Built for Banks, Credit Unions & Financial Institutions

Examiner-Ready Private AI, Deployed Inside Your Network

FDIC, OCC, NCUA, and state examiners are already asking how your institution governs AI. Your staff is already using it with customer data. Cognetryx gives you a governed alternative that runs entirely inside your bank or credit union, so NPI never leaves and your next exam has the simplest possible answer.

Book a Free AI Strategy Assessment → See the Compliance Pitch Framing

FIL-29

FDIC third-party risk guidance now puts AI tools in scope

FDIC, 2024

BAAs, data-sharing agreements, or Reg P disclosures needed when data stays inside

Architectural outcome

90 days

Typical time from kickoff to production deployment

Cognetryx engagements

The Problem

Why Cloud AI Cannot Clear a Banking Examiner

Cloud AI in a regulated financial institution means stacking vendor reviews, third-party risk assessments, data-sharing agreements, and governance layers on top of a tool that was never designed for GLBA. Most initiatives stall at the compliance review. The ones that do not stall often create exam findings later.

Third-Party Risk

FIL-29-2024 Put AI Squarely in Exam Scope

FDIC, OCC, and Federal Reserve third-party risk management guidance applies to any vendor touching your data. Cloud AI processors require the full third-party risk lifecycle: due diligence, contracts, ongoing monitoring, and exit planning. Most community banks cannot resource that for every AI tool staff wants to use.

Shadow AI

Your Staff Is Already Using AI With Customer Data

Loan officers paste borrower information into ChatGPT to draft adverse action notices. Compliance staff use consumer AI to summarize complaint responses. This creates untracked NPI flows that examiners will eventually find, and that institutions cannot easily document after the fact.

GLBA Exposure

Nonpublic Personal Information Cannot Just Leave

GLBA and the Safeguards Rule require specific safeguards for NPI. Cloud AI creates data flows to external servers that may or may not meet your written information security program. A bolted-on redaction layer is not an architecture. It is a patch on a structural problem.

Most community banks and credit unions have concluded they cannot safely adopt AI at institutional scale. The accurate conclusion is narrower: they cannot safely adopt cloud-based AI. When AI runs inside the institution's own network, third-party risk collapses, NPI never leaves, and the exam conversation changes entirely.

The Answer

An Architecture Your Examiner Can Defend

Cognetryx deploys entirely inside your institution's network. No NPI leaves. Every interaction is logged. Every output traces back to your own policies, procedures, or documentation. The exam story is built into the architecture, not assembled at the last minute.

🔒

NPI Never Leaves Your Network

No third-party processing. No cloud data residency questions. The AI is internal infrastructure, governed by your existing Safeguards Rule controls and information security program.

📋

Immutable Audit Logging

User identity, timestamp, source document referenced, and output generated are logged for every query. Examiners get the audit trail your compliance team already knows how to produce.

🔑

Access Follows Existing IAM

The AI inherits the same role-based controls you already use for core banking, loan origination, and customer data. No parallel access system to build or document.

📚

Grounded in Your Own Policies

Loan policy, compliance manuals, BSA procedures, deposit operations, HR handbook, and internal memos are indexed. Responses cite approved source material, not the open internet.

🏛️

You Own the Deployment

Infrastructure, data, and any fine-tuned model weights belong to your institution. No vendor roadmap surprises, no licensing changes, no deprecation risk on models your staff depends on.

⚡

Faster Than the Shadow Tool

Shadow AI wins when sanctioned tools are slower or less useful. Cognetryx beats ChatGPT on your own policy questions because it actually knows your institution's documentation, not just the public web.

Where Institutions Start

High-Leverage Use Cases in Banking and Credit Unions

Most institutions see fastest ROI when AI handles the work that is already documented, already governed, and already repetitive. Cognetryx is designed to operationalize existing institutional knowledge, not replace expert judgment.

📑

Policy & Procedure Lookup

Frontline staff get immediate, cited answers from your loan policy, deposit operations manual, or compliance procedures without escalating to a supervisor or pulling a department head into a routine question.

🏦

Loan File Summarization

Credit analysts summarize borrower documentation and commentary histories grounded in your own file structure and underwriting standards. Output stays in your network, logged, and tied to source documents.

⚖️

Complaint Response Drafting

Compliance staff generate first-draft responses to member or customer complaints anchored in your institution's actual handling precedents and regulatory obligations, not generic legal language.

🔍

Exam & Audit Preparation

When examiners arrive, compliance teams can query institutional memory directly: how a specific policy was applied, which board minutes reference a control, or where a particular procedure was last updated.

🎓

Staff Onboarding & Training

New hires get consistent, institution-specific answers to routine questions that normally consume supervisor time. Onboarding accelerates and interpretive variance across staff falls.

📊

Board & Regulatory Reporting

Assemble first-draft board materials, exam responses, and regulatory filings from source documents already governed inside your institution. Humans review and approve. The AI shortens the drafting cycle.

Compliance Mapping

How the Architecture Addresses What Examiners Ask

Federal, state, and prudential examiners are converging on the same questions about AI governance. Here is how Cognetryx directly addresses each framework without bolt-on tooling.

Framework

The Requirement

How Cognetryx Addresses It

FDIC FIL-29-2024

Third-party risk management expectations covering any vendor that handles institution data, explicitly including AI tools.

No third-party data processing occurs. Deployment is internal infrastructure governed by existing vendor management frameworks rather than cloud processor reviews.

OCC Third-Party Risk Guidance

Due diligence, contract terms, ongoing monitoring, and exit planning for third parties with access to bank data.

Because data never reaches a third party, lifecycle obligations collapse to a professional services and support relationship.

NCUA Supervisory Expectations

Letters to Credit Unions on IT risk, information security, and AI governance under member data protection obligations.

Member data remains inside the credit union's network. Existing information security program applies. CUSO and league deployment models supported.

GLBA Safeguards Rule

Administrative, technical, and physical safeguards for nonpublic personal information.

Existing Safeguards Rule controls extend natively to the AI deployment. NPI never leaves the protected environment.

FFIEC IT Handbook

IT governance, risk assessment, and information security expectations examined by federal and state regulators.

Architecture aligns with FFIEC principles for data governance, access control, audit trail, and change management.

NIST AI RMF

Voluntary but increasingly referenced framework for AI governance, mapping functions across govern, map, measure, and manage.

Traceable reasoning, source citation, audit logging, and human-in-the-loop controls support the full RMF profile.

Built For Banking Leadership

A Partner Your Examiner Will Recognize as Architecture, Not a Patch

Cognetryx is led by a CISSP-certified founder with nearly 20 years of experience building secure infrastructure for regulated industries, and a Head of Go-to-Market who spent nearly two decades inside banking and credit unions. We understand the examiner conversation because we have sat on the other side of it.

Our engagement model is white-glove by default: board and executive briefings, staff training, compliance team walkthroughs, and 30 days of on-site support at go-live. We want your next exam to be easier than your last one.

CISSP FDIC / OCC NCUA GLBA / Safeguards FFIEC NIST AI RMF

Keith Kennedy

Founder & CEO, CISSP

"Examiners are not looking for AI features. They are looking for a defensible architecture. That is a completely different conversation, and it is the one we are here to have."

Keith has advised mid-market and enterprise institutions on SEC/FINRA, HIPAA, and GDPR compliance, ERP migrations, and secure infrastructure builds. He leads the technical and security posture of every Cognetryx deployment.

Common Questions

What Banking and Credit Union Leaders Ask

Does Cognetryx meet FDIC and OCC examiner expectations for third-party risk? +

Because Cognetryx deploys inside your institution's network, we occupy a different regulatory position than a cloud AI vendor. Your data never reaches a third-party processor. For third-party risk management under FDIC FIL-29-2024 and OCC guidance, Cognetryx is treated as an infrastructure and professional services relationship rather than a cloud data processor. Your existing vendor management framework governs the engagement, and every AI interaction is auditable inside your environment.

How does this work for credit unions under NCUA oversight? +

Credit unions operate under NCUA examination with specific expectations around member data, IT governance, and third-party risk. Cognetryx deploys entirely inside the credit union's network, meaning member data never leaves the institution. NCUA Letters to Credit Unions on IT risk, information security, and AI governance are addressed architecturally rather than through bolt-on controls. CUSOs and leagues can also operate Cognetryx on behalf of member institutions.

What about GLBA, Reg P, and Safeguards Rule obligations? +

The GLBA Safeguards Rule requires administrative, technical, and physical safeguards for nonpublic personal information. Cognetryx inherits your existing Safeguards Rule controls because the system runs inside your network. Nonpublic personal information never leaves your environment, so Reg P sharing considerations with third-party AI vendors do not apply. Your existing written information security program covers the deployment.

How does Cognetryx handle shadow AI already happening at our institution? +

Shadow AI in banks and credit unions usually means staff pasting customer information into ChatGPT to draft denial letters, summarize loan files, or write policy language. It is a symptom of documentation burden, not a discipline problem. When your staff has a governed tool that is genuinely faster than the unsanctioned one and grounded in your institution's own policies, shadow AI drops sharply. Cognetryx is built to be that better tool.

What happens during an FDIC, OCC, NCUA, or state examination? +

Every AI interaction is logged with user identity, timestamp, source document referenced, and output generated. Your compliance and audit teams own this trail and can produce it on demand. Because data never left your network, the examiner's hardest question has the simplest answer. We have built the system specifically to support exam preparation workflows, so compliance teams spend less time scrambling and more time responding with confidence.

How long does deployment take for a community bank or credit union? +

Most mid-market institution deployments reach pilot stage in 6 to 10 weeks, with full production rollout in 90 days. Cognetryx includes white-glove onboarding, staff training, board presentations, and 30 days of on-site support at go-live. Timeline depends on infrastructure readiness and the scope of institutional documentation to be integrated. Smaller institutions can often deploy faster because their documentation footprint is more contained.