Golden Copy: Were They Right About 2015?

Data management for financial services did see incremental development, particularly in data governance planning, setting the stage for 2016 expectations

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Further development of data governance took place in 2015, as some predicted, but the data centralization called for in 2016 will need more work on governance to support its progress

Last week's column tried to predict what the major data challenges and management activity will be in 2016, based on industry leaders' and experts' views collected at the end of last year, an exercise Inside Reference Data undertook for the first time at the end of 2014. So it occurs to me that we should also look back at 2015 and consider whether the experts' thoughts were borne out over the course of the year.

Many of our experts the year before, from companies including ANZ Institutional Bank, BNP Paribas, Thomson Reuters, Rimes Technologies, Eagle Investment Systems, GoldenSource and HSBC, said BCBS 239, the European risk data aggregation guidelines, would receive—and require—a lot of attention. This regulation certainly did—last year started out with evidence of BCBS 239 driving data infrastructure changes, but continued with overall readiness to comply still lagging. So BCBS 239 remains a challenge.

The bigger question at this time last year, as identified by these experts, was whether reference data management advances would be incremental, if they happened at all. The development deemed most likely to occur was that data management technology would mature and the focus would center around integration of data sources and getting firms to establish data strategies or governance plans.

Last year, we found evidence that many firms were taking on data governance challenges. TIAA-CREF deployed an "acquisition and attrition" model. In that same story, Citi's Julia Bardmesser said data governance development helps support analytics and emphasized the importance of data standardization. Canadian firms, including TD Bank and Canadian Western Bank, found benefits from making data governance plans cross-functional.

As the year progressed, the industry also started to tie the idea of working on data governance to the need to address risk data management and regard data governance as a means to get a handle on data relevant to risk—in preparation for compliance with risk data aggregation guidelines. By the end of 2015, we were also hearing the industry's thoughts about what effect multiple data sources, and the need to reconcile those sources, can have on implementing data governance efforts.

This evolution in thinking about data management and data governance took more than an instant, although it did not take multiple years. Still, the challenge of centralization identified by experts looking ahead at 2016 means there still may be a lot more work to do concerning properly organizing data so that it can be beneficially managed by evolved and improved data governance plans.

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