Data Freedom and AI: The Value for Financial Services

AI is now essential in financial services, having transformed how advisors serve their clients from personalized planning insights to predictive risk modeling, and its growth isn’t slowing down. According to McKinsey, 78% of businesses are now using AI in at least one business function, marking a 23% increase from 2023. This sharp uptick clearly demonstrates that unlocking meaningful value from AI, not implementation, is the next big challenge for firms. Doing so hinges on one critical factor: data freedom. 

AI models are only as strong as the data behind them. And yet, data ‘lock in’ practices, in which contracts and punitive fees for access and extraction restrict a company from leveraging its own data, have become increasingly commonplace. Without the necessary access and control over their own data, financial experts, from advisors to executives at major banks, face a perfect storm of increased security risk, untrustworthy outputs, and AI tools that never reach their full potential.   

Data freedom is the determinative factor in AI success, more so than even model selection or budget. Now, with the battle over data access is already well underway, it’s time for a new industry standard – one where data can be accessed freely, without penalty or restrictions. 

Where Does Data Freedom Fit in Financial Services? 

Advisors being able to access and utilize their data on their own terms should be the bare minimum, whether it’s for regulatory audits, client reporting, or streamlining system migrations when changing vendors. True freedom, however, goes deeper than accessibility alone to full transparency into how, when, and where that data is stored, processed, and shared. 

The consequences of limited data access, restrictive fees, and the current industry norm of vendor lock-in are more than just an inconvenience – they present very real compliance, operational, reputational, and innovation risks.  

Financial advisors are asked to make weighty decisions on their clients’ behalf every day, and rely on accurate, timely information to do so responsibly. When vendors lock that data away behind proprietary systems, advisors’ agility and visibility take a nosedive. It’s also harder to efficiently implement new AI tools and respond to market shifts, ultimately hindering their ability to deliver a seamless client experience.  

The financial services industry also lives and dies by trust. That firms take compliance and security seriously while still delivering value is more than a client expectation, it’s a necessary principle – especially where AI tools are involved. And yet, for 45% of companies, concerns about data accuracy or bias still sit top of mind, and another 40% cite privacy as a top issue and barrier to AI implementation.  

Business leaders that prioritize their data are better equipped to overcome these concerns. After all, records of client communications, investment recommendations, and transaction data aren’t just operational necessities. They are proof of compliance and protection in the event of disputes, making comprehensive governance policies and free-flowing data access key to technological growth.  

Unlocking AI Innovation to Power Client Success 

When advisors have full control of their data, they can train and deploy better AI systems and deliver tangible improvements throughout the client journey. From automating compliance checks to identifying risk patterns or predicting future triggers to changes in financial needs, the potential of AI to transform financial advisory is immense.   

However, when firms operate within restricted data ecosystems, AI innovation stalls. 42% of companies abandoned AI initiatives this year alone. That’s up from just 17% the year before, with poor data access coming in as one of the leading causes – a finding that holds true across AI maturity level, according to 34% of leaders from low-maturity and 29% from high-maturity organizations. 

For financial advisors, data freedom allows for richer, real-time client insights, while also reducing compliance costs through automated recordkeeping and discovery. And yet, as long as the industry is stuck in a cycle of limited functionality, costly data migrations, and unnecessary disruptions, the advancement of AI technology stands little chance. Only when accurate, accessible, and modernized data serves as the foundation will organizations be able to ensure quicker AI development, better training, and more secure outputs while also encouraging innovation. 

Control over data has emerged as the real competitive advantage in today’s increasingly AI-first financial services industry. In this landscape where the increased risk from vendor lock-in, opaque systems, and costly data migrations is simply not sustainable, data freedom stands as the next step in bringing peace of mind and better outcomes to advisors and their clients alike.