Your SEO optimized title page contents
Ask About Our Solutions

Buy-Side Firms Have Many Questions on the Road to Data Harmonization

In recent months, there has been significant progress seen in data management through cohesion in business support and more focused allocations of systems and resources. New and ongoing regulatory compliance and standards efforts will continue to affect data operations, but they will also push buy-side firms to innovate data harmonization efforts. In turn, this will drive data management approaches to become the most important aspect for all buy-side asset management firms.

Following the implementation of regulations at the start of the year, many buy-side firms now wonder what affect data management systems will have on their data operations. Here are some of the hot button issues for the rest of 2016:

“Firms still wonder about the affect of data management systems.”

Why do firms use enterprise or master data management? And do they need to be integrated?
Both enterprise and master data management systems are most commonly used by asset management firms to centralize financial data records. One of the reasons why firms prefer enterprise data management systems is that while they can minimize flexibility, they can also continuously improve technology. Further, firms use enterprise data management systems as consortia systems to break down proprietary data protectiveness and facilitate centralization.

Similarly to enterprise data management systems, master data management systems are also commonly used to integrate financial industry records. While one of the criticisms on master data management systems is that the currentness of the data can vary due to the large amount of data collected into one file, they also have the potential to streamline data sharing.

However, many industry experts say that the harmonization of enterprise data management systems and master data management systems is the next evolution. Both the data management industry and buy-side firms should focus on breaking up and reducing silos due to different lines of business that restrict the quality of data. This ability to federate and manage several databases simultaneously is now the norm, so the focus should be on the development of expanded data models that enable reuse of the same data for compliance reporting and risk management.

Are enterprise data management systems really prone to data quality issues?
There is a misconception that enterprise data management systems are prone to issues with data quality and management. The reality is, though, these issues are more based on user errors and a firm’s culture of data consciousness, compliance and control. So as firms are emphasizing data governance and qualitative factors, users will all need to be trained in how to use enterprise data management systems and how these systems contribute to continuous monitoring and recalibration for all financial and regulatory reporting platforms.

What regulations will have biggest impact on data management operations this year?
The Markets in Financial Instruments Directive (MiFID II) has become one of the regulations that will spur innovations in complex and multi-faceted data management for many buy-side firms in Europe. As Solvency II has captured the headlines recently after its implementation on Jan. 1, MiFID II has continued to have a tremendous impact on data management. This is due to the fact that it is wider-reaching and more stringent than regulatory requirements like the U.S. Dodd-Frank Act.

The content provided in these articles is intended solely for general information purposes, and is provided with the understanding that the authors and publishers are not herein engaged in rendering regulatory or other professional advice or services.  Consequently, any use of this information should be done only in consultation with qualified legal counsel.  The information in these articles was posted with reasonable care and attention.  However, it is possible that some information in these articles is incomplete, incorrect, or inapplicable to particular circumstances or conditions. We do not accept liability for direct or indirect losses resulting from using, relying or acting upon information in these articles.

Want to find out more?

If you have any questions about our thought leadership content, please get in touch.