Is Your Data Governance Evolving?

April 11, 2012

With the increasing regulatory environment and impending changes brought on by Dodd-Frank, we have seen countless articles discussing the growing importance of data governance throughout the financial services industry.  The pressure is on to not only ensure compliance, but also to put strong policies in place to proactively prevent any chance of data corruption. 

In a recent article titled  “From Chaos to Nirvana in Data Governance Evolution” from the Tabb Group (read full article here,  free registration is required and recommended), they discuss their Data Quality Management Maturity Model (see below) and how firms must evolve from a Reactive state of data governance to a “Predictive” process – which they call data governance “nirvana”.

 

Figure 1: Data Quality Management Maturity Model from Tabb Forum (click on diagram to enlarge)

While we would argue that few, if any, firms are successful at developing Predictive capabilities, it is important that all organizations are striving for and planning to achieve what the model calls the Proactive phase.  This is where data management goes from identifying and reacting to breaches after they happen to taking preventive measures and continuously enhancing data quality. 

Working with global asset managers of all sizes, we constantly hear concerns about the increased requirements of data governance and management.  As the investment accounting system is often the gathering point of data and the delivery point of information going out to end clients, strong policy adherence and automation are key factors to moving data governance to the Proactive phase. 

We address this for our clients with a number of configurable modules that help customize their processes and adhere to their organization’s policies.  For example, our DataTrails module is a robust auditing application that tracks data changes and the parties responsible for them and our Automated Import Manager (AIM) both automates all imports into the system and incorporates an extensive business logic layer that identifies import logic errors before they occur.  In addition, the latest version of our eReports reporting tool has built in workflow processes that put the appropriate checks and balances in place to increase the accuracy of reporting to the end client (see related blog).

While the “Nirvana” state may be more of a vision and perhaps even a dream, every financial services organization needs to be continuously working toward a Proactive method of data governance.  By building this into the system solutions and the organization itself, investment management firms will gain the trust and confidence of their clients and continue to win business over their competition.

Where is your firm on the Data Quality Management Maturity model?  Do you have the tools and systems available to keep your operations evolving?

-Claudine Martin, Product Marketing

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