Ever wondered why your bank isn’t fully embracing AI for faster services? It turns out, keeping your data safe is the biggest speed bump! Financial institutions are grappling with complex cybersecurity risks while trying to innovate. What will it take to bridge this security-innovation gap?

The ambitious journey towards advanced financial automation, particularly through artificial intelligence, is encountering a significant roadblock: data security and privacy concerns. Across regional banks and credit unions, the paramount worry that sensitive information cannot be adequately protected is proving to be the primary impediment to widespread AI integration and technological upgrades, threatening to slow vital progress in an increasingly digital world.

This hesitation stems from a universal apprehension regarding fraud, compounded by doubts that existing security frameworks are robust enough to safeguard underlying data effectively. Industry experts, such as Buran, underscore the validity of these concerns, stating that while automation promises efficiency and innovation benefits, the inherent data security and privacy risks in banking automation are well-founded and demand continuous focus and improvement.

Indeed, Buran’s perspective is not isolated. Recent research from American Banker’s 2025 survey, which polled 153 bank and credit union leaders, highlights that worries about data security and privacy are compelling many to defer or limit their adoption of advanced automation technologies like artificial intelligence. This collective caution reflects a deep-seated institutional responsibility to protect customer assets and information above all else.

Despite these reservations, intelligent automation is recognized for its transformative potential. Fraud detection and prevention, in particular, was identified as the top use case for intelligent automation with the most significant impact on national banks (54%), regional banks (35%), community banks (52%), and credit unions (52%) over the next three to five years. This demonstrates a clear understanding of AI’s benefits even amidst security anxieties.

Successful implementations by financial giants like PayPal and Visa further illustrate the power of AI in bolstering security. Both companies have leveraged artificial intelligence to enhance their defenses against financial crime, with AI-powered scam detection tools and Visa’s dedicated Cybersecurity Advisory Practice serving as prime examples of how innovation can coexist with robust protection mechanisms.

Yet, the path forward remains challenging for many. A substantial portion of credit unions (56%) and banks (50%) with assets between $10 billion and $100 billion identify data security and privacy concerns as the single largest barrier to further integrating automation tools. This sentiment is echoed by leaders such as Ben Maxim, Chief Technology Officer at MSU Federal Credit Union, who notes the historical disconnect between tech advocates and business understanding, likening it to the early days of the internet or mobile technology.

Larger financial institutions, while facing similar considerations, have demonstrated a continued drive to advance their automation efforts. However, the clear distinctions between application security and operations security, once easily defined, are now blurring. Joshua McKenty, CEO of Polyguard, explains that collecting and analyzing user data to reduce fraud inadvertently raises an organization’s profile as a target, making it crucial to ensure the security framework is entirely sound.

Innovating beyond traditional methods, Parijat Sinha, head of open banking products at FIS, suggests a shift in focus. By prioritizing products tailored to “devices and behavioral patterns” over “individual identifiable attributes” when developing automation frameworks, financial institutions can effectively mitigate anxiety surrounding data retention. This approach simultaneously decreases the risk of agentic or generative AI systems circumventing biometric-based defenses, offering a strategic pathway to secure innovation.

Ultimately, the successful integration of AI in finance hinges on unwavering dedication to data security. Executives like Ally’s chief information, data, and digital officer, continue to champion this priority. For Ally, establishing clear-cut security protocols for specific AI use cases and rigorously removing personally identifiable information have emerged as critical methods for fortifying AI security and fostering a more trustworthy environment for financial automation.