While financial services are charging ahead with GenAI, big banks are deploying copilots, insurers are building chatbots, and fintechs are scaling agents. Credit unions are thinking ahead.
They’re asking:
At Wald.ai, we’ve seen this story unfold across dozens of credit unions.
This is where the CUEX Curve comes in: a new framework to help credit unions benchmark, adopt, and scale GenAI without giving up control.
📊 Sidebar: Why We Combined the CUEX Curve with the Classic Innovation Model
The classic “Diffusion of Innovation” curve by Everett Rogers breaks adopters into innovators, early adopters, early majority, late majority, and laggards. It’s useful for understanding when and why adoption spreads in society but it wasn’t built for regulated environments.
The CUEX Curve builds on that foundation with a more actionable lens: it maps AI maturity by internal behavior, governance risk, and infrastructure needs. Where Rogers’ curve explains social momentum, CUEX translates it into compliance-safe execution.
In short: We evolved the innovation curve for the real-world needs of credit union leaders.
The Credit Union Executive Experience (CUEX) Curve is Wald.ai’s proprietary framework designed to help credit union leaders benchmark their AI maturity and scale safely.
Unlike generic tech maturity models, the CUEX Curve addresses the specific compliance, trust, and member-facing demands credit unions face. It breaks adoption into four distinct stages:
To help credit unions benchmark not only adoption, but governance readiness across the CUEX Curve, here’s a combined view of CU-specific adoption data and estimated governance maturity (based on 60%-adjusted BFS benchmarks):
Filene Research Institute’s 2024 Generative AI reports:
These figures show that while 50% of credit unions are moving beyond curiosity, the majority still lack comprehensive governance and controls, pinpointing the “gap zone” between early adopter enthusiasm and full operational readiness.
As credit unions explore the potential of GenAI, attackers are already exploiting it. Security leaders across the financial sector report that AI has enabled more advanced phishing, impersonation and fraud. While no credit unions have publicly disclosed direct breaches, the risks are escalating.
Inside Prompt Injection Issues
AI systems that lack security features can be manipulated using dangerous prompts. This has been repeatedly observed within the financial industry, raising concerns for credit union. Running pilots that have no mechanisms in place for controlling prompts.
Malicious AI-supplied Social Engineering
Phishing emails, impersonation calls and scripts can all be created and generated using AI. Staff and members may inadvertently communicate with malicious impersonators posing as known contacts.
Model Leakage from Public LLMs
Using tools such as ChatGPT comes with privacy issues, especially when dealing with sensitive topics like member data. For internal users, pasting member data is effortless, but without protective measures like redaction or active cleaning, public tools can lead to hidden leaks, evidenced by “shadow AI” as a growing issue.
Credit unions must treat every AI interaction as a potential exposure point. Attackers already do.
1. Lack of Internal Governance
Teams are piloting AI with no oversight. Without prompt guidelines, sandboxing, or logs, risk becomes invisible.
2. No Clear Ownership
Who owns AI? IT? Risk? Ops? Without a designated AI lead, adoption stalls.
3. Infrastructure Misalignment
Many credit unions still use core systems not built for model integration, real-time logging or prompt encryption.
Credit unions don’t just need policies. They need tooling that makes policy work in practice.
Wald.ai helps credit unions turn governance principles into operational safeguards. What usually lives in a PDF or policy deck becomes a product feature.
Wald.ai is the only GenAI platform purpose-built for regulated industries like credit unions. Our solution meets you at your current maturity level:
Real-world examples show what’s possible when credit unions take a proactive, governance-first approach to GenAI:
These use cases are proof points that AI, when governed well, delivers operational lift without compromising compliance.
Credit unions can’t just adopt AI. They must govern it. Wald.ai provides:
At Wald, we’ve spoken to dozens of credit unions. Many have experimented with Microsoft Copilot or Google’s Gemini Enterprise, but are now pulling back from using them in core operations. Two key reasons come up consistently:
Wald.ai offers a safer alternative.
The issue isn’t using copilots. It’s whether you can control where they live, what they see, and what they do.
AI breaches often stem from what teams input, not what the model outputs. Untrained staff may paste:
“Summarize this account statement for loan approval: [member PII]”
Public LLMs like ChatGPT retain this data. That’s a breach.
Wald.ai stops it in real time, detecting sensitive fields and sanitizing prompts before they reach the model.
The CUEX Curve™ helps your board, compliance team, and operations staff speak a common language about AI adoption. It maps strategy to controls, use cases to risks, and intent to infrastructure.
Younger members expect instant, digital-first experiences. They are already using AI tools in their daily lives and expect the same speed and personalization from their credit union. But adopting AI without guardrails can expose sensitive member data and create governance gaps.
Wald.ai helps you meet both expectations. By building secure, permissioned AI agents that can assist with lending, fraud prevention, and support, your team can scale faster and smarter, without sacrificing trust.
Agentic AI is not just a technical innovation. It is a way to meet the next generation where they already are.
Want to know where you stand?
Book a Demo with us. We’ll tell you your current phase, your biggest risks, and your best next step.
Credit unions often operate with leaner teams, tighter compliance mandates, and mission-driven member service. GenAI introduces new data governance and risk challenges that require specialized controls not just productivity tools.
Wald.ai sanitizes every prompt before it reaches the model, strips PII in real time, enforces role-based access and provides full audit trails. Consumer tools often store prompts or lack visibility and policy enforcement.
Yes, with guardrails. Wald’s platform is tuned for compliance-sensitive workflows like underwriting and fraud analysis, with controls built for credit union standards.
That’s where Phase 1 of the CUEX Curve starts. Wald.ai offers immediate AI readiness, access to all leading AI assistants such as ChatGPT, Grok, Claude and more with in-built advanced DLP controls. Secure sandboxes to help you safely move forward.
Credit unions using Wald.ai typically move from pilot to operational as soon as top-line decides, deployment takes only a day with Wald.ai.