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The leading knowledge platform for the financial technology industry

A-Team Insight White Papers

A Model for Data Governance – Does Your Organization Really Have One?

The current focus on new regulations, and their impact on risk management practices, has turned the attention of financial institutions to data. It is increasingly evident that accurate and consistent data is key both to compliance with incoming regulations and to reaping the benefits of a robust risk management strategy.

Business managers have come to the realization that data is an asset that can be turned into a strategic advantage. By tapping into their data assets, savvy business heads are transforming what was once the long-forgotten poor stepchild of the financial enterprise into a weapon that can be wielded to boost profits, streamline operational processes and meet the stringent needs of new regulation, whatever shape it eventually takes.

The complexity of today’s financial institution, however, presents data managers with unsurpassed challenges, making data consistency, standardization and timely processing difficult to achieve. The spate of mergers and acquisitions in the wake of the Credit Crunch has also left many firms with multiple security masters, multiple entity identification databases and multiple approaches to managing them.

Achieving the twin aims of regulatory compliance and operational competitive advantage is possible only where a true data governance model is in place to ensure that all stakeholders understand the goals, methodologies and deliverables of the data management strategy. For many institutions, implementing such a model is a daunting prospect that, even if it’s possible to put in place, may take years to do so. Many others believe they have a model in place, when they clearly do not.

What can firms do to prepare their organizations to adopt a data governance model that will help them achieve their data management aims? What are the key considerations of such a model, and where can they get help in setting the main cornerstones in place?

This paper attempts to answer these questions, and offers some straightforward next steps toward implementing a robust data governance model.