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    Bank Ready AI · Governed Build Specification

    AI-Driven Embedded Finance & Third-Party Oversight

    BaaS & Fintech Partnership RiskCommunity Bank or Credit Union · BaaS / fintech programsStatus: Configured

    This specification is written to be circulated: to risk, to compliance, to technology, and to the examiner. Part I documents the technical build. Part II documents the human capability that makes it defensible.

    Part I

    The Technical Build

    Model & Retrieval

    • Vendor AI review platform (hosted LLM — ARMAI-style intelligent review engines)
    • RAG grounded in policies, SOC reports, contracts, and regulatory guidance
    • Structured + unstructured ingestion across the vendor evidence file

    Deployment

    • Risk/compliance staff portal with API into vendor-management systems
    • Agentic due-diligence and compliance-lifecycle workflow automation
    • Deployed alongside the core processor's infrastructure (Jack Henry at FFBKC)

    Controls

    • Human-in-the-loop review of every AI risk determination — no automated vendor actions
    • Examiner-ready audit trail: every assessment traceable to source evidence
    • Explainability on risk scores and flagged findings
    • PII / NPI handling under GLBA safeguards
    • Recursive governance: the oversight tool is itself a third-party AI vendor with its own TPRM file, model-inventory entry, and validation cadence

    Channels

    • Risk & compliance staff portal
    • API / back-end integration with vendor-management systems

    Part II

    The Human Build

    AI Compliance Officer

    Keeps the oversight program — and the tool itself — inside the regulatory perimeter.

    Visible skills

    BSA/AML Compliance · Regulatory Exam Preparation · AI Audit & Internal Controls

    Governance depth

    Emerging AI Regulation Tracking · AI Policy Development · Model Risk Management (SR 26-2 / NCUA)

    IT Lead for AI Integration

    Connects the review platform to vendor-management and core systems.

    Visible skills

    Core Banking Platform Integration · API Integration & Development · AI Vendor API Management

    Governance depth

    AI Security & Data Privacy · On-Premises / Hybrid AI Deployment · AI Model Inventory & Lifecycle Tracking

    AI Governance Committee Member

    Owns the recursive-governance question: who governs the tool that governs your vendors?

    Visible skills

    Board & Executive Reporting · Third-Party AI Risk Management · AI Ethics & Responsible AI

    Governance depth

    AI Governance Committee Leadership · AI Risk Framework Alignment (NIST AI RMF) · AI Training & Awareness

    Part III

    The Integration Plan

    Confirmed adopters of this use case: First Federal Bank of Kansas City.

    Phase 1 · Foundation — Govern the tool before it governs anyone

    Technical workstream

    • Vendor due diligence on the oversight platform itself — the recursive step comes first
    • Ringfence input sources: which policies, contracts, and SOC reports the engine may ingest

    Human workstream

    • Stand up the TPRM file and model-inventory entry for the AI tool itself
    • Committee approves scope, risk appetite, and the five evidence outcomes as the acceptance bar

    Phase 2 · Pilot — One partner, parallel-run against manual review

    Technical workstream

    • Run AI due diligence on a single fintech partner alongside the existing manual process
    • Benchmark AI evidence outputs against the manual file for completeness and accuracy

    Human workstream

    • Risk staff disposition AI findings with documented rationale
    • Committee reviews parity results and the audit-trail quality before expansion

    Phase 3 · Production — Full portfolio on the evidence-outcome cadence

    Technical workstream

    • Expand to the full partner portfolio with monitoring dashboards
    • Automate evidence-outcome documentation for examination requests

    Human workstream

    • Quarterly board reporting on program risk posture
    • Annual revalidation of the oversight tool — recursive governance as a standing agenda item

    Part III

    Verification Benchmarks

    • Five evidence outcomes produced per partner review: risk analysis, use-case documentation, vendor governance, failure response, performance monitoring
    • Parallel-run parity: AI due-diligence file matches or exceeds manual review completeness
    • Audit-trail traceability: every risk determination resolves to named source evidence
    • Recursive-governance check: the tool's own TPRM file and validation stay current
    Adopter assets
    ~$1B

    First Federal Bank of Kansas City, Q1 2026

    Customers served
    25,000

    Across 9 Kansas City-metro branches

    Evidence outcomes
    5

    Risk, use case, vendor, failure, monitoring — the examiner checklist

    Adopters / vendors
    1 / 1

    FFBKC × ARMAI — early-mover recursive-governance pattern