Reference Data Integration of Risk Data In Major Investment Bank
The company is a leading global financial services firm with assets of over $1 trillion and operations in more than 50 countries. The firm is a leader in investment banking, financial transaction processing, asset and wealth management, and private equity.
Requirement: Manage Risk Through Optimal Credits Trading
The company is using PolarLake to manage risk exposure through real-time communication across bond, futures and credits trading. Specifically, PolarLake is being used to ensure that risk associated with bond and future trading is managed as efficiently as possible and trading performance is improved.
In order to offset risk, the Credits business relies on data relating to bond and future trading, plus price and position information, to be supplied in real-time to the Murex platform that supports credits trading. In order to build such a solution, it is necessary to manage a number of data transformations in real-time.
Solution: Real-Time Delivery of Trade Data to Credits Platform
This role is performed by PolarLake, operating within the bank's 'Credits Message Broker' (CMB), which:
- Receives data relating to bond and futures trades in XML format from Rosetta (which in turn has received this data from the bank’s internal trading platform), and converts this into the MxML format required by Murex.
- Splits multi-event messages into single-event messages, in order to support the integration process
- Where relevant, requests and attaches appropriate Reference data – retrieved from the bank’s internal Reference Data management solution – and delivers this to Murex alongside the trade data.
- Records and audits all messages passing through the CMB, and writes this data to an external database
Why PolarLake? Configuration of Complex Transformations
The transformation of formats from Rosetta XML to MxML is extremely complex. Changes in either schema can involve substantial re-development with significant time and cost implications. However, by using PolarLake this transformation can be configured in its entirety, which in turn means that the solution can be easily adapted to meet changing requirements.
This ability made the PolarLake solution preferable to the alternatives, whether these involved 'hard-coding' the integration process or relying on proprietary integration tools. By delivering improved flexibility PolarLake ensured that the finished solution will support the business by delivering both improved trading performance and increased operational efficiency.