IReF and BIRD: How the ECB Is Rethinking Regulatory Reporting

Most of the infrastructure that keeps the financial system running is invisible. Customers never see the databases that record every mortgage payment, corporate loan, or securities transaction, and investors rarely think about the complex machinery that transforms millions of individual records into the regulatory reports submitted to supervisors every month. Yet behind every figure published by a bank lies an intricate architecture of data, business rules and reporting processes that has evolved over decades, gradually becoming more sophisticated with each new regulatory requirement, and more fragmented.

This is precisely what this publication explores: how the European Central Bank (ECB) is attempting to reshape that architecture through two closely connected initiatives: the Integrated Reporting Framework (IReF) and the Banks' Integrated Reporting Dictionary (BIRD). 

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Although they may initially appear to be another update to the regulatory reporting landscape, together they represent a much broader shift: from a world where banks produce multiple overlapping reports to one where a single, granular dataset can serve as the foundation for statistical reporting and, over time, support a more integrated reporting architecture. Beyond the technical changes, these initiatives also raise important questions about the future of banking data, the role of standardization, and whether Europe is finally addressing a problem that has been building for more than a decade.

The Problem With Today's Reporting Landscape

Over the past fifteen years, European banking regulation has grown considerably. Following the global financial crisis, every new supervisory requirement introduced its own reporting framework, technical specifications, and implementation rules. Liquidity reports, capital requirements, statistical reporting, AnaCredit, Asset Encumbrance and interest rate statistics were all developed to address different supervisory needs, but rarely with a common data architecture in mind.

As a result, banks have gradually built reporting processes in isolation. Different regulators often request very similar information, sometimes even the same underlying data, but with slightly different definitions, formats or reporting frequencies. The consequence is a fragmented ecosystem where identical data is extracted multiple times, transformed through different business rules and ultimately submitted through separate reporting processes.

This fragmentation comes at a significant cost. It increases operational complexity, creates inconsistencies between reports, duplicates data management efforts, and makes every regulatory change more expensive to implement. After more than a decade of incremental regulatory developments, many banks have ended up with reporting architectures that reflect the history of regulation rather than the logic of their own data. Addressing that accumulated complexity is, ultimately, the main objective behind IReF.

Rethinking Regulatory Reporting: Building Around a Single Dataset

At its core, the Integrated Reporting Framework, an initiative led by the European Central Bank, is based on a remarkably simple idea. Today, banks produce multiple statistical reports through separate reporting processes, even though much of the underlying information is exactly the same. IReF aims to change that by allowing institutions to submit a single granular dataset from which the ECB and national central banks can derive the statistical outputs they need.

Instead of reporting aggregated balances or weighted averages, banks will progressively submit information at the level of each individual financial instrument. Every loan, deposit or security will include the relevant attributes, such as its contractual amount, maturity, interest rate, counterparty and sector classification.

Once that information has been reported, the ECB and national central banks will be able to generate different statistical outputs without repeatedly requesting variations of the same underlying data.

Although the change may sound technical, the underlying idea is actually simple: 

Today

• Similar information is requested through multiple reporting frameworks.

• Banks maintain separate extraction and transformation processes for each submission.

• The same underlying data is often calculated, reconciled, and reported more than once.  

With IReF 

• Data is reported once at the level of each financial instrument.

• A single granular dataset supports multiple statistical reports. 

• The objective is to reduce duplicate reporting processes and data requests.

Simplifying the statistical reporting landscape by removing duplication and centralizing information across multiple frameworks is the central ambition of IReF. Delivering that goal, however, requires banks to rethink the architecture that underpins regulatory reporting and adopt a fundamentally different approach to data management.

A Data-Centric Reporting Model

The most significant change introduced by IReF is conceptual rather than technological. For decades, regulatory reporting has been organized around the reports themselves. Operational systems generate data, reporting engines aggregate that information, apply business rules and populate predefined templates, with each reporting framework following its own process.

IReF proposes a different model, one in which the quality of the underlying data becomes the starting point for regulatory reporting. Instead of focusing on aggregated figures, banks will need to ensure that every financial instrument is complete, accurately classified and fully traceable back to its source system. Once that level of consistency has been achieved, producing regulatory outputs becomes significantly more straightforward.

For many institutions, this represents a broader transformation than simply adapting existing reporting tools. It requires stronger data governance, consistent identifiers across systems, better metadata management and much closer alignment between operational systems and regulatory reporting. In many respects, the challenge is architectural, requiring organizations to rethink how regulatory data is managed long before any report is produced.

BIRD: A Common Methodology for Regulatory Reporting 

While IReF defines the information that banks will be expected to provide, BIRD focuses on the methodology used to prepare it.

Developed jointly by the ECB, national central banks and representatives from the banking industry, the Banks' Integrated Reporting Dictionary provides a common framework for transforming operational banking data into regulatory information. Its purpose is to reduce interpretation by establishing shared definitions, common data models and standard transformation rules that institutions can use when building their reporting processes. 

The underlying philosophy will be familiar to organizations working in regulatory technology. Most modern RegTech platforms already rely on transformation layers that map, validate and enrich operational data before generating regulatory reports. BIRD follows the same principle by defining a common interface between source systems and regulatory outputs, making it easier for banks to align their internal data with supervisory expectations while reducing unnecessary differences in interpretation across the industry.

Importantly, BIRD is not intended to replace existing reporting platforms or the proprietary calculations that many institutions have developed over the years. Some regulatory metrics will always depend on institution-specific business logic. Instead, the framework focuses on standardizing the common elements that every bank needs, creating a shared foundation that can support future reporting requirements more efficiently.

Its flexibility also allows institutions to adopt it progressively, depending on their own priorities and level of maturity. This means banks can use BIRD in several ways:

• As a reference dictionary, helping standardize terminology, documentation and data governance.  

• As a methodological guide, providing a consistent interpretation of transformation rules.  

• As an input model, aligning internal data interfaces with the architecture proposed by the ECB.  

For some institutions, that may simply mean improving documentation and governance. For others, it could become the foundation of a broader transformation towards a more reusable and data-centric reporting architecture.

Has the ECB Arrived Too Late?

The objectives behind IReF and BIRD are difficult to question. Reducing duplication, improving data quality and creating a common methodology for statistical reporting are sensible ambitions. The challenge is that these initiatives arrive after more than a decade of regulatory reporting developments, at a point when banks have already invested heavily in reporting platforms, internal data models and proprietary business rules.

Had a common methodology existed when many of today's reporting frameworks were first introduced, institutions could have designed their reporting architectures around it from the beginning. Instead, every bank has gradually developed its own interpretation of regulatory requirements, while technology providers have built sophisticated platforms to support those implementations.

This also explains why BIRD has been introduced as a voluntary framework. Replacing mature reporting infrastructures represents a significant investment, and many institutions are unlikely to revisit systems that already meet their regulatory obligations. The discussion is therefore less about whether the framework makes sense and more about how quickly banks will see enough value to adopt it.

Preparing for the Transition

Although mandatory implementation is still several years away, there are already practical steps that forward-looking institutions can take while the framework continues to evolve. Large-scale data transformation programs typically take years to deliver, particularly when they involve operational systems, governance and enterprise-wide architecture.

Institutions that choose to begin preparing early are likely to focus on several common areas:

• Assessing how current data compares with IReF's future requirements. 

• Using BIRD as a reference model to strengthen data governance and standardize transformation rules. 

• Monitoring the evolution of the ECB's technical specifications and participating in pilot programs where possible. 

• Evaluating whether future reporting architectures should be designed around a more data-centric model. 

Preparing early is more than meeting future regulatory requirements. It also gives banks the opportunity to modernize reporting architectures that, in many cases, have grown incrementally over more than a decade.

Looking Beyond Compliance

Beyond the immediate regulatory changes, IReF and BIRD reflect a broader shift in the way supervisory reporting is evolving. Future reporting frameworks are increasingly likely to rely on common data models, granular information and reusable datasets rather than independent reporting processes.

For banks, this means that the quality of regulatory reporting will depend less on the sophistication of individual reports and more on the consistency, traceability and governance of the underlying data. For technology providers, it creates an opportunity to help institutions bridge the gap between today's reporting architectures and the more integrated models that regulators are gradually promoting.

How quickly the industry embraces IReF and BIRD will become clear over the coming years, but their significance already extends beyond these two initiatives. Regulatory reporting is steadily evolving towards a model built on granular, reusable and well-governed data, placing greater emphasis on the quality of the underlying information than on the reports themselves. Institutions that begin strengthening those foundations today will be in a stronger position as that transformation continues.

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FAQs: IReF and BIRD Regulatory Reporting

• What is IReF (Integrated Reporting Framework)?
  IReF is an ECB-led initiative that lets banks submit a single granular dataset, at the level of each financial instrument, from which the ECB and national central banks can derive the statistical reports they currently request separately.

• What is BIRD (Banks' Integrated Reporting Dictionary)?
  BIRD is a common methodology, developed by the ECB, national central banks and industry representatives, that defines shared data models and transformation rules for turning operational banking data into regulatory information.

• How are IReF and BIRD different?
  IReF defines what data banks need to report — a single granular dataset. BIRD defines how to prepare that data, through shared definitions and standard transformation rules.

• Is BIRD mandatory for banks?
  No. BIRD has been introduced as a voluntary framework. Banks can adopt it as a reference dictionary, a methodological guide, or an input model, depending on their own priorities and maturity.

• How can banks start preparing for IReF and BIRD?
  Institutions can assess how current data compares with IReF's future requirements, use BIRD to strengthen data governance and standardize transformation rules, and monitor the ECB's technical specifications as they evolve.