The Financial Services Authority in mid-June sent out a letter to the top brass of over 200 wealth management firms in London telling them to clean up how they store financial and background data on retail clients. Many had apparently not been making suitable investment decisions for their customers.

Last year, the U.S. adopted the Dodd-Frank Wall Street Reform Act, which requires swap traders to trade their standardized contracts 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 it daily positions, transactions and other reports. In addition, many hedge funds and other private equity advisors must also register with the Securities and Exchange Commission for the first time 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, and 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 is often the one funds should be the most worried about, as corporate structures and affiliations change rapidly. There is also 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 official sources in 60 different languages.

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. Among the questions they must ask themselves: what derived information is in internal applications, what data is derived from data vendors and what data resides on spreadsheets, said Stephen Engdahl, senior vice president of product strategy for GoldenSource, a New York-based enterprise-wide data management software firm.

Next up: figure out just how to ensure accurate data and distribute it to multiple applications. 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 EDMplatform, Asset Control's AC Plus and Cadis EDM offer just that and are 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 integration.

Data virtualization allows users of data to pick and choose data from anywhere in the firm.

Creating a single repository to store all of their data often isn't even feasible or practical. Firms require a lot more than just reference data to come up with what regulators want. They will have to add transaction and position data before they make performance and risk calculations. Enter data aggregation.

DST Global Solutionse_SSRq Anova platform allows fund managers to pull the necessary information from multiple applications. Using a visual dashboard they can also drill down to all the information they want at a particular time interval. That data can then be fed into risk metrics and performance engines to make any necessary calculations.

"Users of data have different requirements," explained Des Gallacher, global head of data management and analytics solutions for DST Global Solutions, the Boston-based subsidiary of DST Systems, a specialist in fund management software. "Chief executive officers want high-level information on top and lowest-fee-generating clients to analyze revenue at risk, while client relationship managers want detailed customer information around exposures, performance and risk. Regulators may want a variety of risk reports for a particular timetable."

Consolidating data from disparate sources will also become critical for hedge fund managers that may have to register with the SEC. To fill out Form ADV, the initial form required for registration, and Form PF, a more detailed form filed after registration, advisors will need to come up with counterparty and market exposure, and leverage.

"A data warehouse can aggregate the data, but if the advisor is using Excel spreadsheets, it will need to designate individuals to ensure it's accurate and inserted in the right sections of forms," said Marshall Saffer, chief operating officer for MIK Fund Solutions, a New York-based hedge fund software firm. "The data warehouse also allows the fund manager to offer regulators-and investors-snapshots of their exposure at a given time period."

Nowhere is the need for solid data management practices more critical than in pricing over-the-counter and non-exchange traded financial contracts for central clearing. Fund managers must value their contracts correctly so they can post the correct initial and variation margin with their clearing agents They must also be able to withstand a regulatory audit. One answer now being espoused by some fund managers: electronically document the methodologies and procedures used such as market data sources and pricing models.

Being able to accurately capture the data points that represent the underlying contract and how it is traded will also go a long way to accurately calculate risk exposure, according to Ebbe Kjaersbo, chief business consultant in North America for SimCorp, a technology firm specializing in investment managers. SimCorp's Dimension platform captures data from all of the entities involved in the OTC derivative trading and clearing process-including the counterparty, clearinghouse and issuer. As a result, the entire fund firm can use exactly the same data with all positions and transactions for all instrument types in a single consolidated database.

Subscribe Now

Access to premium content including in-depth coverage of mutual funds, hedge funds, 401(K)s, 529 plans, and more.

3-Week Free Trial

Insight and analysis into the management, marketing, operations and technology of the asset management industry.