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. Highlighted by this summer’s FINRA fine against a major U.S. broker-dealer, regulators expect firms to ensure accurate data through sound data governance. In this case, FINRA levied fines against the broker-dealer due to data governance failures that led to incorrect pricing data being reported for several years. The flaws in data management resulted from inadequate supervision over systems that integrated and processed pricing information from third-party sources, causing inaccurate pricing on customer statements and regulatory reports.

The complexity of modern financial markets demands that market data solutions go beyond traditional data governance practices. As financial institutions navigate an increasingly intense regulatory 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

Bad data can have a ripple effect across the entire value chain. Timely, accurate, and reliable data is essential, from operations to decision-making. For example, Gartner reported that, in 2023, the average annual cost of poor data quality to organizations was around $12.9 million, underscoring the significant financial risks tied to inadequate data governance.

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. The snowball effect across these layers of operations increases the potential for financial losses and reputational damage as issues become harder to detect and resolve.

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

Modern data governance frameworks such as the Data Management Capability
Assessment Model (DCAM), Enterprise Data Management (EDM) objectives, and Control Objectives for Information and Related Technologies (COBIT) have emerged in recent years to help financial institutions rethink their data governance programs in a unified and holistic way. These frameworks provide the foundation for effective data management, but their success hinges on the quality and accessibility of the market data being used.

Modern frameworks like DCAM, EDM objectives, and COBIT provide financial institutions with tools to address these challenges in a structured way. DCAM, developed by the EDM Council, focuses on assessing and improving data management capabilities for complex datasets, such as third-party market data. COBIT, developed by ISACA, ensures that IT systems managing critical data align with risk management and compliance goals.

EDM objectives serve as the cornerstone for decision-making and risk management in the context of governance. While COBIT provides a structured IT governance framework, EDM objectives supply the specifics needed to manage data effectively, supporting decision-making and risk management. Together, they enable organizations to align IT systems with business goals, creating a governance model that enhances both data quality and operational resilience.

As financial institutions adopt modern data governance frameworks, the need for
advanced, automated data solutions becomes increasingly clear. Institutions that rely on leading third-party market data providers — like those offering cloud-native platforms — are better positioned to meet the stringent requirements set by these governance frameworks.

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. EDM platforms form a critical foundation in data governance by creating a centralized, validated source for standardized data across the organization. Acting as the "single source of truth," EDM platforms ensure data integrity and eliminate redundancies, essential for both regulatory compliance and organizational efficiency.

In many organizations, market data providers play a pivotal upstream role in supplying high-quality, accurate, and standardized market pricing and reference data, which is essential for establishing this “golden copy” of the security master. By integrating and validating data from multiple sources, these providers supply the foundational data on which EDM platforms rely. This approach supports data accuracy, enabling reliable, consistent data across departments from front to back office and aligning data governance with broader corporate governance standards.

Automated workflows from market data providers are critical in early stages of the data lifecycle, ensuring that the data entering EDM platforms is timely, compliant, and in alignment with regulatory frameworks such as DCAM and COBIT. This automation streamlines processes by reducing manual intervention, decreasing errors, and providing seamless, structured data flows to the EDM system.

With an EDM foundation established, organizations are well-positioned to connect to advanced technology solutions that support data governance goals. By integrating this centralized data with flexible, cloud-native platforms, institutions enhance scalability, security, and data accessibility while meeting stringent regulatory and operational requirements. Furthermore, advanced data processing and analytics capabilities enable institutions to leverage big data and artificial intelligence for improved insights and more comprehensive compliance measures.

A successful data governance framework combines robust EDM platforms, foundational data from market data providers, and adaptive technology enablers. This combination supports efficient data access, regulatory compliance, and real-time decision-making, creating a resilient governance structure across the institution.

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 resulting from evolving technology — from manual data reconciliation and rice verification to inefficiencies in managing security pricing updates, exception handling, and regulatory reporting — are compounded by the rigidity of legacy systems. Manual processes not only burden middle- and back-office teams but also expose institutions to risks of human error, slowing down critical decision-making and reporting.

Further exacerbating the issue, the inflexible pricing models of legacy providers force institutions to ingest massive amounts of unnecessary data, leading to inflated costs without corresponding value. This is particularly problematic in an era of margin compression, where the need for efficiency and precision is paramount. Financial institutions are overpaying for data they don’t need, while struggling to access the specific, actionable insights that drive growth and compliance, hindering them from implementing modern data governance programs.

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

QUODD’s approach to data governance emphasizes systematic multi-source data validation, with automated cross-checks and real-time quality assurance. The “gold-standard” security master reconciles data across vendors with unique symbology’s and identifiers, ensuring data is standardized, consistent, and reliable. This validation process is crucial for preventing errors that can arise from inconsistent or unverified sources, thus supporting regulatory compliance and operational precision. This is coming from the provider of the market data pricing; before it is consumed by the EDM or the new technology enablers.

By multi-sourcing, QUODD automatically selects the best available data source based on quality criteria. When primary data sources are unavailable or inconsistent, a backup source is seamlessly integrated, maintaining data completeness and reliability — a core component in modern data governance frameworks.

The QX Automate tool further enables organizations to create customizable data
governance workflows that align with corporate governance standards. These
workflows automate cross-checks and certification steps, reducing manual error and ensuring that each department’s specific data needs are met. Daily, automated workflows ensure essential data checks are completed, which enhances compliance, minimizes human error, and aligns data governance with broader organizational risk objectives.

Not only do emerging technology players like QUODD enable firms to be compliant with modern data governance frameworks, but they also help them meet client demand for better, fast-moving data that can be shared across teams and workflows. The shift towards a democratized data consumption model, where data can be accessed on-demand through an API-driven workflow platform, is becoming the new standard.

Automation of workflows shifts employee focus from repetitive tasks to high-value
activities like analysis, strong risk management and governance, and strategic decision making. By automating data stewardship and validation, financial institutions can reduce manual errors, accelerate decision-making, and reinforce regulatory compliance.

By prioritizing constant validation and multi-vendor cross checks, emerging solutions automatically update and reconcile data feeds from trusted third-party providers to avoid stale or incorrect data from entering the system. This ensures data accuracy and compliance are already being implemented to prevent issues before they become systemic. With these tools, data anomalies and discrepancies are flagged immediately, preventing “blind spots” in data governance protocols so that problems are addressed before they make it into the security master.

Trust in Data as the Cornerstone of Modern Data Governance

Data governance and corporate governance are deeply intertwined, as effective data governance ensures that the data used for decision-making aligns with the
organization's overall governance framework. Both work together to maintain
compliance, manage risk, and enhance transparency, ensuring that data-driven
decisions support the broader corporate objectives and ethical standards.
QUODD’s advanced solutions allow financial institutions to modernize their data
governance frameworks, underpinning regulatory compliance, operational efficiency, and corporate governance resilience. This shift is critical for firms aiming to enhance trust across employees, customers, and regulators in the modern financial landscape.

As financial institutions modernize their data governance, they are not only enhancing compliance but also turning data into a strategic asset which enables a firm to identify new revenue opportunities, maximize return on data investments, and respond more quickly to market demands.

Next generation third-party market data solutions will be at the core of this
transformation, driving efficiencies, supporting compliance, and creating new
opportunities for growth.