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BUILT FOR BANKING · AI

Built for Banking AI That's Documented, Governed, and Explainable — by Design

Every cybersecurity vendor is racing to market AI. DefenseStorm is building AI the way banks build trust — with documentation, oversight, and accountability at every step.

Our AI capabilities are governed by seven Built for Banking AI Principles, mapped to the frameworks your institution already reports against: NIST AI RMF and CRI AI RMF. Every AI output is explainable to a non-technical professional. Every capability is inventoried and documented. Because when your examiner asks how your vendor's AI is governed, the answer should be a transparency package — not a phone call to your sales rep.

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Framework-aligned AI governance

NIST AI RMF CRI AI RMF
Ai_Risk

Your vendor's AI is your institution's risk.

When a cybersecurity vendor deploys AI inside your security operations, your institution inherits a risk it must govern, document, and explain to its examiner. Not the vendor — the institution.

The NCUA launched an AI hub, and banking regulatory guidance is pending.

Governing AI requires the same discipline as governing any other system — inventory, documentation, oversight, accountability. Whether you can apply it depends on what your vendor lets you see.

The question is not whether your vendor uses AI. The question is whether your vendor’s AI can be defended under examination without the vendor in the room.

The DefenseStorm Standard
AI in GRID Active must be defendable to your examiner — without DefenseStorm in the room.
If the customer's risk officer cannot explain what the AI does, how it works, what data it uses, and what controls govern it — DefenseStorm has created a problem for the people it claims to serve.

THE SEVEN BUILT FOR BANKING AI PRINCIPLES

Seven Principles. One Standard. Built for Your Examiner.

These seven principles are the operating standard governing every AI capability inside GRID Active, DefenseStorm's intelligent data engine. They are not aspirational. They are the current operating posture — documented, auditable, and mapped to the frameworks your institution already reports against.

Principle 1
Visibility

Every AI capability is inventoried, documented, and visible to the customer. No hidden models. No undocumented machine learning. Institutions with no-AI policies can disable AI features entirely — a product capability, not a configuration workaround.

Principle 2
Explainability

Every AI output is explained in terms a non-technical professional understands. Confidence levels are visible in the platform interface. Mandatory operator feedback loops serve multiple purposes including drift detection.

Principle 3
Documentation

Model cards for every AI feature serve as artifacts for due diligence — not marketing collateral.

Principle 4
Governance Structure

DefenseStorm’s internal AI governance includes defined roles and responsibilities for AI governance, internal AI acceptable use policy, review and approval processes before ship, testing and validation standards, drift monitoring, and AI-specific incident response procedures.

Principle 5
Fourth-Party Transparency

Full disclosure of every external AI model or API operating within GRID Active — including data flows, retention and training practices, contractual protections, security posture, and contingency plans. The visibility you need to manage fourth-party risk.

Principle 6
Security of AI Components

Protection against adversarial attacks, data poisoning, prompt injection, and unauthorized access. AI components are secured to the same standard as every other platform component, with failover and resilience requirements.

Principle 7
Framework Alignment

AI governance maps explicitly to the frameworks FIs use, so they can demonstrate compliance through our documentation. The goal: reduce the compliance burden.

AI Capabilities in Production

Live in Production. Governed by Principle.

UEBA Threat

Behavior-aware threat detection that identifies anomalous user and entity activity within your environment. Risk-scored events are triaged inside CTS Ops with banking context, generating structured evidence for governance reporting.

Governed by:

All seven Built for Banking AI Principles. Model card documented. Operator feedback loops active.

LEARN MORE: EXPLORE MDR FOR BANKING

Gen AI Query Assistant

Plain-English access to GRID Active data. Ask questions about your security environment in natural language and receive auditable, logged responses. Every query is tracked for governance.

Governed by:

All seven Built for Banking AI Principles. Every query logged and auditable. Fourth-party AI providers fully disclosed.

LEARN MORE: EXPLORE GRID ACTIVE

What's Next

DefenseStorm's AI roadmap expands capabilities under the same governance standard. Every new AI feature ships with a model card, framework alignment documentation, and human sign-off boundaries — because earned autonomy means capability grows step by step, not all at once.

Framework Alignment

Mapped to the Frameworks Your Institution Already Reports Against

Built for Banking AI Principle NIST AI RMF CRI FS AI RMF v1.0
Visibility Govern Inventory & Classification
Explainability Map, Measure Explainability & Interpretability
Documentation Govern, Map Documentation & Reporting
Governance Structure Govern Governance & Accountability
Fourth-Party Transparency Govern, Map Third-Party AI Management
Security of AI Manage Security & Resilience
Framework Alignment All functions All control families

AI Governance Comparison

Not All AI Is Governed the Same Way

AI Governance Criteria DefenseStorm Horizontal MDR Vendors FI-Vertical Security
AI inventory documented
Right Icon Yes
Right Icon No
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Model cards per AI feature
Right Icon Yes
Right Icon No
Right Icon No
Fourth-party AI disclosed
Right Icon Yes
Right Icon No
Right Icon No
Mapped to NIST AI RMF
Right Icon Yes
Right Icon No
Right Icon No
Mapped to CRI Profile
Right Icon Yes
Right Icon No
Right Icon No
AI opt-out capability
Right Icon Yes
Right Icon No
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Examiner-ready AI docs
Right Icon Yes
Right Icon No
Right Icon No

Frequently Asked Questions

What are the Built for Banking AI Principles?
The Built for Banking AI Principles are seven operating standards that govern every AI capability inside DefenseStorm’s GRID Active platform: Visibility, Explainability, Documentation, Governance Structure, Fourth-Party Transparency, Security of AI Components, and Framework Alignment. They are mapped to NIST AI RMF and CRI AI RMF.
Does DefenseStorm use third-party AI models?
Yes, and DefenseStorm fully discloses every external AI model or API operating within the platform. Fourth-Party Transparency is one of the seven B4B AI Principles — relevant data is documented to facilitate due diligence and fourth-party risk management.
Can a bank opt out of AI features in DefenseStorm?
Yes. Institutions with no-AI policies can disable AI features entirely. This is a product capability, not a configuration workaround. DefenseStorm recognizes that some institutions may have policies that prohibit AI, and the platform respects that requirement.
How does DefenseStorm's AI governance map to NIST AI RMF?
DefenseStorm’s seven B4B AI Principles are organized under NIST AI RMF’s four core functions: Govern, Map, Measure, and Manage. Each principle maps to specific NIST functions as well as CRI AI RMF control objectives.
What AI capabilities does DefenseStorm currently offer?
DefenseStorm currently has two AI capabilities in production: UEBA Threat (behavior-aware detection with banking-context risk scoring) and Gen AI Query Assistant (plain-English access to GRID Active data, fully logged and auditable). Both are governed by all seven B4B AI Principles with model cards documented.
How is DefenseStorm's approach to AI different from competitors?
Most cybersecurity vendors market AI that’s faster. DefenseStorm builds AI that surfaces the information leadership needs to make meaningful decisions — and documents it so your examiner can verify it. The difference: when your examiner asks how your vendor’s AI is governed, DefenseStorm provides a transparency package mapped to NIST AI RMF and CRI AI RMF. Competitors provide a marketing slide or nothing at all.
What is 'earned autonomy' in DefenseStorm's AI approach?
Earned autonomy means AI capability grows step by step, under explicit policy, with human sign-off boundaries. DefenseStorm does not deploy fully autonomous AI. Every critical decision involves human-in-the-loop oversight from CTS Ops banking experts or users at the institution, with clear escalation paths.
Can I share DefenseStorm's AI governance documentation with my examiner?
Yes. DefenseStorm provides a Customer Due Diligence Package that includes AI Feature Inventory, Model Cards, Fourth-Party AI Disclosure, Privacy and Data Governance documentation, AI Governance Policy Summary, and Framework Alignment Maps — designed specifically for examiner review and vendor due diligence.

When your examiner asks  about AI, be ready.

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