The Value Of Sharing

Stories in the July issue of Inside Reference Data report that data operations professionals are saying they are seeing the industry try new ways of handling data, or at least make significant alterations to existing systems and methods. Or these professionals are trying to achieve such changes themselves.

The purpose of data management operations should be enabling the fastest and best decisions, data scientist Hashmat Rohian of Aviva Canada tells us in "Context Clues." He advocates moving away from dependence on the familiar resource of Excel spreadsheets to organize and work with data, and moving toward whiteboarding, process mapping and graph databases as more effective means of processing and managing data.

Speaking of innovation in data processing, Inside Reference Data has covered the concept of crowd computing, as notably practiced by WorkFusion, before. But respected managers from Goldman Sachs and HSBC are starting to consider the practice, in which data processing tasks are split into small segments, each to be done by individual workers linked online. In "Wisdom of Crowds," HSBC's Julia Sutton says that for crowd computing to take hold, it will still have to be managed by firms' own data groups. Goldman Sachs' Gururaj Krishnan noted that only about a quarter of know-your-customer requirements can be automated, suggesting that crowdsourcing might be difficult to adopt. Nonetheless, as Sutton acknowledges, risk data aggregation principles mean some changes must be made.

In "Alternative Paths," executives from State Street, CIBC and other firms discuss a few possible ways to improve data management - starting with "breaking orthodoxy" in policies, procedures and systems, as State Street's David Blaszkowsky says. Just as Rohian pointed to "next best actions," CIBC's Christine Knott talks about centralization, both of data and personnel separated in silos. That's needed to support the ability to take the best possible action in investment management or trading.

In our Industry Warehouse column, consultant Rares Pateanu points to another means used to bring data and personnel together: enterprise-wide agreements made in the wake of the 2008 crisis to set the meaning for business entities, the way metadata and data repositories would be shared, and, also, centralization of data governance processes - which is exactly what firms' executives related in the aforementioned story that they are still trying to do.

Similarly, in the separate discipline of pricing, transparency is high on the agenda of firms looking to get a better handle on pricing data, as firms and service providers said in a webcast recounted in "Full Disclosure." To carry out transparency, sharing information also comes into play, as HSBC's Anthony O'Connor observes in this story. Vendors are happy to share, but when processes include proprietary techniques, sharing becomes more difficult, he said.

So, in a range of aspects of data management, it's becoming more apparent that old, established ways of handling data may no longer be appropriate or sufficient to produce the necessary analysis and insights for the financial industry. Firms have to be open to a little more sharing of expertise both internally within business units and externally to take advantage of capabilities like crowdsourcing, even as they still protect proprietary interests and information.