SCOTTSDALE, Ariz.—If you were to give the average financial institution a grade on its ability to acquire, manage and use data, it would be a “50 out of 100.”
That’s the conclusion of Cornerstone Advisors’ new Improving Your Financial Institution’s Data IQ report, which finds that banks and credit unions have made progress in governing and organizing their data, but still have significant gaps to close before they can fully leverage new technologies like artificial intelligence.
Correll Davis, senior consultant at Cornerstone Advisors, said the firm’s assessment methodology—designed to measure “Data IQ” across five key categories—found that even the highest-scoring areas fall short of excellence. Data governance topped the list with a score just over 50, edging out customer data by a single point. Market data was the weakest area, with an average score of 45.
“There’s a lot of excitement around AI-based tools and platforms, but many institutions aren’t taking the first step of looking at how well they’re actually managing the data they already have,” said Davis, who co-authored the study with Cornerstone Chief Research Officer Ron Shevlin. “A lot of the time the data management fundamentals just aren’t where they need to be.”
The stakes are high. Cornerstone estimates that future spending on data initiatives will total between $1 million and $2 million annually for every $1 billion in assets—an investment that demands active oversight from every leader, not just IT, if institutions are to see meaningful returns.
The Silo Problem
Davis said the most common weakness among low–Data IQ institutions is the inability to connect siloed systems. For example, a credit union’s lending department might excel in using data to drive decisions, but that intelligence rarely flows to other units, like deposits or marketing. Without the tools—or the strategic intent—to combine these disparate data sets, institutions miss opportunities to identify trends and insights that span the entire organization.
In contrast, high–Data IQ institutions both manage individual silos well and integrate them seamlessly, he said.
“They’re using data lakes, warehouses, or business intelligence tools that bring together all their sources,” Davis explained. “That allows them to get a holistic view of members or customers and make more informed decisions.”
While the survey covered both banks and credit unions, the report did not break out scores by institution type. Davis stressed that the path to improvement is similar across the board. The key takeaway: resist the urge to simply purchase the latest technology and expect it to fix underlying issues.
“You can’t just buy a new platform and think it’s going to solve all your problems,” Davis said. “Leaders need to work through what they have today, define clear business use cases, and modernize existing tools first. Then they can make strategic moves forward.”
The message from Cornerstone’s research is clear—before financial institutions can become data-driven innovators, they need to double their “Data IQ” by breaking down silos, tightening data management practices, and building a strong foundation for future technology investments, Davis added.
The report lists steps to take to become a high data IQ organization:
- Make Data Strategy a C-Suite Priority – Leadership must champion data governance and design, not just leave it to IT.
- Start With Outcomes – Define the reports, insights, and business improvements you need before building repositories.
- Streamline and Sync Repositories – Minimize data silos, ensure repositories are synchronized, and eliminate spreadsheets as sources of truth.
- Standardize Language – Create and enforce a data dictionary to unify nomenclature and formatting across systems.
- Build a Culture of Data Integrity – Hold every employee accountable for accurate, up-to-date data.
- Leverage Outside Expertise – Use vendors or consultants to speed complex implementations, transfer skills to internal teams, and maintain modern governance tools.
- Choose the Right Build Model – Weigh internal vs. vendor solutions; a hybrid approach often balances control and capability.
- Plan for Exit and Autonomy – Ensure vendor contracts allow full access to the organization’s data and enable internal teams to take on more responsibility over time.