New MaRisk requirements contain extensive guidelines for data management
On October 27th, 2017 the Federal Financial Supervisory Authority (BaFin) published the long-awaited new minimum requirements for risk management (MaRisk), which are essentially valid with immediate effect. The only exceptions to this are major changes or new additions to the MaRisk requirements such as, for example, the general section 4.3.4, which deals with the subject of data management. While this entire section (4.3.4) only applies to system-relevant institutes, it remains to be seen to what extent this becomes established as an evaluation benchmark for other institutes.
The new data management guidelines are nearly identical to the already widely discussed data management requirements of the 239 BCBS principles. The following requirements will apply to your institute:
Governance and responsibilities
The set-up of a data management unit together with a clear allocation of data responsibilities forms a substantial basis for data quality.
Compliance with internal and external requirements must be reviewed independently. This may be done through the data management unit depending on your set-up.
Data structure and hierarchy (data linage)
Documenting data flows (front-to-end) and defining a data structure are time-consuming and can only be assisted by technology under certain circumstances.
Setting up a data dictionary and setting out clear field definitions (metadata definition) will facilitate the aggregation of data for a wide range of reporting requirements in future too.
Analyzability and verifying plausibility
Data aggregation capacities
The set-up of an integrated finance and risk architecture for, inter alia, the analysis of data for a wide range of purposes is costly, but worthwhile.
Not least as a result of the regulatory situation, data – and its management – is becoming the most important asset for banks. The Q_PERIOR Data Management Design Framework offers an extensive overview of the topic of data management. It examines all aspects of sustainable data management, from data strategy to data culture.
In order to implement these requirements without hurting your budget while at the same time increasing efficiency, activities in and around the field of data management should ideally be pooled. This is the only way financial institutions can generate additional added value with investments. If you would like a quick indication of how your company is positioned currently from a data management point of view, please get in touch. Using efficient tools we can give you a quick overview and direct your attention to measures that could help you to facilitate sustainable data management.