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European Association of Public Banks (EAPB)

A revision of the reporting system can only be beneficial if all reports are taken into account. This relates to statistical reporting, regulatory reporting and reporting to resolution authorities and deposit guarantee institutions (the latter two are not relevant for many EAPB members). In the end only in this way simplifications and reductions in cost can be achieved. Therefore, all relevant stakeholders must be taken into account in a feasibility study, i.e. both the reporting authorities and the reporting institutions.
Not relevantSomewhat relevantRelevantHighly relevant
Training / additional staff (skills)X   
IT changesX   
Changes in processesX   
Changes needed in the context of other counterparties / third-party providersX   
Time required to find new solutionsX   
Other (please specify)X   
Highly agreeAgreeSomewhat agreeDon’t agree
Data Dictionary - Semantic levelX   
Data Dictionary - Syntactic levelX   
Data Dictionary - Infrastructure levelX   
Data collection - Semantic levelX   
Data collection - Syntactic levelX   
Data collection - Infrastructure levelX   
Data transformation - Semantic levelX   
Data transformation - Syntactic levelX   
Data transformation - Infrastructure levelX   
Data exploration - Semantic levelX   
Data exploration - Syntactic levelX   
Data exploration - Infrastructure levelX   
A robust and well-defined data model for all reporting areas is the key to a future-oriented new reporting format. Approaches that are already well advanced in development, such as BIRD, should definitely be included in the development. The data dictionary should be structured in such a way that a transaction with all its components only needs to be reported once in order to fulfill all reporting requirements.
Understanding reporting regulationX  
Extracting data from internal systemX  
Processing data (including data reconciliation before reporting)X  
Exchanging data and monitoring regulators’ feedbackX  
Exploring regulatory dataX  
Preparing regulatory disclosure compliance.X  
Other processes of institutionsX  
Highly important
Highly costly
High cost reductions
High cost reductions
option 2
Regarding the granularity of the data to be reported, reporting at the individual transaction level must be intended. If aggregations and evaluations are carried out at the reporting recipients on the reported data, the rules used for this must be transparent and traceable for the reporting institution. Furthermore, it should be possible for the reporting party to get access to these results. In the end, only the reporting institution can be responsible for e.g. calculated capital ratios. Due to this initial situation, only option 2 (page 78 of the Discussion Paper) can be the preferred way of implementation, with the reduction of the volume of data to be reported being a key objective.
Highly (1)Medium (2)Low (3)No costs (4)
Collection/compilation of the granular dataX   
Additional aggregate calculations due to feedback loops and anchor valuesX   
Costs of setting up a common set of transformations*X   
Costs of executing the common set of transformations**X   
Costs of maintaining a common set of transformationsX   
IT resourcesX   
Human resourcesX   
Complexity of the regulatory reporting requirementsX   
Data duplicationX   
Other: please specifyX   
Highly (1)Medium (2)Low (3)No benefits (4)
Reducing the number of resubmissionsX   
Less additional national reporting requestsX   
Further cross-country harmonisation and standardisationX   
Level playing field in the application of the requirementsX   
Simplification of the internal reporting processX   
Reduce data duplicationsX   
Complexity of the reporting requirementsX   
Other: please specifyX   
Authorities and reporting institutions jointly
Definition of appropriate rules.
Data collection on prudential, statistical and resolution legislation should be aligned; supervisory scope should change.
Valuation methods, for example, fair value, amortized costs etc. should be harmonized; unique valuation method.
Rules across the entire EU should be harmonized.
Alignment across the entire EU, like legislation on confidentiality and data privacy, etc.

Legal aspects should be treated at national level and taken into account at European level definitions.
The majority of the institutions report to different authorities in their countries.

Problems that arise from reporting to different authorities:
- Differences in: (data) delivery models, accounting rules, definitions, consolidation aspects, technical formats, reporting timelines and frequencies;
- Overlapping data requests;
- Local differences in terms of regulation;
- Mix of aggregated and granular data;
Multiple dictionaries
Because of differences in primary reporting definition as well as in the technical input layer across EU countries, institutions are consequently using a different semantic and syntactic data definition and a different semantic and syntactic definition for the data collection.

In other cases, dictionaries differ country by country or by reporting framework. Some are using an internal data dictionary, while some other banks are using one conceptual data dictionary with more technical implementations. That’s why, each system has its own implementation.
Different formats
Very important
- One dictionary for all data collections, without any regard to the final purpose, who the requesting authority is, and what the national vs EU nature of the request is.
- Only one collection layer, no existence of multiple reporting layers.
- Proper governance should be established, in order to reuse and share already existing data.
- Standardized transformation rules deriving regulatory data/templates.
- In order to protect sensible data from EU and other countries, encryption facilities should be available.
- For all types of reports and in all jurisdictions, the interfaces for data collection should be consistent.
- Uniform protocols and formats should be used for data exchange between the institutions and the authorities.
- Common roles and access control rules.
- Data quality should be assured through quality controls and control framework.
- Clearly defined Data Dictionary covering the data definitions; principles and rules of data quality management;
- Complex data transformation should be avoided.
Following aspects should be taken into account to reduce the costs:

- A commonly used single granular data model in the European banking industry is essential to reduce the costs of reporting.

- To the reporting institutions both the proposed "centralized system" (5.2.10) and "distributed system" (5.2.11) are beneficial in a same manner, but we consider that the centralized system would produce a lower TCO. Furthermore, if the "distributed system" allows for national divergence of data requirements, this alternative will be significantly worse than the centralized system for the reporting institutions.
Yes, to a limited extent
not valuable at allvaluable to a degreevaluablehighly valuable
Data definition – Involvement    
Data definition – Cost contribution    
Date collection – Involvement    
Date collection – Cost contribution    
Data transformation – Involvement    
Data transformation – Cost contribution    
Data exploration – Involvement    
Data exploration – Cost contribution    
Data dictionary – Involvement    
Data dictionary – Cost contribution    
Granularity – Involvement    
Granularity – Cost contribution    
Architectures – Involvement    
Architectures – Cost contribution    
Governance – Involvement    
Governance – Cost contribution    
Other – Involvement    
Other – Cost contribution    
The estimation of costs is bank-specific and requires a detailed analysis. Moreover, it depends on the scenario (full integration to optimizing current DPM), the granularity of reporting frameworks and transformation aspects. Because of theses unknowns we are not able to provide a figure.
A push approach
With regard to the organization of future reports, an institute should only have to deliver a report to one central office and only clarify any data quality problems that arise with this office (single point of contact). Since the responsibility for the correctness of the data lies with the supplying institute, the push model seems to be the only possible solution in terms of architecture.
We agree with the EBA-description of the ‘Agile Coordination Mechanism’, because it represents a simple and efficient way to manage a better governance of new data requests and to make use of the capabilities of the CDCP and the common data dictionary. For example, since the objective of the data request can differ, it could start with defining the data definitions per competent authority. Once this is done, it could detect and eliminate overlaps. A unified code for each data definition will support this (and will ease machine readability). In case an authority wants to add a new definition, it should clearly state why this definition from its point of view is missing in the central dictionary. Then a board of supervisors for prudential and statistical reporting should judge the new requests and, if approved, should ensure that the data element is added to the central framework.
We consider that this matter should be discussed in the further course.
Other (please explain)
The use of RegTech by the institutions differs. Some of them do not use it at all. Others use it partially, for example, to support data collection and transformation. There are also institutions using it widely, in each step of the reporting process.
The advantages of using RegTechs can only be assessed on an institution-specific basis. The larger and more complex or specialized an institution's business, the lower the marginal benefit of using a RegTech.
Farid Aliyev