Managing the Complexity and Distribution of Pricing and Reference Data
While centralizing reference data collection and cleansing is inherently a good thing, it can add to complexity. The fact is distributing data, adding data feeds and adding new asset classes to ten, twenty or even a hundred downstream systems is a challenge for many firms. Buy side, sell side and fund administration firms who address these issues will achieve cost reduction, productivity improvement and improved risk management.
"Our clients have grown frustrated with data base replication, ETL and EAI. They are being forced to sort out a messy situation with limited visibility of the scale of the problem."
Warren Buckley, PolarLake CTO
The PolarLake product deals with the constant change in Pricing and Reference Data environments. The product allows business operations and business analysts to:
- Distribute, synchronize and control data distribution irrespective of the number of downstream systems
- Manage and control large scale data mappings in a controlled excel like environment built for Business Analysts
- Deal with new instruments, new downstream systems, new data feeds, new asset classes and variations on existing asset classes in a controlled manner
- Collect all vendor data into a centralized repository and implement policies on access control and distribution rules with an inbuilt policy engine.
The product allows for the technical complexity of batch, real time and request reply and has proven to scale across over 100 downstream systems.
Industry Insight
Why ETL just isn’t good enough for Reference Data Distribution
ETL as a concept sounds very well suited to the world of Reference Data Distribution. Extraction, Transformation and Loading all sound like good things to do when distributing Reference Data. This is why a lot of the ETL vendors show up at the usual Reference Data conferences. It all sounds logical. And lots of Financial Institutions are using it for Reference Data Distribution, usually because there is an available license and it is notionally “free” to use. This all sounds straightforward?
Case Studies
Reference Data, Trade Data Integration to Murex and Settlement Systems
A leading investment bank is using PolarLake to improve the efficiency and accuracy with which trading and settlement systems are updated with credit default swap affirmations originating from external broker/dealers.
2010