Philadelphia, Pa.-based American Heritage Credit Union achieved $1 billion in growth over just 18 months by activating the data that was previously siloed across its systems. The greatest competitive advantage in financial services is the ability to connect, understand and act on your own data.
Modern data platforms are redefining what it means to be data-driven.
The Fragmented Reality of Banking Data
According to Bank Director’s 2025 Technology Survey, 56% of financial institutions keep data locked inside the system that created it. Another 41% still manage key information in spreadsheets, introducing operational risk, governance challenges and compliance exposure. Most telling, only 38% of banks can access even half of their customers’ financial data.
This fragmentation creates a daily drain on performance. Employees jump between systems to find basic answers. Executives make strategic calls without a full customer picture. Branch staff greet members with no insight into last night’s digital interactions. When data lives in silos, you can’t see the full story, and you can’t act on it.
The Journey to Data Intelligence
Stage 1: Building the Unified Foundation
The average U.S. financial institution operates over 200 vendor systems, according to a study by McKinsey & Co., each storing its own version of truth. The result is operational friction and lost insight.
Modern data lakehouse architecture solves this by combining the scale of a data lake with the performance of a data warehouse — delivering performance at a fraction of traditional costs while operating exponentially faster. Look for solutions that connect cores, digital banking, lending, card and marketing systems into one real-time, query-able foundation. This isn’t just integration; it’s institutional memory that turns fragmented data into living context.
Once data flows into this unified layer, analytics, compliance and performance tracking move from reactive to proactive. Trends appear early. Bottlenecks become measurable. Risk becomes manageable.
Stage 2: From Aggregation to Intelligence
Connection is only the first step. Once normalized, data transforms from a static record into dynamic intelligence.
Leading analytics engines deliver curated dashboards and insights to every level of the institution, from executives to branch staff. Instead of relying on monthly reports, leaders see real-time metrics on portfolio growth, channel performance and customer behavior.
Consider a customer with a mortgage, auto loan and checking account, who is also a heavy user of online banking. In fragmented systems, that is four separate stories, but in a unified environment, it is one cohesive narrative that reveals financial behavior and next-best opportunities.
Stage 3: Turning Insight Into Action
The real breakthrough happens when intelligence becomes action. Predictive analytics, artificial intelligence (AI) and workflow automation transform insight into measurable outcomes:
• Issues become solutions as anomalies trigger automated workflows that route tasks for resolution before they escalate.
• Opportunities become growth as AI-identified cross-sell or refinance opportunities convert directly into referrals and marketing campaigns.
• Manual work becomes automation as reports, approvals and compliance checks that once took days are now seamless background processes.
Across retail, risk, marketing and operations, this intelligence layer turns data into momentum where every decision, interaction and campaign is powered by live insight.
Let’s Get Practical
Do start by measuring what matters — churn rates, cross-sell, share-of-wallet, hold-times marketing campaigns linked to opened products, customer profitability, employee efficiency. These metrics define your starting point and return on investment.
Don’t treat data activation as an IT project. Every department needs data and thus should be represented in both the foundation and delivery. Executives need daily financial visibility. Front-line staff need complete customer relationships in real-time. Managers need daily performance metrics to be proactive, and lending needs pipeline visibility.
Do anchor transformation around your institution’s mission. A community bank focused on farmers will need different insights than an urban credit union serving first-time homebuyers.
Don’t try to do it all at once. Start with a high-impact process like loan onboarding or marketing analytics. Early success builds confidence and momentum. Data activation never ends but can deliver wins every quarter.
Data fragmentation is a silent tax, a hidden cost embedded in every transaction, every decision and every customer interaction. The institutions that win are those that connect their systems, activate their data and empower every team with actionable intelligence.
The right platform connects, analyzes and activates your data so issues turn into solutions, insights turn into action and strategy turns into measurable growth.
Some financial institutions will spend another year debating how to become data driven. Others will spend it executing.
The $1 billion question: Which one will you be?
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