Most organizations don’t realize they have a data readiness problem until they try to do something new with their data.
I’ve seen organizations invest heavily in modernization only to discover they’re still spending too much time finding and validating data. Many have more information than ever before yet answering a simple business question can still require significant effort.
Over time, these inefficiencies accumulate, and teams spend more time finding and validating information than using it to make decisions. Because every critical business function depends on trusted information, even minor friction points can have an outsized impact on performance.
Financial services, in particular, face unique obstacles in this area. Risk information resides in customer records and transaction data across the enterprise. As this data moves between core banking systems and reporting environments, complexity grows. Regulatory requirements and years of technology investments add layers that make information harder to access and harder to trust.
As organizations expand their AI ambitions, many find that these long-standing challenges can limit their ability to put data to work effectively. Before financial services CTOs can prepare for the next wave of innovation, they need to reduce the friction that prevents the business from fully using the data it already has.
Why hidden data friction undermines data readiness
Data friction often remains invisible during normal operations. Over time, organizations develop workarounds that keep business moving and become part of the process, making the underlying problem harder to see.
The result is often an organization with more data than ever, yet less confidence in its ability to use that data effectively. What begins as a minor inconvenience can gradually become a significant barrier to agility, making the true cost difficult to recognize until business demands expose it.
For financial institutions, the same challenges that limit AI initiatives can also complicate risk assessments and create blind spots around sensitive data. These barriers directly affect how quickly and confidently the business can respond to change.
That’s one reason security continues to dominate modernization discussions. In Rocket’s 2026 IT Leaders Survey, 69% of organizations rank data security as their top modernization concern, ahead of both cost control and innovation priorities. The finding suggests modernization slows down when people can’t trust the information they’re using.
Rising costs are also a consequence of insufficient data readiness. Nearly half (42%) of IT leaders are kept up at night by concerns about controlling costs, as they are expected to optimize expenses while funding innovation that delivers measurable business impact. Few have the luxury of choosing between efficiency and innovation. Instead, they are expected to deliver both simultaneously, often amid economic uncertainty and ongoing modernization efforts.
As expectations for speed, transparency, and security continue to rise, these obstacles become increasingly difficult to ignore. In an industry where secure and accessible data underpins every aspect of the business, far more than efficiency is at stake.
Where should financial institutions look for data friction?
Data friction tends to accumulate over time as information moves across the enterprise and through the processes that depend on it. For financial institutions, those points of friction often emerge when information needs to move across business, risk, compliance, and operational systems.
The difficult part is identifying where information gets stuck on its way from a business question to a trusted answer. In many financial institutions, friction arises when information flows between systems and processes, slowing the path from a business question to a trusted answer.
What does data readiness look like in practice?
When data is ready, teams spend less time searching for information and more time using it to make decisions. Trusted information is available when needed, without extensive reconciliation across systems or teams.
Too many organizations start with technology before they understand where the friction actually exists. The first step is understanding why teams are spending so much time reconciling information in the first place.
Accessibility remains a critical part of data readiness, with two-thirds (66%) of respondents identifying data accessibility for AI as a top modernization concern. Information that is difficult to access or reconcile creates the same operational drag as missing data. In financial services, where decisions depend on timely, trusted information, even minor friction can have outsized consequences.
Building a stronger foundation for modernization in financial services
Treating data readiness as an AI project misses the point. Organizations need trusted data to support risk management, compliance, customer service, and business operations long before they need it for AI.
In financial services, complexity is largely unavoidable. Operational resilience depends on meeting stringent compliance requirements while enabling secure, efficient access to sensitive data. While that complexity may never disappear, the unnecessary friction created by disconnected processes and siloed systems can.
Organizations that view data readiness solely as a technology initiative risk treating symptoms rather than root causes. Those that focus on reducing data friction across the business create a stronger foundation for modernization that supports AI adoption, improving the organization’s ability to adapt and respond to whatever comes next.
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