About · AI Governance & Implementation for Credit Unions
A design partner for the AI decisions that reach
the board and the examiner.
Bank Ready AI helps executive teams at credit unions decide where AI belongs, where it does not, and how governance, technology, people, and member service fit together — before any platform is bought, built, or piloted.
Founder
Alex Zaboli
formerly KPMG & PwC bank risk & regulatory
IIThe moment
The board wants a strategy. Existing obligations still apply. A lean team carries the risk.
The pressure to adopt AI is real. NCUA has not issued AI-specific rules or regulations, but applicable technology-neutral legal requirements, NCUA-relevant guidance, and your institution’s accountability remain. Bank supervisory references and voluntary frameworks can inform the analysis; they are not an NCUA AI rulebook.
IIIWhy most AI projects fail here
Three failure patterns show up in nearly every engagement.
Vendor-led adoption without a governance spine
A platform is chosen before the workflow, the data, or the failure modes are defined. When examiners ask for the third-party inventory, the use-case boundary, and the input data lineage, the institution answers in fragments.
A pilot that never becomes a program
The proof-of-concept works in a conference room. The path to production doesn't exist because integration architecture, human-in-the-loop controls, and monitoring were never designed alongside the model.
The vendor-examination gap doesn’t remove your accountability.
NCUA lacks general statutory authority to examine third-party vendors. That makes the credit union’s own due diligence and ongoing oversight important. NCUA identifies AI considerations including algorithmic decisionmaking, fair lending, member-data privacy, operational resilience, model risk, and AI-specific security. These are considerations to assess in context — not an exhaustive, mandatory six-control framework.
IVMy vantage point
Here’s my take — executives at credit unions don’t want generic advice on the AI era. They want a design partner who will help them realize what’s possible and how to integrate it within their current tech stack — under the supervisory expectations their examiners actually enforce.
A decade in bank risk, now applied to credit unions.
The career experience below is mine, earned at prior employers. The work of Bank Ready AI is the firm’s own — a separate, current practice.
2016–2017
Internal audit & control remediation
KPMG — mortgage lending & servicing, National Mortgage Settlement era
Designed and tested controls and executed remediation programs under examination pressure.
2018–2019
Enterprise risk, SOX/ICFR & regulatory reporting
KPMG — large banks, regional banks, asset management, a GSE
Enterprise risk management, SOX and ICFR compliance, finance transformation, and FR Y-9C regulatory reporting.
2020–2025
Treasury, liquidity & stress-testing governance
PwC and KPMG — bank risk & regulatory advisory
Treasury liquidity stress testing and governance: intraday liquidity, stress-testing frameworks, and deposit behavior calibration for regional banks.
2025
Retail credit loss forecasting, learned from the founder
SRA — bank modeling firm
Sat with SRA's founder many times as he walked me through the retail credit loss process — the inputs, the outputs, and where judgment sits. A close study of the discipline, end to end.
2026–present
Founder
Bank Ready AI
AI governance and implementation advisory for credit unions.
VWhy I built this practice
Credit unions need a design partner before a build partner.
Most vendors arrive with a solution looking for a workflow. Most consultants arrive with a deck. Neither of those approaches produces the artifact an examiner will ask to see or the operating discipline a lean team can actually sustain.
Bank Ready AI is a small, senior advisory practice built around a simple premise: an AI deployment is only as defensible as the design it started from. Executive teams keep control of the strategy, the stack, and the vendor relationships. I provide the specification, the governance architecture, and the second set of eyes an under-resourced team doesn’t otherwise have.
VIStart the conversation
If AI is on your board agenda, it should be designed before it’s deployed.
A complimentary 20-minute go/no-go call with Alex Zaboli to discuss one AI use case and make a preliminary decision on the next step: explore further, gather more information, or pause. This is not a conclusive feasibility assessment; technical, operational, and governance diligence is required before an implementation decision.
Microsoft Bookings lets you book as a guest — no Microsoft account is required.