Only 3% of financial institutions have effectively deployed AI into production, according to new Ataccama research
As new AI regulations loom, financial institutions are modernizing compliance and data quality systems to close the gap between AI pilots and enterprise-scale adoption
Boston, Mass. – October 28, 2025 – Ataccama, the AI-powered data trust company, today released the third edition of its Data Trust Report 2025, revealing a sharp divide between financial institutions’ AI ambitions and their ability to execute at scale. While 99% of institutions are testing AI, just 3% have deployed it enterprise-wide. Success depends less on the models themselves and more on whether the data that fuels them is complete, trusted, and ready to use.
Decades of mergers and legacy infrastructure have left financial institutions managing hundreds, and sometimes thousands, of systems, often with conflicting definitions of core concepts, such as “customer,” “account,” or “transaction.” In one system, a “closed account” might still appear active in another, creating mismatched data that can cascade into faulty credit decisions or compliance misreports. Training an AI model can take weeks, but preparing accurate, compliant data to feed it often takes months. That imbalance explains why AI proofs of concept rarely make it to production, and why CDOs are now rethinking their data foundations.
“The low percentage doesn’t reflect failure; it reflects reality,” said Mike McKee, CEO of Ataccama. “Many financial institutions are racing to deploy AI, but the ones that succeed will find the right balance between speed and trust. That means cleaning up the data, establishing clear ownership, and making sure AI systems can explain their decisions. That balance is what earns both customer trust and regulatory compliance.”
Almost half of financial services executives (46%) rank improving data quality as their top priority, and more than a third cite it as their biggest challenge. The report underscores that scaling AI depends less on algorithmic sophistication and more on reliable, contextual, and ready-to-use data, such as ensuring that the same customer record is consistent across onboarding, lending, and fraud systems. Data that can be traced, validated, and trusted to drive critical business outcomes becomes the real differentiator.
To close the gap, financial institutions are moving beyond one-off fixes and embedding data governance and quality directly into everyday processes. Rather than treating data management as a reactive task, they are building trust into the workflow itself by integrating quality checks, ownership, and observability into the systems that run the business. The focus is shifting from cleaning up data after the fact to ensure it’s reliable and compliant from the start. The implications go well beyond operations. Inaccurate transaction histories can trigger false fraud alerts, and incomplete know-your-customer (KYC) data can delay onboarding or raise regulatory flags.
McKee added, “Enterprises have evolved from CIO-driven data warehouses and projects to CEO-driven data products and priorities that directly impact competitive advantage and business outcomes. Every decision now depends on knowing which data you can trust, where the gaps are, and how to close them. That means getting the fundamentals right — from KYC documentation to financial records and transaction information — because accuracy isn’t optional. A single mismatch can mean a compliance violation or a denied customer request. Perfect data everywhere isn’t realistic, but perfect data where it counts is non-negotiable. The institutions that focus on those critical use cases and get them right will scale AI with confidence because they’ve built trust into every decision their business makes.”
The report also highlights a major shift in mindset. Close to 50% of financial data leaders now rank compliance and reporting among their top business priorities, which is nearly double the rate in other industries. What was once viewed as a constraint has become a catalyst for modernization. New regulations such as the EU AI Act, which introduces penalties starting in 2026 for high-risk AI systems, are giving financial institutions both the mandate and the momentum to unify data silos, establish clear lineage, and apply AI to validate data in real time. Compliance, once seen as a cost, is now driving transformation as institutions prepare to meet stricter transparency and accountability standards.
As AI becomes central to financial strategy, data trust is quickly becoming the new competitive edge. There is no AI strategy without a data strategy. Success depends on having accurate, well-governed, and explainable information that leaders can rely on to make confident decisions at scale. Institutions that combine automation, governance, and compliance discipline achieve faster product launches, cleaner regulatory reporting, and greater confidence in high-stakes AI use cases such as fraud detection, credit scoring, and risk modeling.
Trust is becoming the new currency of digital finance. Financial institutions that invest now in automated quality, transparent governance, and explainable AI will lead the next phase of AI adoption built on confidence.
Read the full report to see how leading financial institutions are transforming compliance mandates into catalysts for modernization and turning trusted data into a competitive advantage.
About Ataccama
Ataccama is the AI-powered data trust company. Organizations worldwide rely on Ataccama ONE, the unified data trust platform, to ensure data is accurate, accessible, and actionable. At the core of the platform is our leading data quality suite that integrates data quality rules, catalog, lineage, observability, and governance to continuously improve the reliability of enterprise data. This quality-first foundation makes data quality the engine of trust, powering AI, analytics, and operations with confidence. Ataccama helps organizations drive innovation, reduce costs, and mitigate risk. Recognized as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality and the 2025 Magic Quadrant for Data and Analytics Governance, Ataccama continues to set the standard for enterprise-grade data trust. Learn more at www.ataccama.com.
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