Bank leaders are under pressure to deliver real-time decisioning, personalized experiences, and enterprise-wide AI—yet many are constrained by data architectures built for transaction recording and regulatory reporting.
From regulatory burden to growth engine: Reengineering data for the next era of banking examines how institutions can redesign their data foundations to meet both supervisory expectations and business ambitions. It explores how banks can move beyond siloed, transaction-focused systems toward connected, reusable, and intelligence-driven data.
This perspective highlights why competitive advantage will depend not on how much data banks have—but how effectively they structure, govern, and activate it. It provides a clear blueprint for transforming data into a driver of growth, agility, and innovation in a real-time, AI-enabled environment.
Key findings include:
• Regulatory-grade data is underutilized. Data built for accuracy and compliance often lacks the structure for real-time insight, reuse, and forward-looking decisions. • Architecture limits insight. Legacy systems excel at recording what happened but struggle to inform what should happen next across customers, products, and time. • Centralization alone isn't enough. Reporting-focused models create consistency but not agility, reuse, or enterprise-wide intelligence.
• Ownership drives transformation. Aligning data ownership to business domains enables higher quality, reusable data products, and embedded governance. • Reengineering enables AI at scale. A unified, well-governed data foundation is essential to support real-time decisions, automation, and predictive insights.
This piece provides a roadmap for banks looking to modernize their data architecture— without compromising control—and to build a foundation that supports both regulatory integrity and growth.