News Stay informed about the latest enterprise technology news and product updates.

Poor reference data management causing headaches in financial sector

Regulatory pressures and the need to improve data quality are forcing financial institutions to rethink their reference data management strategies.

About 62% of financial institutions plan to “extend or customize” their reference data management strategies over the next two years, a new survey has found.

The survey of 107 reference data professionals from banks and financial services companies around the globe revealed that financial organizations planning to update reference data management strategies are doing so primarily to improve overall enterprise data quality and reduce risk of exposure to new and changing regulatory compliance mandates.

The survey, which was conducted by IT outsourcing and reference data management provider iGATE Patni in conjunction with Inside Reference Data magazine, also found that to a lesser extent, organizations are planning to update reference data strategies to improve operational efficiency and increase customer satisfaction levels.

Reference data is most often described as information that is used by an application, but does not originate within that application. For example, reference data could be data that is purchased from an external source and fed into on-premises systems—such as real-time stock market transaction data. Reference data might also be a product master list that a customer relationship management application refers to as it completes a function.

Survey respondents said one of the biggest obstacles to successful reference data management is making the most of budgets. Many spend too much money acquiring reference data and not enough money maintaining its quality, consistency and usability over time, according to Fred Cohen, group vice president and global head of the capital markets and investment banking practice at iGATE Patni.

Cohen said that “siloed” reference data management practices—where multiple departments within large organizations can end up purchasing the same information repeatedly—is another example of money being wasted.

“It’s just very inefficient,” Cohen said. “We’ve met companies that are spending $200 million-plus a year buying reference data and they’re wasting about 25% of it.”

For more on reference data management

Learn how The Dodd-Frank Act is affecting data management strategies

Read about the differences between master data management and reference data management

Learn about the data security implications of financial services regulatory reform

Regulatory pressures lead to new thinking
Regulatory pressure stemming from the Dodd-Frank Wall Street Reform and Consumer Protection Act and several other new regulatory mandates is prompting many organizations to rethink their approach reference data management and data management in general, agreed Andy Hayler, president and CEO of The Information Difference Ltd., a UK-based information management research and analysis firm.

“If you look at the industries that are really heavily into things like master data management and data governance, a very significant chunk of those are financial services companies,” Hayler said. “And I think one of the reasons [for that is] the regulatory pressure.”

Financial services firms are also rethinking data management practices to reduce the chances of taking on too much risk when investing in other companies. Hayler said inconsistent data can make it difficult to understand how much risk is involved in doing business, particularly when dealing with large organizations that have many subsidiaries.

“Counterparty risk is a big driver [because] there are issues related to whether you are really confident that you know the hierarchies of companies,” Hayler said. “Are you really sure that this company is not owned by this other one, even if it’s two or three steps removed?”

Improving reference data management practices
One of the keys to properly managing reference data is maintaining a thorough understanding of its lineage—where it came from, where it is being used and how it is being manipulated throughout the organization, according to Cohen.

“Once their data comes in from the vendor, most completely lose track of who is using what data and how much of it,” Cohen said. “Not only are they losing the data governance but they’re losing control of their data spending.”

Taking the time get a handle on how reference data is being used across business units can also give organizations the tools to save money over time, Cohen said.

“If they don’t have the knowledge of who is using what, they won’t have any ammunition to go back and renegotiate their reference and market data contracts,” he said. “You need to know where you’re coming from before you can figure out where you’re going.”

Dig Deeper on Data quality techniques and best practices

Start the conversation

Send me notifications when other members comment.

Please create a username to comment.