by Grégoire Bourban
June 25, 2018
Come October 2018, credit institutions under the aegis of the European Central Bank (ECB) and National Central Banks (NCBs) in eurozone countries, will deliver their first full Anacredit reporting packages based on the state of business as of the end of September 2018. So what makes this piece of regulatory reporting so different from all the others?
Anacredit reporting demands precisely described granular data points presented in a data model designed by the regulator – the first time the ECB is after data-point information. It is accompanied in that experiment by the lesser-known Securities Holdings Statistics, applicable to some large banking groups and also going live at the end of Q3 this year. Next in line will be FINREP, a revamp of the existing requirements for more data granularity in filings. All three are part of the ambitious Banks’ Integrated Reporting Dictionary (BIRD) programme, marking a shift towards reporting at the granular level.
Under the BIRD programme, the ECB and NCBs intend to provide “a precise description of the data that must be extracted from internal systems to generate reports” and “clearly defined rules for transforming these data in order to comply with reporting requirements”. The direction of travel is set: the central banks in the European Union (EU) are moving from the specification of aggregated reporting figures to the specification of those figures’ building blocks.
After a decade of seismic shifts that have reshaped financial regulation, producing a complex landscape littered with sometimes very similar and often overlapping requirements, the banks should warmly welcome the BIRD initiative. It attempts to standardise and integrate the data specifications underpinning several key regulatory reports and represents a tremendous opportunity to decrease the overall burden and cost of regulatory compliance.
The pressure on systemically-important banks (SIBs) to uphold their data governance significantly increased with the advent of BCBS 239, the risk data-management and integration principles issued by the Basel Committee on Banking Supervision. Anacredit goes further. All credit institutions – SIB or not – with at least one branch in the eurozone should ensure their data management and architecture can accommodate the new regulatory challenges.
At the heart of the new world of granular regulatory specifications lies the need for detailed and robust processes around data management throughout the entire data lifecycle and across all systems. At any point in the lifecycle, data ownership should be clearly defined and the different teams within the organisation should be held accountable for the data they own and produce. This accountability should be enforced and visible at senior management level. In a nutshell, the quality of the granular data should be ensured through appropriate procedures and processes from data input onwards.
On the data architecture front, the cost-cutting opportunities opened up by Anacredit and the BIRD programme should be assessed against the backdrop of the institution’s current data landscape and use. For example, the detailed data requirements and model imposed by the regulator for Anacredit may cover at least partially a bank’s internal needs for credit risk management, so it would make sense for the bank to embed those specifications into its own credit risk datamart. By doing so, it would ensure a close alignment between externally-reported and internally-consumed credit risk data. In this way the reported data will become available in an internal data warehouse, making de facto redundant the now ubiquitous specialist third-party regulatory-reporting datamarts. And there are plenty of similar cost-saving opportunities.
In theory, the more granular the data points specified by the regulator, the more precise the related regulatory requirement. More precise regulatory requirements can in turn lead to greater co-operation in the implementation of regulation among financial institutions as interpretations converge. Resource sharing and other synergies in implementation projects across banks using a same core platform and a similar operating model can be then unlocked, yielding significant cost savings for all the participants in the scheme.
While a new world order where all regulatory requirements in the EU and beyond are expressed at the data-point level is still some way off, banks should not wait to engage in the strategic leap forward in data governance and management needed to efficiently and effectively cope with the oncoming regulatory paradigm shift. To wait will inevitably cause problems.
In a world where aggregated information is sent to the regulator, financial institutions could modify aggregated values to make up for biases introduced by inferior-quality granular data. In the new world, the granular data themselves will be exposed to the regulator. Poor or even average-quality data will not be an option.