SCBE-AETHERMOORE: Bank Pilot Program

Document: BANK-PILOT-2026-001 Classification: Business Development Target: Financial Institution Innovation & Security Teams

Executive Summary

SCBE-AETHERMOORE provides quantum-safe, explainable authorization and transport fabric for high-risk AI and service-to-service traffic in banking environments.

What We Solve:

  • AI agents and microservices can exfiltrate, trade, or misconfigure at machine speed
  • Current solutions detect anomalies after the fact; we prevent unauthorized actions deterministically
  • Quantum computers will break RSA/ECC within 5-10 years; banks need PQC-ready infrastructure now

How We Fit:

  • Sits under or beside SWIFT, MQ, gRPC, Kafka
  • Uses NIST-approved post-quantum cryptography (ML-KEM-768, ML-DSA-65)
  • Integrates with existing IAM (OIDC/SAML/OAuth2)

1. The Bank Problem

Current State 

AI Agent → [No Governance] → Payment Queue → Transaction Executed
                ↓
         No audit trail
         No mathematical proof of authorization
         Vulnerable to quantum attack

With SCBE-AETHERMOORE 

AI Agent → [SCBE 14-Layer Check] → [Cryptographic Token] → Payment Queue
                ↓                          ↓
         ALLOW/QUARANTINE/DENY      Tamper-proof audit
         Explainable score          Quantum-resistant
         Real-time decision         HSM-compatible

2. Pilot Scenario: AI Agent Governance

Use Case: Fraud Analytics AI Agents

Scenario: Bank deploys AI agents for real-time fraud detection. Agents need to:

  • Read transaction streams
  • Flag suspicious patterns
  • Trigger holds or alerts
  • Update detection rules

Risk: Compromised or malfunctioning agent could:

  • Approve fraudulent transactions
  • Leak customer data
  • Modify detection rules to create blind spots

SCBE Solution

Agent Action SCBE Governance Outcome
Read transactions Token scope check ALLOW if authorized realm
Flag fraud Trust score + policy ALLOW with audit seal
Trigger hold Multi-signature consensus ALLOW if 3/5 agents agree
Modify rules Elevated trust required QUARANTINE for human review
Exfiltrate data Position outside boundary DENY + noise response

Technical Flow 

1. Agent requests action token from SCBE Gateway
2. SCBE computes 6D position in hyperbolic space
3. 14-layer pipeline evaluates:
   - Identity verification (PQC signature)
   - Trust score (behavioral history)
   - Policy compliance (action + target)
   - Consensus (for sensitive ops)
4. Decision: ALLOW / QUARANTINE / DENY
5. If ALLOW: Sealed envelope with proof
6. All decisions logged to tamper-proof audit

3. Architecture: Bank Integration 

┌─────────────────────────────────────────────────────────────────┐
│                     BANK INFRASTRUCTURE                          │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  ┌──────────┐    ┌──────────────────────────────────────────┐   │
│  │ AI Agents │───▶│         SCBE-AETHERMOORE GATEWAY         │   │
│  │ (Fraud,   │    │  ┌────────────────────────────────────┐  │   │
│  │  Ops,     │    │  │     14-Layer Governance Pipeline   │  │   │
│  │  Analytics)│    │  │  ┌─────┐ ┌─────┐ ┌─────┐ ┌─────┐  │  │   │
│  └──────────┘    │  │  │L1-L4│→│L5-L7│→│L8-11│→│L12-14│ │  │   │
│                   │  │  │Embed│ │Geom │ │Trust│ │Decide│  │  │   │
│                   │  │  └─────┘ └─────┘ └─────┘ └─────┘  │  │   │
│                   │  └────────────────────────────────────┘  │   │
│                   │                    │                      │   │
│                   │         ┌──────────┴──────────┐          │   │
│                   │         ▼                     ▼          │   │
│                   │    ┌─────────┐          ┌─────────┐      │   │
│                   │    │  ALLOW  │          │  DENY   │      │   │
│                   │    │ + Token │          │ + Noise │      │   │
│                   │    └────┬────┘          └─────────┘      │   │
│                   └─────────┼────────────────────────────────┘   │
│                             │                                    │
│                             ▼                                    │
│  ┌──────────────────────────────────────────────────────────┐   │
│  │                  EXISTING BANK SYSTEMS                    │   │
│  │  ┌────────┐  ┌────────┐  ┌────────┐  ┌────────────────┐  │   │
│  │  │ SWIFT  │  │ Kafka  │  │  IAM   │  │ SIEM/SOC       │  │   │
│  │  │ISO20022│  │   MQ   │  │OIDC/SSO│  │(Splunk/QRadar) │  │   │
│  │  └────────┘  └────────┘  └────────┘  └────────────────────┘  │   │
│  └──────────────────────────────────────────────────────────┘   │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

Integration Points

Bank System SCBE Integration Purpose
IAM (Okta, Ping, Azure AD) OIDC/SAML adapter Map existing identities to SCBE agents
Message Queue (Kafka, MQ) Sidecar proxy Govern message publish/subscribe
API Gateway Policy enforcement point Pre-authorize API calls
SWIFT/ISO 20022 Message sealing Tamper-proof payment messages
SIEM (Splunk, QRadar) Audit log export All decisions → security analytics
HSM (Thales, nCipher) Key storage PQC keys in hardware

4. Regulatory Mapping

GLBA / Gramm-Leach-Bliley Act

GLBA Requirement SCBE Capability
Safeguard customer information Sealed envelopes with PQC encryption
Access controls 14-layer authorization with audit
Encryption in transit ML-KEM-768 key encapsulation

PCI-DSS v4.0

PCI Requirement SCBE Capability
3.5: Protect stored keys HSM integration, forward secrecy
4.2: Strong cryptography in transit AES-256-GCM + PQC
7.1: Least privilege Token-based action authorization
10.1: Audit trails Tamper-proof decision logs

DORA (EU Digital Operational Resilience Act)

DORA Requirement SCBE Capability
ICT risk management Mathematical risk scoring
Incident reporting Real-time audit with timestamps
Third-party risk Agent trust scoring
Resilience testing Chaos/fault injection support

Zero Trust Architecture (NIST SP 800-207)

ZTA Principle SCBE Implementation
Never trust, always verify Every action requires fresh token
Least privilege Scoped tokens per action
Assume breach Fail-to-noise, no information leak
Continuous monitoring Real-time trust decay

5. Pilot Timeline: 10-Week Program

Phase 1: Discovery (Weeks 1-2)

  • Security architecture review
  • Identify pilot scope (AI agents, traffic type)
  • Map to existing IAM/network
  • Threat model documentation

Phase 2: Lab Deployment (Weeks 3-5)

  • Deploy SCBE Gateway in innovation VPC
  • Configure test agents (3-5)
  • Integrate with test IAM
  • Run basic governance scenarios

Phase 3: Integration (Weeks 6-8)

  • Connect to SIEM for audit logs
  • Configure policies for pilot use case
  • Load testing (latency/throughput)
  • Operator dashboard setup

Phase 4: Validation (Weeks 9-10)

  • Security team review
  • Compliance mapping documentation
  • Performance report
  • Go/no-go decision for production

Deliverables

Deliverable Format Purpose
Threat Model PDF/Markdown Security committee review
Integration Spec Technical doc Engineering handoff
Latency Report Metrics dashboard Performance validation
Audit Export SIEM-compatible Compliance evidence
Runbook Operations doc Incident response

6. Pricing Model

Option A: Pilot License

| Item | Price | |——|——-| | 10-week pilot program | $50,000 | | Includes: Gateway, support, integration help | | | Success criteria defined upfront | |

Option B: R&D License

| Item | Price | |——|——-| | Annual license (non-production) | $100,000/year | | Source code access | Included | | Integration support | 40 hours |

Option C: Production License

| Item | Price | |——|——-| | Enterprise license | $250,000-500,000/year | | Unlimited agents | Included | | 24/7 support | Included | | Custom integrations | Scoped separately |

7. Why SCBE vs Alternatives

Capability SCBE-AETHERMOORE Darktrace CrowdStrike
Approach Preventive (math) Detective (ML) Detective (ML)
AI Agent Focus Purpose-built Retrofitted Not designed for
Quantum-Safe ML-KEM, ML-DSA No No
Explainable Decisions Full score breakdown Black-box ML Black-box ML
Fail Mode Noise (no info leak) Alert after breach Alert after breach
Audit Trail Cryptographic proof Log-based Log-based

Our Position: Complement, not replace. SCBE handles prevention for machine-to-machine flows; existing tools handle detection for human behavior.

8. Quick Demo (60 Seconds) 

# Clone and run
git clone https://github.com/ISDanDavis2/scbe-aethermoore-demo.git
cd scbe-aethermoore-demo
pip install -r requirements.txt
python demo_memory_shard.py

Expected Output:

=== SCBE-AETHERMOORE Governance Demo ===

Agent: fraud-detector-001
Action: READ transaction_stream
Trust: 0.92
Decision: ✅ ALLOW

Agent: compromised-agent-666
Action: MODIFY detection_rules
Trust: 0.15
Decision: ❌ DENY (returned noise)

Agent: analyst-bot-042
Action: EXPORT customer_data
Trust: 0.78
Decision: ⏸️ QUARANTINE (human review required)

9. Contact & Next Steps

To Start a Pilot:

  1. Schedule architecture review call
  2. Define pilot scope and success criteria
  3. Sign pilot agreement
  4. Begin Week 1 discovery

Repository: https://github.com/ISDanDavis2/scbe-aethermoore-demo Patent: USPTO #63/961,403

Appendix: Technical Specifications

Cryptographic Primitives

  • Key Encapsulation: ML-KEM-768 (NIST PQC)
  • Digital Signatures: ML-DSA-65 (NIST PQC)
  • Symmetric: AES-256-GCM
  • Hash: SHA-3-256

Performance Targets

  • Decision latency: < 5ms (p99)
  • Throughput: 10,000+ decisions/second
  • Availability: 99.99% (with redundancy)

Deployment Options

  • Docker containers
  • Kubernetes (Helm charts)
  • AWS Lambda / Azure Functions
  • On-premise (air-gapped supported)

© 2026 Aethermoore - Issac Davis, Founder | Patent Pending (63/961,403) | Products | Demo

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