Season 2 | Ep. 51: Part 2 | Using Data As A Strategic Asset With Jeff Fink, Lumio Insights

In today’s fast paced, data-driven world, effective governance has emerged as a cornerstone for success. For financial institutions, data is more than a resource—it’s a strategic asset. However, harnessing its full potential requires a robust framework (discussed on a preview episode here) to ensure quality, compliance, and accessibility. Jeff Fink, CEO and Cofounder of Lumio Insight joined the Risk Intel Podcast with Ed Vincent to explore the critical components of a successful data governance framework, identify the roles responsible for maintaining standards and policies, and discuss the ideal time to start implementing these practices. Whether your institution is just beginning its data governance journey or looking to refine its approach, these insights will help set you on the path to success. Listen to the full episode or read the summary below to learn more:

The Critical Components of a Successful Data Governance Framework for a Financial Institution

Effective data governance is foundational for financial institutions striving to manage their data as a strategic asset. A robust data governance framework encompasses several critical components:

• Data Ownership
• Data Stewardship
• Data Quality
• Data Integrity

These pillars ensure that the institution's data is not only accurate and complete but also secure and compliant with regulatory requirements. Jeff emphasizes the necessity of audit trails, data classification, and retention policies to safeguard data and maximize its value.

“I love these 3 terms: complete, accurate, and organized…that’s what we want to say when we’re creating definitions of what valid data is within an organization… to make sure we can get a as much value out of it [data] as possible” - Jeff Fink, CEO and Cofounder of Lumio Insight

One key aspect of data governance is the automation of processes like data ingestion, retention, and deletion. Automation ensures that data retention policies are consistently followed, eliminating manual errors and inefficiencies. Jeff highlights strategies such as rolling snapshots for daily, weekly, and monthly data, which enable institutions to keep only what is beneficial while complying with regulatory standards. This approach not only optimizes analytics but also ensures that redundant or non-strategic data is efficiently managed.

Standards and Policies: Who's Responsible

Establishing and enforcing standards and policies is essential for successful data governance. Within a financial institution, this responsibility often lies with data owners and stewards. Data owners set the strategic direction by defining what data is critical and ensuring alignment with business objectives. Meanwhile, data stewards manage the day-to-day processes, focusing on data quality, access, and compliance. This dual role ensures that policies are not only set but also operationalized effectively.

“A data governance committee can really set the direction and the vision of what to do”

Jeff also underscores the importance of building robust processes for data retention, quality, and classification. These processes should align with an institution's overall architecture, including structured storage systems like data warehouses for optimized reporting and data lakes for long-term compliance. Properly assigned roles and clear standards facilitate collaboration across departments, fostering a culture of accountability and continuous improvement. Ultimately, this framework empowers institutions to unlock the full potential of their data while adhering to regulatory and strategic requirements.

When Should People Start Thinking About Data Governance?

For any bank or credit union, the best time to start thinking about data governance is as early as possible. Ideally, governance frameworks should be established before significant data processes are in place. As Jeff suggests in this episode, “Let’s build the guardrails first and then build on top of them.” However, he acknowledges that many organizations may already be operating without these foundational frameworks. In such cases, it's never too late to implement data governance.

Starting where you are and incrementally building a governance structure is a practical approach. Institutions can adopt a phased strategy, beginning with their current data architecture and progressively enhancing it to meet governance objectives. The goal is to create a scalable framework that evolves alongside the organization, ensuring robust controls, compliance, and the strategic use of data assets. Financial institutions that prioritize data governance early—or make it a priority now—position themselves to leverage data as a key competitive advantage in an increasingly data-driven industry.

Data governance isn’t just a compliance measure; it’s a strategic imperative for financial institutions looking to thrive in a competitive landscape. By establishing a solid framework, defining roles and responsibilities, and implementing automated processes, organizations can unlock the full potential of their data. Whether starting from scratch or refining existing practices, the message is clear: it’s never too late—or too early—to prioritize data governance.

‍Begin today, and ensure your data serves as a powerful tool for informed decision-making, regulatory compliance, and long-term growth.

Schedule time here to connect with SRA Watchtower or Lumio Insight to learn how.