Financial-services firms are scrambling to improve their reference data to achieve STP and in turn improve efficiency, reduce errors, lower risk and save money. At WS&T's "Drilling Down on Straight-Through Processing," conference yesterday industry players explored reference data and what can be done to "Clean up" the static information--from security identifiers to counter-party information and settlement instructions--that is necessary for every trade.
John Bottega, director, global markets and investment banking, enterprise data standards at Merrill Lynch said that reference data is the number one cause of breaks in STP not just in the clearance and settlement area, but across the entire lifecycle of a trade. He noted that there are four main components necessary for clean reference data: information architecture, technology, process and organization.
The information architecture layer should include standards covering common names, values and formats that will enable various databases to communicate and share data back and forth. In addition, the information architecture should include a data dictionary with common definitions of data elements and common symbology for the consistent identification of data.
For the technology component, Bottega said that as vendor feeds come in, it's vital that feeds are parsed to a staging area and rules engine and then are loaded to "golden copy" for use across the enterprise. Rounding out the technology component should be workflow tools, a database management system and query layer.
For the process component, Bottega said that centralized workflow and error correction is essential for consistent and complete reference data. And all of these efforts should be supported by the organization for total success of the reference-data program. Overall, he said, reference-data strategies should be a joint effort between business and technology personnel and departments as a top down and bottom up initiative.
Rich Robinson, assistant vice president, global equities IT at Deutsche Bank AG, added that reference data is a key inhibitor to straight-through processing as firms must deal with multiple data sources from multiple vendors in different formats as well as multiple data definitions and terminology.
By standardizing vendor feeds and data definitions and terminology and centralizing shared data, firms can improve their reference data strategies as well as their processes and communication. He said that shared data should be centralized in a depository