The need for data governance systems in financial institutions

Data has become as complex as it is vital to a financial institution’s success. Asset management firms rely on the accuracy, quality and correlation of their data for trading, accounting and risk mitigation. This is particularly true now, as firms seek out more and more data – having irregular or unstructured data management processes can significantly restrict the usability and access to their data, which caps the value they can derive from their data. Simply put, the integrity of data governance systems is more important to financial institutions than ever.

“The integrity of data governance systems is more important than ever.”

Most firms find data governance to be a headache
Data management approaches have been a staple for asset management firms for decades now. However, data governance has only come to the forefront of priorities for financial institutions in recent years. This is not to say that these firms have not recognized the need for data governance, or that it may be a firm’s chief asset in itself.

According to a survey by WatersTechnology, 80 percent of executives surveyed felt that data is a vital asset, but 60 percent had not implemented data governance infrastructure. The fact is that despite the growing need for data governance, many executives view the process of implementing such a program as a large-scale undertaking. Many firms actually go to great lengths to ensure data storage infrastructure, but they have not taken steps to enhance the accuracy, quality and correlation of their data.

One of the primary reasons for these failures to implement effective data governance programs is that data pertains to all business units in a firm. The process of effective data governance is a rigorous – and transformational – business alignment. To implement such a program, a firm needs strong executive supervision, because data governance requires collaborative workflows to breakdown informational bottlenecks in an institution. Further, firms need the technologies and support infrastructures in place to synthesize data sets in a way that they can be effectively managed and monitored across all business units. These technologies need to support capturing and visibility for massive amounts of new data sets entering the systems. On top of all that, a firm needs to implement these data governance systems so that they improve the quality and accuracy of the data captured.

This is no small feat, as many executives of smaller asset management firms and financial institutions either feel that they do not need transformational data governance systems, or if they do, they do not see the necessity in having a Chief Data Officer to oversee it. A data officer at the executive level should be a requirement for all firms, not simply larger institutions with the liquidity and capability to install this level of technology personnel. Chief data executives are the coordinators of data sets across all business units and the primary point of contact for the quality of a firm’s data.

The need for stronger data governance systems
Data governance is essential for financial institutions because it meets the core values of minimizing risks and improving business intelligence. Effective data governance systems not only align both of these fundamental objectives, they mitigate risks associated with regulatory and financial bodies as the result of inaccurate, low-quality data. Further, according to a Worldwide Business Research report, best-in-class data governance systems also enable firms to pursue new business opportunities with more well-informed decisions. Ultimately, data governance is not only a valuable asset to a firm, it is its most important asset.

A prime example of a financial institution that realized the value of data governance was JPMorgan Asset Management. The firm’s managed data solutions left it in a position of interpreting its data rather than having accurate information. There was no single, concrete truth to its data sets. For instance, the firm was encountering issues with different ROI rates for the same securities. According to a WatersTechnology interview with Scott Burleigh, executive director at JPMorgan Asset Management, this led to a massive amount of duplicated data, not to mention the risks involved with several disparate responses to the same questions.

“Client guideline management – investment mandates about what to include in portfolios, risk management requirements, limits, counterparty instructions – impacts our data strategy and drives our data needs more than anything else,” Burleigh explained. “And clients are watching us like hawks – even more so since the crisis. For example, we used one data source to value an asset, and our client used a different source and thought we were out of compliance.”

Data is the lifeblood of all financial markets.

Data governance needs to be stronger and more structured
Data is the lifeblood of all financial markets. However, for some executives, the value of data is just one of the top five costs for financial institutions after wages and building expenses. But according to a separate WatersTechnology interview with Klay Stack, CTO at Marathon Asset Management, many C-level personnel are starting to figure out that it should be the top priority of every firm because it holds all of their proprietary information.

“For us, data is strategic, Stack stated. “It doesn’t just sit there and accumulate; it’s a living organism that will grow and become more important. Because the more data you have, the more challenges you have maybe even for smaller firms like us. And those responsibilities will always be there.”

If buy-side firms seek effective risk management, they can benefit greatly from using managed data services. They must be willing to take on risk, incorporate initiatives to limit these difficulties with strategic plans and, finally, leverage a proactive approach.

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