Using xBRL-CSV for granular data: a proof of concept from XBRL Europe
“Our proof of concept suggests that xBRL-CSV could streamline the reporting process and facilitate users in comparing and analysing information from across different countries and reporting requirements, including extensive and detailed data,” says Vincent Le Moal-Joubel, data scientist and XBRL expert at the Banque de France. In a new post over in the Taggings section of the XBRL International website, he presents important work on behalf of the XBRL Europe Bank and Insurance Working Group, illustrating how the xBRL-CSV format can be used to handle granular data.
The proof of concept takes AnaCredit as its example, as this produces very large volumes of information on individual bank loans. Currently, each country implements AnaCredit differently, making it very expensive to comply with, or even to develop complaint software. The working group developed a data point model and provisional taxonomy to connect the reporting template with consistent, machine-readable meanings.
“The most important benefit XBRL brings is standardisation of data,” explains Le Moal-Joubel. Users are guided to correctly produce each fact and produce comparable data using familiar XBRL tools, already in place across Europe. XBRL also offers extensibility, allowing countries to add local reporting requirements, and the ability for users to determine how data is displayed, for example switching between languages – both very valuable in the European context – as well as the potential for validation of data quality.
When it comes to granular data, xBRL-CSV brings a critical additional advantage: it produces dramatically smaller files, making reports substantially easier to produce, handle, send and store. For AnaCredit data, the working group found that using xBRL-CSV reduces file size by almost a factor of ten in comparison with traditional XML-based XBRL. xBRL-CSV files are also easily readable and editable without technical XBRL knowledge, helping filers and other users to focus on the data.
The working group plans to develop the proof of concept to carry out more experimentation and demonstrate additional functionalities. “There is no doubt that trends in reporting are moving towards the collection of larger volumes of more granular data, but this data is meaningless unless it can be handled and analysed effectively. So far, xBRL-CSV appears to offer an efficient and practical solution for future reporting,” says Le Moal-Joubel.
Read more here.
