Enhancing Data Governance in the Age of Automation

As data becomes the cornerstone of financial operations, the importance of governance and risk management has increased exponentially. Recent regulatory fines have shown that regulators expect firms to have strong data governance practices. One recent case revealed how inadequate supervision over data integration from third-party sources led to inaccurate pricing on customer statements and regulatory reports, emphasizing the critical role of sound data governance across the financial sector.

As financial institutions navigate an increasingly complex environment, automated data solutions that ensure accuracy, consistency, and transparency have become essential partners in modern data governance.

Risks of bad data governance in today’s complex environment

Timely, accurate, and reliable data is essential for each part of an organization’s value chain. The downstream impacts of inaccurate data coming from a security master system, or a "golden copy" can snowball quickly as they work their way into back-, middle-, and front-office applications. Routine tasks compound and become increasingly difficult to unwind as time goes on.

In the back office, inaccurate data can lead to failed trade settlements, errors in financial reporting, and regulatory violations. Middle-office operations, like risk management and portfolio valuation, may misrepresent exposure due to flawed data. In the front office, poor data accuracy affects trade execution, client advice, and order routing. These cascading impacts underscore the need for accurate, reliable data to maintain operational integrity and protect an institution’s reputation.

Modern data governance frameworks: the role of DCAM, EDM, and COBIT 

The increasingly complex data management risk environment has provided fertile ground for the emergence of modern data governance frameworks like the Data Management Capability Assessment Model (DCAM), Enterprise Data Management (EDM) objectives, and Control Objectives for Information Technologies (COBIT) have emerged to help financial institutions manage data comprehensively.

DCAM, developed by the EDM Council, assesses and enhances data management, particularly for institutions handling complex datasets such as third-party market data, pricing, and reference data. It establishes controls over data quality, governance, and architecture to ensure accuracy and consistency.

COBIT, created by ISACA, focuses on IT governance, aligning market and pricing data systems with risk management and compliance goals. EDM objectives serve as the foundation for decision-making and risk management, making data easier to access and analyze.

Together, COBIT and EDM objectives enable organizations to align IT with business goals, enhancing data quality and operational resilience.

EDM platforms as foundations for technology solutions in corporate governance

Implementing new data governance frameworks successfully heavily depends on the stability of an institution’s Enterprise Data Management (EDM) system. These platforms are critical to holistic data governance across an institution, providing a centralized, validated “single source of truth” across an organization. This foundation ensures data integrity, eliminates redundancies, and supports regulatory compliance and operational efficiency.

Market data providers play a key role by supplying high-quality, standardized market pricing and reference data, forming the foundational “golden copy” of the security master. By integrating data from multiple sources, EDM platforms can deliver accurate, consistent data across departments, supporting corporate governance standards.

Automated workflows from these providers enhance the early stages of the data lifecycle, ensuring that data entering EDM platforms is compliant and timely. This automation reduces manual intervention, minimizes errors, and enables seamless data flows, aligning with regulatory frameworks such as DCAM and COBIT.

With this EDM foundation, institutions can integrate cloud-native platforms to enhance scalability, security, and data accessibility. These advanced solutions enable the use of analytics and AI for better insights, compliance, and decision-making.

Limitations of legacy providers of market data pricing and reference data

As noted, market data providers play a key role the success or failure of the performance of an EDM system operating in a modern data governance framework. However, the stresses of today’s data demands have exposed the inefficiencies of the old guard of technical debt-laden, file-based and/or terminal-based systems, which have long dominated market data delivery.

Challenges like manual data reconciliation and price verification to inefficiencies in managing security pricing updates, exception handling, and regulatory reporting are compounded by the rigidity of legacy systems.

The DNA of new market data providers rising to meet governance needs

New entrants into the market data space are pushing the pace of innovation and support the move towards modern data governance frameworks. 

Some of the ways in which these new entrants are setting a new standard include systematic multi-source data validation, automated cross-checks, and real-time quality assurance. The “gold-standard” security master reconciles data across vendors with unique symbologies, ensuring consistency and reliability before it’s used by EDM platforms or other systems.

By multi-sourcing, an organization selects the best data source based on quality, automatically switching to a backup source if needed. This process maintains data completeness and reliability, a core component in modern data governance frameworks.

New tools available today enable organizations to create customized governance workflows aligned with corporate standards. These automated workflows cross-check and certify data, reducing manual error, enhancing compliance, and meeting each department’s specific needs.

Emerging technologies not only support compliance with governance frameworks, but also meet client demands for fast, accessible data. By automating data stewardship and validation, they can be a key partner to help institutions reduce manual tasks, focus on high-value activities, and reinforce regulatory compliance.

Trust in data as the cornerstone of modern data governance

Data and corporate governance are now intertwined, with effective data governance ensuring that decision-making aligns with an organization’s governance framework. Both work to maintain compliance, manage risk, and enhance transparency, supporting broader corporate objectives. This shift means that data governance goes hand in hand with building trust among employees, customers, and regulators.

As institutions modernize data governance, they are not only cementing trust across the organization but are also unlocking data’s strategic potential. Advanced third-party data solutions are poised to plat a significant role in this transformation, supporting compliance, driving efficiency, and opening new avenues for growth.