Reference Data Standards: Cornerstone for Compliance Reporting
Key Drivers for Compliance Reporting
Data Life-cycle Management
– A significant concern for financial services firms: recent SEC and government legislation (e.g., BCBS 239, CCAR, AML)
Data Lineage
– No documented data flows from source to target. It is difficult to identify owners of data and assess change impact on applications.
Accountability for quality of information
– Low level of confidence in information exchanged across business lines which is used for corporate reporting, both internal (i.e. G/L, Profitability) and external (i.e. SEC, FED Compliance)
– No consistent definition of business elements/rules across the enterprise.
Data Segmentation Matrix
Pillars of Reference Data Standards
Identify and categorize all business entities (internal and external) for processing efficiency, regulatory compliance and risk mitigation
Identify all instruments and transactions with precision
- Identify all data elements associated with a financial transaction lifecycle with absolute precision (standard terms, definitions and relationships)
- Define a common a protocol for efficient and accurate processing
- Reference Data tables needs to be populated long before any application goes live
- Timely update/maintenance of enterprise-wide reference data values
- Reference Data element values need to be ‘normalized’
– Clearly and unambiguously define formal and hidden sub-types
– Define correct level of reference data element value abstraction
– Resolve overlapping reference data values
– Eliminate gaps in reference data values
– Eliminate different level of reference data values in a category
Challenges in Reference Data Management
- Dependency on personal expertise in interpreting content rich data.
- A necessary and critical first step in reference data management is clean data. No amount of sophistication in technology solution is going to make up for poor quality data.
- Identifying business elements in scope.
- Identifying data sources and establishing data lineage for each subject area.
- Capturing business rules – policies defining how data is created or eliminated or derived.
- Capture data usage rules and data ownership/governance rules.
Benefits of Standardized Reference Data
- Regulatory Compliance
– Audit and Transparency
– Consistency
– Process Controls & Security
o Best-practice business process for dimension management
o Comprehensive control and security to ensure compliance
o Flexible security to reflect roles and responsibilities
- Increased Accuracy
– Single Dimensional Repository
– Web-based Deployment
– No Redundant or Conflicting Data
o Eliminate wasted time and effort reconciling and correcting dimensional and hierarchical conflicts
o Subscribe to identical, centrally managed dimensions, eliminating redundancy and conflict
- Faster Results
– Collaborative, Web-based Workflow
– No Manual Reconciliation
– Process Efficiency
Totally agree. Would possibly challenge the impact on ‘data lineage’ as this tends to be target to source for financial data. Reference data (internal and external codes) don’t usually change through a date flow. If any company tackles governance and data management for any set of data, it should start with reference data. Basis for most reporting and analytics.