Banks Hold Only a Fraction of Customer Data as AI Changes Finance

For decades, banks have been the primary holders of customer financial information. Yet as digital technology advances, the share of a person's life visible to their bank is shrinking. The story of Chris Dancy, a Tennessee resident who equipped himself and his environment with hundreds of sensors, illustrates how much more data can be collected beyond traditional banking records. Dancy's experiment, which began over a decade ago, involved tracking everything from his heart rate and sleep patterns to his location, mood, and even the temperature of his home. By assembling this data, he created a comprehensive digital profile-what is now called a digital twin-allowing him to understand and improve his own habits and health.

This example raises a critical question for the financial sector: how much do banks really know about their customers compared to other companies? If a person's life is divided into six layers-physical, environmental, social, emotional, cognitive, and financial-banks typically access only a portion of the financial layer. Even within that, data is fragmented across multiple institutions and products, often limited to transaction histories and account balances. Estimates suggest banks may see just 10% of the total picture, while technology firms and digital platforms collect the remaining 90% through smartphones, apps, and online services.

The Rise of Digital Twins and Data Fragmentation

The concept of a digital twin, once limited to manufacturing, now applies to individuals as technology enables the collection of detailed personal data. Platforms such as search engines, social networks, and mobile devices gather information on users' physical activity, social connections, emotional states, and cognitive interests-often with greater depth and frequency than banks. For example, a search engine may know a user's anxieties and aspirations before any financial institution does, simply because people share more openly with digital assistants than with bank staff.

This shift has significant implications for the financial industry. As artificial intelligence (AI) agents become more capable, the value of data moves beyond marketing and into direct action. AI-powered services can plan, manage, and optimize aspects of a customer's financial life, but their effectiveness depends on the completeness of the underlying data. The company with the richest, most accurate digital twin of a customer is best positioned to offer relevant, timely, and personalized financial advice or services.

AI Agents and the Competitive Landscape

The emergence of AI agents marks a turning point in how financial services are delivered. Where banks once relied on limited financial data to market products, AI can now act on behalf of customers-managing budgets, planning for retirement, or navigating complex transactions. However, an AI agent is only as effective as the data it can access. If a bank's view is restricted to a narrow slice of financial activity, it risks being outperformed by technology companies that see a broader, more nuanced picture of the customer's life.

According to industry estimates, the global market for personal financial data is expanding rapidly. In 2025, the volume of data generated by individuals worldwide is projected to exceed 180 zettabytes, with financial data representing only a small fraction. Meanwhile, the adoption of AI-powered financial tools is accelerating, with over 60% of major banks piloting or deploying AI agents for customer service and financial planning as of late 2025. Yet, regulatory frameworks such as the EU's General Data Protection Regulation (GDPR) and similar laws in other jurisdictions continue to limit how much personal data banks and platforms can collect and use without explicit consent.

Trust, Consent, and the Future Role of Banks

Despite the competitive pressure to gather more data, banks face strict regulatory and ethical boundaries. Trust remains a core asset for financial institutions, and customers expect their banks to protect sensitive information. Rather than attempting to collect every possible data point, banks must decide which layers of a customer's life they can access responsibly-balancing value creation with privacy and consent. This may involve partnerships with technology firms, new consent-driven data models, or focusing on areas where banks retain a unique advantage, such as regulatory compliance and secure asset management.

For customers, the changing landscape means that the most useful financial services may come from providers who can integrate data across multiple domains-physical, social, cognitive, and financial-while maintaining transparency and trust. As AI agents become more central to financial decision-making, the question is not just who holds the data, but who can use it most effectively and ethically to serve the customer's interests.

Understanding the distinction between data layers is essential for both banks and consumers. The financial layer includes what a person earns, spends, saves, and owes, but it is only one part of a much larger picture. Physical data covers health and movement; environmental data relates to living conditions; social data maps relationships and networks; emotional data tracks mood and stress; and cognitive data reflects learning and intentions. As technology evolves, the ability to combine these layers securely and with consent will shape the future of financial services and the broader digital economy.