One of the drawbacks of the IReF-only approach is that it does not implement the standardised data dictionary (BIRD) envisaged by the ECB. This may lead to increased reporting overhead in the long term, as new regulatory requirements are expected to be based on the BIRD data model.
In addition, if the institution chooses a proprietary data model, there is a certain degree of dependency on the software provider, which could lead to a reduction in flexibility compared to institutions using other approaches.
IREF Collection Layer is the reporting scheme of IReF and establishes the connection between BIRD and IReF. This was presented for the first time as part of BIRD version 6.0. An extended technical layer is also to be created for country-specific data requirements (source: Bundesbank)
The IReF-first-BIRD-later approach
In this approach, both IReF and BIRD are implemented in phases. In the first phase, only IReF is implemented (similar to the IReF-only approach). After the institute is IReF compliant, it can choose to implement BIRD (either fully or partially) to achieve a higher degree of standardization.
The advantage of this approach is the lower implementation or project risk, which is mainly due to lower complexity compared to a comprehensive BIRD and IReF implementation. In the first phase, the focus is on ensuring timely IReF reporting capability and taking advantage of the IReF-only approach. This also includes the possibility of using the existing reporting software with its advantages and disadvantages, as described in the paragraph above. The subsequent implementation of BIRD has the advantage that all participants (authorities, institutions) have gained sufficient practical experience with BIRD by the time it begins, and the quality and completeness of the uniform data model should be significantly improved. In addition, the BIRD implementation can also have the benefit of reducing the number of queries from the supervisory authority regarding the submitted data due to the uniform data language. In addition, there is also an opportunity to use multi-party service providers.
A disadvantage of this approach is the additional effort and time required to implement BIRD separately in the second phase. Some of the implementation steps (for example, data quality checking) may need to be done twice – first for IReF and later again for BIRD. In addition, a decision must be made as to which parts of the existing reporting architecture need to be changed in order to implement BIRD, or what degree of alignment with BIRD should be implemented in order to achieve better standardization and thus exploit automation potential.
Institutions that are already using a reporting software provider for regulatory reporting may choose to follow the IReF-first-bird-later implementation approach to first ensure IReF reporting capability based on the vendor's data model and current software, and then decide how much flexibility and standardization they need in the future. This would depend on how different the final version of BIRD will be compared to the software vendor's data model.
The IReF and BIRD approach
This approach implements BIRD and IReF, where BIRD is considered the basis for IReF. This requires an initial analysis to verify the compatibility of the existing data repository with the BIRD definitions. As both BIRD and IReF must be implemented by the respective launch or pilot phase, institutions adopting this approach should start the compatibility analysis at an early stage on the basis of the BIRD resources published so far on the ECB's website.
A major advantage of this approach is the high degree of standardization. Full alignment with the unified BIRD data dictionary means automation capabilities can be implemented more easily. It is possible to use artificial intelligence and cloud solutions to develop tools and integrate them into the reporting landscape. These can include data analysis tools, data quality verification tools, testing tools, and data aggregation tools, among others. The approach also makes it possible to outsource certain aspects of regulatory reporting with less effort in the future (use of multi-party service providers). A high degree of standardization can also lead to a reduction in ad hoc data requirements from supervisors, which can contribute to a significant reduction in resources in the long term. It can also be assumed that new regulatory requirements will be easier to implement, as new supervisory requirements are expected to be aligned with the BIRD standard for data definitions.