Walk into just about any boardroom today and you’ll hear the same refrain: “We’re investing in AI.” It’s fast become the mantra of modern financial services. Predictive analytics, personalized experiences, smarter risk models. Everyone’s chasing it.

But behind this promise is a hard truth: AI simply can’t fix a bad foundation – and that foundation is customer data.

A new Stibo Systems study of 500 U.S. business leaders found that 91% say customer data management is critical, yet only 31% actually trust their data. That’s the trust gap quietly eating away at time, money and confidence at some of the world’s most data-rich financial institutions.

The rising customer experience bar

Fintech and financial new entrants have elevated the bar when it comes to customer digital experience and are capturing younger generations. The numbers talk: In 2024, Trimco Group found that 56% of millennials reported having at least one fintech checking or savings account. Around the same percentage of U.S. customers now primarily manage their finances through mobile apps and a significant 89% of customers across all generations use mobile banking.

Customer expectations for the “personal touch” are clear and non-negotiable. According to Zalando Partner, 70% of consumers expect personalized advice from their banks and as 91% of customers emphasize the importance of quality customer service when selecting a bank.

Banks are now investing to catch up – their siloed legacy infrastructure lacks agility and technical advancement, which prevents them from fully tapping into the enormous potential of digital transformation to create these in-demand customer experiences.

The fragmentation problem

We don’t talk about it enough, but it’s happening every day: global banks running multimillion-dollar AI projects while still relying on disconnected systems, duplicate records and manual spreadsheets to keep customer information straight.

For an industry built on precision, too much customer data is still scattered across silos. Account details, transactions, policy information – it all lives in different systems that don’t speak the same language.

The Stibo Systems study found 76% of organizations still rely on “shadow databases” just to reconcile customer information and 60% of teams spend more than six hours a week cleaning data. That’s triage.

A single duplicate record can delay onboarding, flag false compliance risks or distort a customer’s profile across multiple lines of business. When the customer data doesn’t match, customer trust erodes – and we all know how hard that trust is to win.

Governance: The missing link between compliance and growth

As an industry, financial services have historically treated data governance as a compliance requirement. It’s now high time to treat it as a growth strategy.

Stibo Systems found that 57% of institutions admit they lack formal governance policies, which means the same customer might look different in five different systems. What does that mean? The data just becomes noise.

Good governance is about clarity. It’s the difference between “we think” and “we know,” between being check-the-box ready for an audit and actually making smart decisions.  

AI is only as good as the data you feed it

Nearly half of leaders in Stibo Systems’ study named AI-driven products and services as a top goal for 2025. But 28% are already struggling to adopt AI because their customer data just isn’t ready for it.

Let’s be honest: we’ve all seen AI tools that vastly overpitched and woefully underdelivered. The reason more often than not comes down to lack of trust in the data inputs.

The untapped advantage hidden in customer data

The irony – or maybe the good news – is that financial institutions already have the raw materials for innovation. It’s just trapped.

When banks, insurers and asset managers connect customer and other data, the view of that data changes completely. Suddenly, cross-sell opportunities appear. Fraud detection sharpens. And marketing gets personal again, which people expect right now.

When organizations invest in mastering the customer data domain, they open up ways to create context around the insights from that data. The payoff spans a wide range of positive impacts, from revenue growth (cross-selling and up-selling, higher customer lifetime value, reduced attrition) to operational efficiency and cost reduction, as well as enhanced audit and compliance, risk management and fraud detection.   

The bottom line

The financial services industry has always been built on relationships. And in this AI era, those relationships are defined by the data behind them.

The next competitive edge will be for the businesses that can trust their customer data enough to use it confidently – and that’s worth investing in.