Artificial Intelligence/Financial Artificial Intelligence
Financial Artificial Intelligence
Put AI to Work. Protect the Institution. Demonstrate the Governance.
Artificial intelligence is changing how financial institutions serve clients, manage risk and compete. Gregg Global helps broker-dealers, investment advisers, banks, credit unions, insurers and fintechs identify where AI can create meaningful value, select the appropriate technologies, securely integrate AI into financial workflows, establish governance and validate results. We begin with the challenge, not the technology.
The Opportunity Is Larger Than Automation
The question is not where an institution can use AI. It is where AI can improve the way financial work gets done.
AI should enhance institutional capability, not simply add another technology layer.
From Financial Objective to Responsible AI
The Gregg Global Financial AI framework.
Assess
Prioritize
Architect
Implement
Secure
Govern
Verify
Evolve
Core areas
- Financial AI Readiness & Opportunity Assessment
- Architecture selection
- Private and controlled AI
- Workflow transformation
- AI security and Shadow AI
- AI vendor risk
- Regulatory intelligence and compliance support
- Governed/reliable AI
- PROP/hybrid architecture
- Agentic AI
- Human oversight
- Verification and ongoing leadership
Start With the Work. Not the Technology.
Financial AI Readiness & Opportunity Assessment
Before selecting technology, Gregg Global helps organizations understand what they are trying to accomplish, which workflows create the greatest opportunity, what information is involved, what technology is appropriate, and where fiduciary and professional judgment must remain. The result is a prioritized Financial AI roadmap connecting use cases, technology, information, governance and implementation.
AI Does Not Remove the Regulatory Obligations Attached to Financial Information
Select an institution type.
Applicability depends on registration status, charter, activities and jurisdiction. As of today, most financial AI oversight sits at the guidance and supervisory-priority level rather than as a single binding AI rule — precision matters, so we distinguish final requirements from guidance, proposals and withdrawn rules.
Model Risk Management for AI
The interagency Model Risk Management guidance was revised in April 2026 (OCC Bulletin 2026-13, jointly issued with the Federal Reserve and FDIC), replacing the prior SR 11-7 / OCC 2011-12 framework. Notably, the revised guidance explicitly excludes generative and agentic AI from its formal scope, leaving a supervisory gap institutions must self-govern until dedicated guidance is issued.
No Final AI-Specific Rule
The SEC's 2023 proposed rule on predictive data analytics and AI conflicts of interest was formally withdrawn in June 2025 — it is not current law. FINRA's guidance (Regulatory Notice 24-09, and the GenAI section of its 2026 Annual Regulatory Oversight Report) reminds members that existing supervision, communications and recordkeeping rules already apply to AI use; neither document creates new binding requirements.
State-by-State, Model Bulletin Driven
The NAIC's Model Bulletin on the use of AI systems by insurers (adopted December 2023) is a non-binding model — it only takes effect where a state insurance department separately adopts it, which roughly half of states have done. NYDFS addresses insurer AI use in underwriting and pricing through Circular Letter No. 7 (2024), distinct from its Part 500 cybersecurity regulation.
Examination Priority, Not Yet a Rule
NCUA maintains an AI resource hub and has named AI oversight an examination priority, but has not issued a binding AI-specific model-risk regime. Credit unions are examined under existing vendor-management, fair-lending and BSA/AML frameworks.
Regulatory applicability varies based on registration status, activities, jurisdiction, information handled, and other circumstances. This module is for general orientation only and does not provide legal advice, regulatory opinions, or a determination of whether a specific law or regulation applies to a particular organization. Gregg Global distinguishes final, binding requirements from guidance, supervisory priorities, proposed rules and withdrawn proposals, and verifies status against current primary authority before publication.
Not Every Financial Problem Requires the Same AI
The Right AI for the Right Financial Work.
LLM
Strong applications may include research, summarization, natural-language client communications, and drafting.
Private AI
May be appropriate where greater control is required over client data, proprietary research, infrastructure and model access.
Propositional AI
May be valuable where the workflow places greater importance on factual grounding, repeatability, source provenance, deterministic reasoning, and auditability — such as compliance reporting and regulatory filings. Complementary to LLMs, not a replacement.
Hybrid AI
Combines architectures according to the requirements of different workflow stages — for example, LLM interpretation → approved information → proposition-based reasoning → governance → human review → LLM presentation.
Specialized AI
Purpose-built models for fraud detection, AML monitoring, underwriting support and other defined financial functions.
The Right AI for the Right Financial Work.
Sensitive Information May Require a Different AI Environment
Private & Controlled AI
Publicly available AI is not the only option. Solutions may include private AI environments, on-premises AI, controlled knowledge environments, and role-based permissions.
The appropriate environment depends upon the information, use case, security requirements and the institution's risk profile.
Your AI Environment May Be Larger Than Your Approved Technology List
Shadow AI Governance & Control
Advisors and staff can adopt AI applications faster than an institution can approve and govern them. A policy is important. But policy alone does not control technology.
Discover → Assess → Approve → Govern → Enforce → Monitor
AI Can Assist the Advisor. It Does Not Replace Fiduciary Judgment.
As AI systems become more capable and autonomous, fiduciary responsibility becomes more important, not less.
AI Capability
- Research
- Analyze
- Extract
- Summarize
- Draft
- Recommend
- Automate
Human Fiduciary Judgment
- Review
- Verify
- Interpret
- Approve
- Advise
- Decide
- Take responsibility
Use AI to expand institutional capability while preserving the judgment fiduciary and suitability obligations require.
Financial AI Risk Is About More Than Hallucinations
Responsible Financial AI requires controls appropriate to the use case.
From Plausible Output to Verifiable Work
Governed & Verifiable AI
Some financial applications require more than a fluent response — what source supports this statement, was the information authorized, can the result be reproduced, was human approval required?
Define
Establish authoritative information, users, permissions and objectives.
Ground
Connect factual claims to approved sources.
Govern
Apply permissions, policies, constraints, approvals and escalation.
Prove
Preserve supporting evidence and a reviewable record.
When AI Can Act, Governance Must Move With It
Agentic AI
AI is progressing from systems that answer questions toward agents capable of initiating tasks, accessing tools, sequencing activities and taking actions within financial workflows. That creates opportunity — and changes the control environment.
Identity
Who or what is acting?
Access
What information can it access?
Permission
What tools can it use?
Action
What actions can it take?
Approval
When is human approval required?
Evidence
How is the action documented?
Put AI Into the Workflow
Financial AI Workflow Transformation
The value is not simply having AI. It is improving the work.
Identify → Design → Integrate → Govern → Train → Measure
AI Is Becoming Part of the Client Relationship
A mature AI program can become part of the institution's value proposition.
Clients, boards and examiners increasingly care not simply whether an institution uses AI, but how it affects accuracy, information protection, fairness, pricing and service. Institutions should be prepared to explain where AI is used, how client information is protected, and where human review occurs.
AI Does Not Stand Still. Neither Should Your Strategy.
Financial AI Leadership & Advisory
Financial Artificial Intelligence Capabilities
AI Strategy & ReadinessAssessments through roadmap
Financial AI Workflow TransformationStrategy into working systems
Private & Secure AIControlled environments
AI Governance & Shadow AIPolicy and technical controls together
AI Technology & Architecture AdvisoryTechnology-independent selection
Governed & Verifiable AIBeyond plausible output
Agentic AI GovernanceWhen AI can act
AI Security & Data ProtectionThe cybersecurity of financial AI
Model Risk & Regulatory AlignmentDistinguishing rule from guidance
Financial AI LeadershipOngoing strategy and reassessment
Why Gregg Global
Financial + Technology + Risk
Financial AI sits at the intersection of institutional trust, information, technology and regulatory risk.
Technology Independent
We begin with the challenge rather than a predetermined platform.
Regulatory Precision
We distinguish binding requirements from guidance, proposals and withdrawn rules, verified against current primary authority.
Security Integrated
Security and information protection incorporated from the beginning.
Emerging Technology
We evaluate LLMs, private AI, proposition-based architectures, agents and other emerging approaches.
Implementation Focused
Strategy progresses into workflow integration, implementation, governance, training and support.
Sophisticated Capabilities. Designed for the Financial Environment.
Begin With the Financial Challenge.
You do not need to know which AI platform to buy. You do not need to determine whether the answer is an LLM, private AI, proposition-based AI, an agent, or a combination. And you do not need a completed AI strategy before talking with us. We can start there.
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Discuss Your Financial AI Strategy
Gregg Global provides technology, cybersecurity, risk, investigative and advisory services. Gregg Global does not provide legal advice, legal representation, regulatory opinions or insurance coverage advice. Regulatory requirements vary by institution, registration, activity, jurisdiction and circumstances. Organizations should consult qualified legal and compliance professionals regarding requirements applicable to their specific use of artificial intelligence.