Finding Proactive Advances
Features in the June issue of Inside Reference Data focus on innovations and advances in data management
At times, it may seem that most of what data managers are hearing about, and gets reported here, is about how financial data operations can contend with problems, challenges or obstacles, whether due to regulatory demands or limited resources. This can be useful for those who need ideas about how to address certain data management issues, but sometimes it can be refreshing to hear about ways that data operations managers are innovating or making improvements for their own sake, as a model for what to aspire to when managing data.
This month, some of our stories contain this kind of outlook. This begins with "Teaching the Machines," our "Interview With" feature, in which WorkFusion executive Adam Devine speaks with Joanna Wright about how artificial intelligence is being applied more often in data management, both by his company and others. WorkFusion now offers a machine-learning algorithmic solution for corporate actions, customer onboarding and standing settlement instructions.
Eventually, automation of tasks such as extracting information from press releases about corporate actions will be commoditized, Devine believes. "It used to be a competitive differentiator for big financial service businesses to be able to access certain data," he says. "It's businesses like ours that are automating this work and fuelling this trend."
While not as flat-out innovative, improvements in data governance planning, partly through new ways of working with metadata, also represent a positive advance for data management. In "Governance With Confidence," executives like Citi's Julia Bardmesser and TIAA-CREF's Joseph Spinelli are applying standardization and organization techniques, including the use of metadata, to track data and avoid duplication. TIAA-CREF, Spinelli says, looks to find correlations between the investments and the demographics of investors in its funds. Metadata, and fine-tuned definitions for data, are used to discover those correlations.
Just as data governance planning is an established concept that is seeing such new ideas and methods, managed services is becoming a more carefully considered proposition, with firms deciding just where they want to be on a continuum ranging from accepting a utility, unchanged, to customizing the parts of the service they will receive. In "Management Choices," Brown Brothers Harriman's Sheila Tully relates how the firm used GoldenSource to manage its records in response to client requests, rather than going with a completely managed service. Taking advantage of mutualization through a utility has economic benefits, as SmartStream's Joseph Turso says, and also offers more consistency. Executives speaking in this story make clear that managed services now have a pre-requisite or preliminary step—choosing just how managed a firm wants those services to be.
Innovation, however, is not without its hurdles, and sometimes takes a winding path. This issue also accounts for that in "Cracks in the GLEIS?", a report on potential data quality issues with the legal entity identifier, a data concept that looks like a positive change for the industry in many ways, although it has had a long gestation period. We hope you find all these reports give you useful examples and models for data management work.
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