Think Your Financial Institution Isn't Using AI? Think Again. 

As financial institutions evaluate whether adopting AI is the right next step, many overlook a critical reality: AI is already embedded in the vendor solutions they use daily. Whether realized or not, vendor platforms may already be leveraging institutional data. Without a clear understanding of which vendors are using AI, how they are using it, and whether your data is involved, financial institutions may be exposing themselves to unnecessary risk.

The Office of the Comptroller of the Currency (OCC) along with the Federal Reserve have recognized this gap and is now urging banks to understand their AI usage comprehensively, including indirect exposure through third-party vendor relationships. As of now, their approach is to keep a close watch, with the aim of deepening their understanding of how financial institutions are deploying the technology. However, they are now asking banks to map out how they use AI technology in routine bank examinations. *

Why Vendor AI Use Creates Risks

One of the most significant risks associated with vendor-enabled AI is data exposure. Financial institutions must have a clear understanding of where their data is stored, how it is being used, and whether it is being leveraged to train AI models. Without this visibility, sensitive information could be unintentionally shared or repurposed beyond its original intent. Further, banks and credit union executives should evaluate how vendors are securing that data. What safeguards are in place to prevent breaches, misuse, or unauthorized access? Are there clear controls, such as ‘kill switches,’ to immediately cut off AI processes if an issue arises? And just as importantly, how is data privacy defined, maintained, and contractually enforced? Without concrete answers to these questions, financial institutions are not just adopting innovation; they are assuming unnecessary and avoidable risk.

Beyond understanding how their data is used, executives should insist on vendor transparency, as it is critical to effectively managing AI risk. Financial institutions should expect clear, detailed disclosures from their vendors, outlining where and how AI is embedded within their solutions. This includes understanding the AI models being used, the data inputs they rely on, and the business processes or decisions they support. Banks and credit unions should also assess whether these vendors maintain formal AI governance frameworks. Without this level of transparency and control, financial institutions are unable to fully evaluate risk and ensure compliance.

In many cases, AI functionality is powered by external platforms, cloud providers, or embedded third-party models that may have their own data practices and risk exposures. This creates an additional layer of complexity for financial institutions, as they often have little to no direct visibility into these relationships. To effectively manage this, banks and credit unions should require vendors to disclose their critical subcontractors and provide transparency into how data is managed, protected, and governed throughout the vendor ecosystem.

What Examiners Will Expect

Regulators are increasingly expecting financial institutions to demonstrate a clear understanding of how AI is being used across their vendor ecosystem. This includes identifying which vendors are leveraging AI, how data is involved, and where and how that data is stored. Beyond visibility, banks and credit unions should have formal governance frameworks in place that include AI-specific monitoring, accountability, and controls.

In February 2026, the U.S. Department of the Treasury released new resources to guide AI use in the financial sector. The information address challenges and provide practical tools and reference materials to help financial institutions evaluate AI use cases, manage risk across the AI lifecycle, and embed accountability, transparency, and resilience into AI deployment decisions. Together, these expectations signal a shift toward more proactive oversight where financial institutions must not only understand AI risk but actively manage and govern it.

How to Move Forward

So, how do financial institutions move forward? The path begins with building a comprehensive vendor inventory that clearly identifies which partners are leveraging AI and which are not. From there, financial institutions should enhance their due diligence processes to specifically address AI-related risks, updating vendor reviews, revisiting contract language to include data usage and AI provisions, and ensuring ongoing visibility to how vendor partners operate. Finally, strengthening ongoing monitoring and governance frameworks will ensure that AI risks are identified upfront and continuously managed as regulatory expectations evolve.

AI is no longer a future consideration; it is already influencing the technology ecosystem that supports financial institutions. The challenge is not whether AI is present, but whether institutions understand where it exists, how it operates, and what risks it may introduce. Those that prioritize transparency, strengthen vendor oversight, and establish governance frameworks will be best positioned to harness the benefits of AI while safeguarding their data, customers/members, and reputation.

When AI is applied strategically and governed effectively, it can drive operational efficiencies, improve customer/member experiences, strengthen fraud prevention efforts, and support long-term growth. The key is balancing innovation with appropriate oversight.

Engage fi helps banks and credit unions evaluate emerging technologies, strengthen vendor management practices, and build governance frameworks that support responsible AI adoption. Contact us to learn more.

*https://www.reuters.com/business/finance/us-bank-regulators-ramp-up-scrutiny-ai-use-financial-companies-2026-06-12/