European supervisors are quietly rebuilding the digital plumbing of regulatory reporting, and the consequences for banks and insurers could be profound. Across the continent, authorities are pursuing a strikingly consistent agenda built on three strategic pillars: simplification, standardisation and integration.
According to Regnology, viewed individually, the announcements may appear disconnected. Examined together, they point to a wholesale evolution of the supervisory data ecosystem.
Regnology recently delved into the rise of machine-readable and AI-enabled regulatory reporting.
Regulators and regulated firms alike are abandoning legacy, report-centric pipelines in favour of a data-centric paradigm in which information is treated as a strategic, reusable asset.
These architectural changes also lay the groundwork for SupTech innovation and AI-assisted regulatory processes. While AI is not the immediate goal of every initiative, high-quality, standardised and machine-readable data is a non-negotiable prerequisite for deploying it effectively.
Collect once, use many
The first major theme is a systematic assault on data fragmentation. Instead of treating reporting as a set of isolated, template-driven compliance chores, authorities are building consistent data foundations that can serve multiple regulatory, supervisory and analytical purposes.
The European Banking Authority’s simplification proposals mark a significant shift, integrating and streamlining requirements spanning FINREP (aligned to IFRS 18), operational risk, liquidity risk, ESG, supervisory benchmarking, stress-testing data and selected Pillar 3 disclosures. The package goes further than trimming data points; it aims to improve cross-domain consistency, curb overlapping collections and reuse existing structures. Notably, the framework is not shrinking everywhere – new harmonised requirements for third-country branches may initially expand reporting scope.
ESMA offers perhaps the boldest example. Its “Report Once” proposal identifies up to €1bn in potential annual savings by structurally simplifying transaction reporting across MiFIR, EMIR and SFTR, tackling the underlying architecture through shared standards, common data structures and more efficient exchange.
EIOPA, meanwhile, is cutting the burden within Solvency II itself. Its proposals include reduced reporting frequencies, removal of selected annual templates, stronger proportionality and technical simplifications. Solo undertakings can expect an estimated 22% reduction in data points, with quarterly templates falling by 26% and annual templates by 30%.
Granularity and quality rise up the agenda
Even as processes are consolidated, supervisors are demanding more granular, higher-quality data. The ECB’s Integrated Reporting Framework (IReF) is the flagship, replacing country-specific statistical templates – AnaCredit, BSI, MIR and SHS – with a single, harmonised euro-area framework built on granular data points. The ECB’s multi-year roadmap, with a pilot in 2030 and official reporting in 2031, hands banks a concrete timeline for modernising their data architecture.
The Single Resolution Board reinforces the trend. Its Expectations on Valuation Capabilities require banks to establish structured valuation data repositories, a Valuation Data Index, an enhanced Valuation Data Set and supporting valuation playbooks, phased in through 2029, so that reliable granular data can be produced rapidly in a resolution. Complementary guidance on liquidity and funding in resolution focuses on the operational capability to estimate liquidity needs, report positions and mobilise collateral under crisis conditions.
A common language for an AI-ready ecosystem
Integrated reporting and granular data demand consistent definitions across systems, authorities and regulatory domains. That is where the Data Point Model (DPM) standard comes in, connecting reporting templates with clearly defined business concepts, dimensions and validation logic, making requirements machine-readable and systematically processable.
Following publication of DPM 2.0 in 2023, the EBA, ECB and EIOPA formed the DPM Alliance in 2024, creating joint governance for the standard and harmonising definitions across banking, insurance and statistical reporting.
For supervisors, this structured metamodel could unlock agentic AI-driven smart data validation using ML anomaly detection, automated text extraction via NLP and predictive risk modelling that adapts to regulatory updates. For financial institutions, RegTech tools built on governed semantic models can support regulatory impact analysis, consistency checks, data mapping and change detection, with agent-based workflows on the horizon, subject to governance, auditability and human oversight.
All eyes now turn to the EBA’s forthcoming DPM 2.1 update. The strategic direction is unambiguous: success requires targeted investment in a robust, well-governed and reusable data foundation, not merely refreshed templates.
Read Regnology’s full post here.
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