Financial institutions everywhere are facing major data management challenges as they strive to meet emerging regulatory requirements. Broad regulations like FINREP, COREP and MiFID II are all placing new reporting demands on banks and other financial firms. At the same time, individual jurisdictions are introducing their own reporting rules, adding complexity to the overall data management challenge.
Against this backdrop, financial institutions themselves are seeking better quality data - in terms of accuracy, timeliness and granularity - to support their business lines and central functions like finance and risk. As a result, firms are finding they need both aggregated data to provide a top level view of their activities, and a more granular view that allows them to respond to regulators' and managers' ad hoc enquiries.
Meeting this dual requirement is no trivial matter. But new regulations from the Austrian central bank could provide a blueprint for solving this data management challenge. The Austrian regulator has defined a series of so-called Smart Cube data reporting formats that require banks to automate and standardize their data collection and validation
processes. But to implement this new reporting structure properly, banks are finding that they need to underpin their reporting processes with a robust data management model, as embodied by a so called Basic Cube approach.
Adoption of the Basic Cube approach, however, holds the promise of enhanced data quality for regulatory reporting. But will it be extensive enough to yield benefits in other areas of the bank, like finance and risk management, which require similar, if broader data sets.
to find out more, download this white paper here.