Getting Data Management in Order
June 23, 2011
By Chris Kentouris
The Financial Services Authority in mid-June sent out a letter to the top brass of over 200 wealth management firms in London berating them for not making suitable investments for their retail clients.
Last year, the U.S. adopted the Dodd-Frank Wall Street Reform Act and similar pending regulations on the other side of the Atlantic require swap traders to trade their standardized contracts on an electronic trading through an electronic trading platform, clear them through a central clearinghouse and report them to a trade repository. The legislation has also created the Office of Financial Research which will require that large systemically important firms send daily position, transaction and other reports. Many hedge funds and other private equity advisors must also now register for the first time with the Securities and Exchange Commission and provide plenty of documentation on their operations.
What is the common thread among the disparate scenarios? “The need for accurate data so firms can correctly value their holdings, keep track of their positions and counterparties on an enterprise wide basis to monitor their market, credit and liquidity risk,” said Tim Lind, global head of strategy and business development for enterprise content at Thomson Reuters.
The key obstacle: the data is stored in too many applications, in too many formats and may be inconsistent or inaccurate. Counterparty data – information about customers and trading partners -- is the one fund managers should be worried about the most. Because corporate structures and affiliations change so rapidly that it’s hard to keep up. There is no single centralized source of information; it’s scattered in multiple legal filings and corporate websites. Thomson Reuters, for one relies, on over 1,000 information providers.
So what’s a fund manager to do to get its data infrastructure in order? For starters, take inventory. Firms do have all the information they need available in their systems “The challenge is joining the dots across silos for a complete data map across a firm,” said Daniel Simpson, chief executive officer of Cadis, a London-based enterprise data management firm. “Data management can establish that linkage across the enterprise to provide the granular data necessary.”
Among the questions firms must ask themselves: what derived information is in internal applications; what data is derived from data vendors and what data resides on spreadsheets, according to Stephen Engdahl, senior vice president of product strategy for GoldenSource, a New York based enterprisewide data management software firm.
Next up: figure out just how to ensure accurate data and distribute it downstream. One way is to rely on a data scrubbing engine which comes as part and parcel of a central repository system and integration mechanism. GoldenSource’s EDM platform, Asset Control’s AC Plus and Cadis EDM do just that and be flexible enough so each business line can have a different view of the financial contract or counterparty using a common data model.
But some traditional and hedge fund managers are taking a different tack in embracing data virtualization or “data as a service” as a higher level approach to data management. It is based on establishing canonical standards for data, which are adapted to the needs of consuming applications. The core governance process enables identification, as well as normalization or cleansing of parallel data throughout the various systems in which it resides. The result is support of multiple “golden copies,” according to Vijay Oddiraju, CEO of Volante Technologies, a provider of modeling and metadata management software for financial data.
