Jess Turner, Executive Vice President, Global Head of Open Finance & Developer Experience at Mastercard.
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The financial services industry has spent the better part of a decade building the pipes for data access. With APIs, data-sharing frameworks and regulatory standards, the infrastructure for open finance is more mature than ever. Yet many institutions find themselves stuck in an uncomfortable middle ground: They’ve invested in connectivity but haven’t figured out how to turn that access into measurable business outcomes.
The question most institutions started with (“Why should we participate in open finance?”) has largely been answered. Our research found that three-quarters of surveyed senior executives now attribute direct revenue growth to open finance initiatives. Meanwhile, 76% of surveyed consumers said they would switch providers to access digital features that make managing their finances easier, and more than half have already done so.
The harder question, which separates leaders from laggards, is how to operationalize the insights that open finance makes available. That’s where things tend to stall.
The Operationalization Gap
According to a 2024 Deloitte survey, only 8% of banks and credit unions reported having the data maturity required to support personalization at scale. Meanwhile, a 2025 FICO survey found that 73% of surveyed consumers said they’d be more likely to do business with providers that deliver personalized products and services. That disconnect is an organizational problem.
The average consumer today spreads their finances across five to seven accounts. Even a customer’s “primary” bank may see only a fraction of their financial life. Open finance gives institutions a window into the rest of that picture: permissioned data across cards, deposits, investments and bills. However, a window is only useful if you know what you’re looking at.
Raw transaction data is notoriously difficult to parse. Inconsistent labels, missing context and fragmented formats mean that even with broader data access, many institutions can’t reliably identify the signals that matter, such as a recurring subscription, a shift in spending behavior or a customer quietly moving assets elsewhere. You can’t act on what you can’t interpret.
From Raw Data To Decision-Ready Intelligence
The institutions making the most progress are the ones treating data readiness as a strategic priority, not an IT project. That means investing in four capabilities:
1. Structuring internal data so it’s consistent and accurately labeled.
2. Completing customer views with permissioned open finance data.
3. Standardizing categorization and enrichment across sources.
4. Making that data usable in real time for decisioning tools and AI applications.
This is about making existing data connected, contextualized and actionable. When a transaction string is enriched with merchant details, location, category and recurrence patterns, it stops being noise and starts being insight.
Patterns tell a story, such as a customer who orders from the same coffee shop every morning, books travel every March and recently started making payments to a competitor. That story should be informing every interaction, from the next offer to the next underwriting decision.
Turning Insight Into Growth
The payoff for getting this right is significant. Institutions most active with open finance are seeing measurable lift across revenue, retention, cross-sell conversion and customer deposits. The cost of getting it wrong is equally clear: Two-thirds of executives report losing customers because they couldn’t offer the level of personalization or convenience those customers expected. In the U.S., that figure rises to 78%.
Open finance has the potential to reshape underwriting, making credit decisions more accurate by incorporating cash flow data and real-time financial behavior rather than relying solely on traditional credit scores. It can accelerate onboarding, reducing the friction that causes customer drop-off. It can strengthen fraud detection by giving institutions a clearer baseline of normal behavior.
The trust dimension matters, too. Nearly half of consumers are willing to share their financial data, but only when they understand what it will be used for and what they’ll get in return. Institutions that invest in clear, transparent consent experiences will unlock more data, which fuels better personalization and builds more trust. It’s a flywheel, but it only turns when the value exchange is genuine.
The Path Forward
Open finance has moved past the question of whether to participate. The institutions that will lead the next era of financial services are the ones asking a different set of questions: Is our data ready for the decisions we need to make? Are we translating access into action? Are we earning the trust that keeps the flywheel turning?
The infrastructure is in place. The consumer demand is unmistakable. What’s left is the hard, essential work of turning data into outcomes. That work starts inside the institution, not outside of it.
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