Bank-fintech partnerships have driven some of the most transformative innovations in modern finance, from neobanking to improved financial inclusion. These collaborations have lowered barriers and expanded access. Yet, as banks increasingly rely on third-party vendors for advanced AI capabilities, a critical tension emerges: the bank remains fully accountable for decisions made by systems it neither designed nor fully understands.
The Accountability Gap in Vendor-Provided AI
For over a decade, U.S. banks have managed model risk under SR 11-7, a framework that covers both internally developed and purchased models. In April 2026, regulators introduced SR 26-2, replacing SR 11-7 and SR 21-8, signaling a new era of oversight. However, this new guidance deliberately excludes advanced AI—specifically generative and agentic AI—because these technologies are deemed “novel and rapidly evolving.” This omission leaves a significant gap: the very technology vendors are deploying fastest falls outside the regulatory framework banks have relied on.
Most banks do not build their own AI models. They purchase them from a handful of large infrastructure providers, and for good reason. The pace of AI development outstrips what most institutions can manage internally, especially those with strict compliance requirements. Even when banks layer their own tools on top of third-party models, the underlying model may be replaced multiple times during the approval process. This creates a situation where banks are accountable for outcomes they cannot fully trace or explain.
Why Vendor Choices Become Bank Strategy
Fintechs move faster and are often more willing to take on risk than banks, which is why these partnerships are so valuable. However, no vendor can assume a bank’s accountability to its customers or regulators. If a bank is not deliberate, the vendor’s decisions effectively become the bank’s AI strategy by default. This is not a hypothetical concern.
Consider a bank that partners with a vendor to deploy AI fraud detection. The system flags a legitimate small business as fraudulent based on an unusual but honest cash flow pattern. The business is denied credit. The bank now faces fair-lending exposure, potential discrimination complaints, and reputational damage—all for a decision its own staff cannot reconcile because the vendor will not disclose the model’s logic.
The Regulatory Void and Its Consequences
Regulators are aware of this issue. The FDIC has floated the idea of an independent standard-setting body to help banks evaluate vendor risk, but this is still in early stages. Even if established, such a body would likely lack the trust needed for banks to accept certifications at face value. Conditions vary by deployment, and banks will still need their own vetting procedures. Moreover, participation would be voluntary, reducing the likelihood of widespread adoption.
Practical Steps for Banks to Manage AI Risk
Until regulators provide clear guidance on advanced AI, banks must take proactive steps to protect themselves and their customers. Here are key actions to consider:
- Ask hard questions before partnering: Demand transparency about how the AI works, what data it uses, and how decisions are made. If a vendor cannot or will not explain, that is a red flag.
- Define your deal breakers: Know what risks you are unwilling to accept, and ensure contracts reflect those boundaries.
- Establish internal oversight: Even if you do not build the model, you must have processes to monitor its performance and escalate issues.
- Document everything: Maintain records of vendor communications, model versions, and decision logs to support your accountability.
- Stay informed: Follow regulatory developments and industry best practices to anticipate changes.
Conclusion: Accountability Cannot Be Outsourced
In the end, accountability for AI cannot be bought from any vendor—hyperscaler, core provider, or fintech. With technology this new and unregulated, there is no such thing as being overly cautious or asking too many questions. A vendor that flinches at scrutiny has already revealed its position. Banks must take ownership of their AI strategies, ask the right questions, and set their own standards. The responsibility is theirs alone.