift in investment away from downstream fixes for individual reporting templates and towards centralised data models, governance and traceability. The objective is to create a reusable data foundation that can support multiple reporting obligations rather than maintaining separate structures for each framework.
The consultation therefore represents more than another technical update to supervisory reporting. Regnology’s analysis highlights a broader shift towards a connected, legally traceable metadata environment in which regulatory data can be defined once, governed centrally and reused across reporting frameworks. If that architecture develops as intended, the emphasis for financial institutions will increasingly move from fixing individual reports downstream to building the data foundations that support reporting, regulatory change management and AI-enabled processes.
Read the full Regnology analysis
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