Seeking the Path to Data Quality

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Trying to produce quality data requires a complex, intertwined effort comprised of making standards compatible and moving to more advanced data management methods. Achieving this result, however, is necessary for current regulatory compliance challenges

Inside Reference Data regularly covers ongoing developments in standards and regulation. This month, among other areas, we delve into data quality—the reason for and end goal of all the standards being developed and debated.

Nicholas Hamilton, who has joined Inside Reference Data as a reporter based in London, speaks with Llew Nagle, head of consumer service management for reference data at Deutsche Bank. Nagle tells us that with ISO 15022, ISO 20022 and XBRL competing for acceptance, the industry cannot see standards as a catch-all solution for data communication issues. More descriptive codes, including country codes and currency codes, are necessary, he says.

As Bill Meenaghan, a product manager at Omgeo, relates in this month’s Industry Warehouse, data accuracy—in this case with settlement instructions—can increase a firm’s ability to comply with market standards and best practices. This shows a direct through-line from data quality to regulatory compliance, and thus, possibly, to more reliable and trustworthy markets.

This may be easier said than done, of course. Data quality can also depend on compatibility, as Adam Honoré, research director of the institutional securities practice at Aite Group, pointed out in a recent conference call. “Everybody has their own keys. Some are using Cusips or ISINs. Some have proprietary keys such as RIC or BIC codes,” he says. “I don’t think there are incentives from the key data suppliers to have a consolidated solution. It’s a tough road.”

While at Sibos, I heard from Meenaghan’s colleague, Tony Freeman, director of industry relations at Omgeo. As recounted in an online “Editor’s View” following the conference, Freeman wonders about the financial industry’s inability to arrive at one set of standards as other industries do. Those managing data are contending with how to identify it and where it all goes. With the various code types Honoré cites floating around and the messaging standards competing for acceptance as Nagle sees, it will be a minor miracle if anything gets done at all.

If universal compatibility is key to achieving quality data, accuracy may only be half the battle. Enterprise data management (EDM) is said to be a more accurate and faster means of managing data than mature data strategies still in use at many firms, as described in the special report attached to this issue. The EDM Council, which pursues identifier standards, classification schemes and contractual definitions for financial securities, went to Basel last month to lobby the G20 to accept the US definition of the legal entity identifier. If markets worldwide can agree on this identification standard, can they follow the same path to data quality?

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