The Truth About Data Quality in Banks: Tools Can’t Fix What People Don’t Own

A robust data platform can transform your bank’s data quality with one specific stipulation: It must be paired with the right top-down approach that encourages and empowers every banker to own the data they use.

While we know that KlariVis can be a key enabler for success in data transformation, we consistently stress to every client that technology alone isn’t enough — it’s how your people use and embrace the technology that truly drives lasting results. Building a culture of data stewardship among your leadership team is essential to ensuring that the platform delivers maximum impact. When everyone across an organization works from the same playbook, there is a shared sense of pride and ownership, and teams collaborate more effectively. This unified approach allows banks to hold their employees to higher standards around data quality.

Here are a few of the lessons we’ve learned when it comes to approaching data stewardship as a bank leader:

Data Quality Is a Challenge of Unification

The key to unlocking the incredible value within your bank’s data is a combination of selecting the appropriate tools and ensuring your people truly understand, adopt, and feel a sense of ownership around them.

In many banks, tech teams and business units operate in silos, often with IT focused solely on systems and business teams unaware of how directly and significantly data quality impacts their work. This disconnect can undermine data initiatives and leave tech investments underutilized. A survey of 250 financial services industry leaders by World Business Research revealed that the biggest barriers to leveraging data management technologies for innovation are data silos (54%) and lack of buy-in (49%). Forrester Research has also noted that disconnected IT strategies often jeopardize the positive impact that IT teams can have on revenue, profit, customer satisfaction, and employee engagement.

Bridging this gap is crucial to ensuring that teams work together to maximize the value of your bank’s data.

Culture Building Isn’t a Sprint, It’s a Marathon

Many banks treat data quality as just another task on a long list of objectives. But pristine data quality cannot be achieved with a quick-fix, or through the altruistic efforts of a few executive stewards. It comes from building an internal, bank-wide culture that values and enforces shared responsibility for data quality, consistency, and accessibility.

A healthy data culture means data quality is never an afterthought — it’s constantly a top priority. Data quality isn’t a short-term project, it requires long-term, consistent effort and a shift in mindset.

As one executive noted in our November KlariVis Data & Innovation Summit, “[Really understanding the data] isn’t an overnight change…this is a constant nurturing of activity that I, as their team leader, have and continue to coach them through in order to change how they structure their day.”

Invest in People

Investing in tools that clearly visualize your data important, but on its own, it’s still not enough. The most advanced software or cutting-edge AI won’t solve your data problems unless your organization invests in its people alongside it.

Everyone — regardless of their role — needs to understand why data quality matters and how they contribute. Yes, an enterprise-wide solution like KlariVis provides the foundation for an excellent data strategy, but none of that matters if employees are not empowered to leverage it appropriately. When employees truly see the connection between their daily actions (or inaction) and data quality, they’re more likely to embrace the tools and practices that drive tangible results.

Three Key Questions to Ask Yourself…

To ensure the digital tools and platforms you’ve invested in (or are considering) deliver the value they should, ask yourself these questions:

• Is the business impact of data quality understood by your team?
  Data quality directly impacts profitability, risk, and customer trust. If employees don’t understand the stakes, poor data management can lead to costly errors, missed opportunities, and damaged relationships with customers.
• Do my employees understand their role in data quality?
  Data quality is everyone’s responsibility, and it should be clear to them what daily actions they need to take to improve or maintain that quality. When employees see how their daily work impacts data, they’re more likely to take ownership.
• How can I provide strategic incentives to maintain data quality?
  Data quality must be woven into daily workflows and reinforced regularly. Offering rewards linked to performance metrics can drive employees to focus on key goals, such as data accuracy and consistency. Without clear motivation, through incentives or enforced bank-wide standards, these priorities can slip behind competing pressures.

Imagine the impact if banks stopped chasing the next “it” technology and really focused on sustainable change. By creating an environment where data quality is a shared responsibility, understood across the organization, and embedded into everyday processes, they can unlock real value. The results won’t come overnight, but with the right focus, they’ll be unbelievably significant.