Abstract
The collection of granular data has been one of the major shifts in the compilation of central bank statistics in the last twenty years. The increase in computing power and storage capacity, and the corresponding increasing digitalisation of the economy, has transformed the statistical landscape and the “business as usual” of financial statistics. Granular data allow flexibility and thus to meet better changing user needs; they reveal the heterogeneity in the economy, the concentration of risks, and the interconnectedness of the entities; and they map better the intricacies and flows of a globalised world. Finally, and perhaps crucially, they allow collecting data once to serve a variety of purposes.
Nevertheless, granular data face substantial challenges and necessitate a paradigm shift if they are to achieve their multiple goals. The change in the scale of the statistical units analysed – from the sector level information, to the credit institution and down to the transaction – requires the identification of entities and objects in a standardised manner. Granular data also impose consistency and homogeneity on the data at source (through the use of generic and detailed reporting formats), as well as authoritative reference databases. The globalised nature of financial entities requires increased international cooperation between collecting authorities and close work with the reporting entities. Last but not least, they also need the transformation of the internal organisation to collect, process, store, and integrate the data inside the collecting institutions.
These challenges are being addressed at the ECB in different ways. We provide an overview of selected endeavours in the field of securities issuance, holding statistics and financial accounts, showing the path from reference databases, through the collection of granular data and the intermediate outputs, to aggregate statistics with a full granular foundation.