The lack of timely risk data was a major contributor to the global financial crisis of 2008 as the collapse of Lehman Brothers sent shockwaves through the banking world. Since then, regulators have established LEI and BCBS 239 standards for recording, aggregating, and tracking financial transactions. These new standards collectively enable banks to assess risk, trace data lineage, and understand dependencies on other systems, investments and financial houses.
BCBS 239 requirements create several complex data management challenges that include:
- Systems must trace financial risk information backward until its data lineage ends at an authoritative source
- Risk calculations and reports must span discrete data silos as a unified source
- Developers must reconcile significant terminology differences across departments and systems
- Systems must connect historical entity codes with ISO’s new Legal Entity Identifiers for all data elements
- Regulatory reports must solve data consistency and latency problems across all silos so the reports are accurate and consistent as of a specific time
Given these complications, many banks have embraced a federated model that leaves data dispersed in its original silos, while maintaining control of the model using centralized metadata. Progressive banks are using BSBC 239 to justify building a strong metadata foundation for risk management, regulatory and analytic applications.
Data management experts agree that metadata challenges should be solved using graph databases rather than traditional database technologies. Neo4j, the world’s leading graph database is a perfect platform for addressing the challenges of BCBS 239 regulations.
Learn how connected data and graph database technologies are transforming risk reporting in modern banks to help them meet the stringent demands of risk reporting compliance.