The final release of the CRD IV 2.9.1 taxonomy has been published and this means that reports in 2020 need to be created with the 2.9.1 version. The reference dates differ between the different kinds of reports:
Package 2.9 RESOL to apply from 31/12/2019
Package 2.9 COREP to apply from 31/03/2020
Package 2.9 FINREP to apply from 30/06/2020
Package 2.9 LCR to apply from 30/04/2020
Package 2.9 SBP to apply from 31/12/2019 (IMV from 26/09/2019):
More information regarding the new taxonomy version you can find on this link.
The description of changes between the previously used version 2.8.1 and the new version 2.9.1 is quite extensive, since the taxonomy has been changed a couple of times last year. If you want more information regarding the changes, please let us know, and we can help you get through the documentation.
We have updated our template by creating it straight from the presentation documents in the taxonomy itself, instead of using the old templates. We did this to be less dependent on EBA creating the template. This means that the layout of the file changed a bit:
Furthermore, the taxonomy has split up several tables into sections a, b, c, etc. We followed this presentation since it may prevent some possible validation errors regarding elements containing invalid hypercubes in all base sets. These validation errors are difficult to solve most of the time and we hope that splitting up the tables according to the taxonomy presentation will help prevent these validation errors. This may cause issues importing XBRL files from earlier templates, but we are trying to solve that as soon as possible.
The prevalidation is not included yet. We noticed some differences in validation rules and have to adapt the template generator to prevent false positives. This will be included as soon as possible.
The template can be downloaded on this link.
Please let us know if you have any questions regarding the new taxonomy or new template.
The importance of proper XBRL tagging for data analysis XBRL can have some major upsides with regards of automatically analyzing a lot of financial data.