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UBS Enhances Risk Management and Compliance with Neo4j Data Lineage Tool
Technology Category
- Analytics & Modeling - Real Time Analytics
- Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries
- Equipment & Machinery
- Finance & Insurance
Applicable Functions
- Quality Assurance
Use Cases
- Real-Time Location System (RTLS)
- Track & Trace of Assets
Services
- System Integration
The Challenge
UBS, a multinational investment bank and financial services company, was faced with the challenge of complying with regulations put in place to strengthen systems for risk data aggregation and internal risk reporting following the 2007 global financial crisis. Specifically, UBS needed to comply with the Basel Committee on Banking Supervision issued standard 239 (BCBS 239). This regulation required banks to provide transparency into the data flows that feed their risk reporting, necessitating broad data governance and detailed data lineage. Data lineage, which involves tracking the entire lifecycle of information, is a crucial component of risk management. UBS initially built an application called Group Data Dictionary (GDD) as its data lineage and data governance tool on Oracle. However, they soon discovered limitations with an RDBMS approach, which relies on JOINS to connect data across tables. UBS realized it needed a better solution for creating real-time data lineage visualizations and exporting lineage information for ad-hoc analysis via Excel.
The Customer
UBS
About The Customer
UBS is a multinational investment bank and financial services company based in Switzerland. Founded in 1862, it is a significant player in the Swiss banking industry. UBS maintains offices in over 50 countries, employs more than 66,000 people, and reported total assets of over $958 billion in 2018. The company operates in five main business areas: personal banking, wealth management, corporate and institutional clients, investment banking, and asset management.
The Solution
UBS turned to Neo4j to build a more efficient data lineage and data governance tool. Neo4j, a graph database, offered several advantages over a relational database, including querying using Neo4j’s Cypher query language. Cypher allowed UBS to more easily traverse connected data, especially compared to PL/SQL, which relies on JOINS across multiple tables to generate the lineage in a relational database format. The new tool needed to integrate smoothly with the legacy system, as all UBS workflows and auditing capabilities remained on Oracle. UBS synchronized Neo4j with the Oracle system, starting with an initial data load and then performing an incremental sync in which transactions were read from an Oracle table and written into Neo4j in real time. UBS used Neo4j to evaluate data lineages and depict the results in GraphJSON, which then flowed into a D3.js visualizer to render the data as a lineage diagram. This setup allowed for easy reporting, with the data being used for ad hoc reporting and entire lineages being exported to Excel.
Operational Impact
Quantitative Benefit
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