Financial Institutions must improve data quality and prove to regulators that they have an ‘end to end’ data governance framework. Banks are utilizing ModelDR to build a congruent data structure that overarchs multiple systems with large numbers of data attributes
Data Point Modelling is being utilised to meet regulator demands for transparency around intra day bank liquidity (IDBL).
Regulatory requirements might include
– records of daily cash liquidity movement
– internal & external monitors on daily liquidity flows
– limits on cash funding requirements of internal trading desks
– controls on IDBL requirements by reducing Intra desk portfolio size if predefined funding limits are exceeded
Risk Data Management
Banks must improve data quality and demonstrate full traceability. Banks are developing a universally defined XBRL data governance framework. Currently global banks report to local regulators in various locally defined reporting codes. The global use of disparate but similar financial definitions increases and duplicates the volume of regulatory reporting. Adoption of universal and congruent reporting in XBRL will streamline and improve efficiency
XBRL Regulatory Reporting
The eXtensible Business Reporting Language is the global standard for regulatory reporting in the financial world. The European Central Bank chose the data point model for its COREP and FINREP XBRL based initiative with 5000 European banks reporting.
These ECB regulatory reports have 30,000 elements. The bank used the data point model to bring this scope of data together. Leading banks are learning from the success of the ECB