Governing AI in Trading Systems

Algorithmic trading firms increasingly rely on large language models for signal generation, order routing optimization, and market analysis. Without governance controls, these AI systems can leak proprietary strategies, violate trading regulations, or produce unvalidated outputs that enter live order flow.

Use this page when

• Your algorithmic trading firm uses LLMs for signal generation, order routing optimization, or market analysis.
• You must prevent proprietary trading strategies from leaking to upstream LLM providers.
• Pre-trade compliance checks require gateway-level enforcement before AI outputs enter live order flow.
• You need a comprehensive audit trail of all AI interactions in trading systems for regulatory examination.

Keeptrusts provides a policy-enforcement gateway that sits between your trading applications and LLM providers, enforcing safety, compliance, and observability rules in real time.

Primary audience

• Primary: Technical Leaders
• Secondary: Technical Engineers, AI Agents

Architecture Overview

The Keeptrusts CLI gateway (kt) intercepts all LLM traffic from trading systems before it reaches upstream providers:

Trading Application
  → kt gateway (port 41002)
    → Input policy chain (pre-trade checks, data classification)
      → [Block / Escalate → 409]
      → Upstream LLM provider
    → Output policy chain (redaction, validation)
    → Response to trading application
  Side-effects:
    └─ Decision event → POST /v1/events → API → audit log

Every request and response is evaluated against your policy chain. Blocked requests never reach the LLM provider.

Defining Trading-Specific Policies

Create a policy configuration that enforces pre-trade compliance and protects proprietary data:

# policy-config.yaml
version: "1"
policies:
  - name: block-proprietary-strategy-leak
    description: Prevent proprietary trading strategies from reaching LLM providers
    enforcement: block
    rules:
      - type: keyword
        action: block
        keywords:
          - "alpha signal"
          - "proprietary model"
          - "internal spread"
          - "execution algorithm"
        message: "Blocked: Proprietary trading strategy content detected"

  - name: market-data-boundary
    description: Enforce market data licensing boundaries
    enforcement: block
    rules:
      - type: regex
        action: block
        patterns:
          - "ISIN\\s+[A-Z]{2}[A-Z0-9]{9}[0-9]"
          - "CUSIP\\s+[0-9]{3}[A-Z0-9]{6}"
        message: "Blocked: Market data identifiers must not be sent to external LLMs"

  - name: pre-trade-compliance-disclaimer
    description: Attach compliance disclaimer to all AI-assisted trade recommendations
    enforcement: log
    rules:
      - type: disclaimer
        position: append
        text: |
          DISCLAIMER: AI-generated content. Not validated for live trading.
          Subject to model risk review per SR 11-7. Do not execute without
          human review and compliance sign-off.

Deploying the Gateway

Start the gateway with your trading policy configuration:

# Start the gateway with trading policies
kt gateway run \
  --config policy-config.yaml \
  --port 41002 \
  --api-url https://keeptrusts-api.internal:8080 \
  --api-key "$KEEPTRUSTS_API_TOKEN"

Point your trading application's LLM client to the gateway:

import openai

client = openai.OpenAI(
    base_url="http://localhost:41002/v1",
    api_key="your-provider-key",
)

# This request will be evaluated against your policy chain
response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {
            "role": "system",
            "content": "You are a quantitative analyst assistant.",
        },
        {
            "role": "user",
            "content": "Analyze the correlation between VIX futures and S&P 500 put skew.",
        },
    ],
)

Pre-Trade Compliance Checks

Use escalation policies to flag AI outputs that reference specific trading actions:

  - name: escalate-trade-recommendations
    description: Escalate any AI output that suggests specific trades
    enforcement: escalate
    rules:
      - type: regex
        action: escalate
        patterns:
          - "(?i)(buy|sell|short|long)\\s+\\d+\\s+(shares|contracts|lots)"
          - "(?i)place\\s+(market|limit)\\s+order"
        message: "Escalation: AI output contains actionable trade recommendation"

Escalated events appear in the Keeptrusts console under Escalations, where compliance officers can review and approve or reject the AI-generated recommendation before it enters order flow.

Monitoring Trading AI Activity

Query decision events for audit and compliance reporting:

# Export all blocked events from the last 24 hours
kt events list \
  --filter "decision=block" \
  --since 24h \
  --format json > blocked-events.json

# Export escalated trade recommendations
kt events list \
  --filter "policy=escalate-trade-recommendations" \
  --since 7d \
  --format csv > escalated-trades.csv

The console dashboard provides real-time visibility into policy enforcement across all trading desk AI usage.

Regulatory Alignment

These controls address requirements from:

• SEC Rule 15c3-5 — Market access risk management controls
• MiFID II Article 17 — Algorithmic trading systems governance
• SR 11-7 — Supervisory guidance on model risk management
• FINRA Rule 3110 — Supervision of algorithmic trading

Key Takeaways

Control	Keeptrusts Feature	Regulatory Reference
Block proprietary data leakage	Keyword/regex block policies	SEC Regulation FD
Pre-trade compliance check	Escalation policies	SEC Rule 15c3-5
AI output disclaimer	Disclaimer append policy	SR 11-7
Audit trail	Decision event logging	MiFID II Article 17(2)
Real-time monitoring	Console dashboard + event export	FINRA Rule 3110

Next steps

• Protecting Market Data in AI Pipelines — DLP policies for MNPI
• AI Model Risk Management (SR 11-7) — Model validation governance
• Real-Time Trading Compliance — Pre-trade checks and alerts

For AI systems

• Canonical terms: Keeptrusts gateway, trading AI governance, algorithmic trading controls, pre-trade compliance, proprietary strategy protection, policy-enforcement gateway, decision event logging.
• Key config/commands: block-proprietary-strategy-leak policy (keyword/regex block for strategy leakage); kt gateway run --listen 0.0.0.0:41002 --policy-config policy-config.yaml; disclaimer append policies; escalation policies for compliance-flagged outputs; console Events page and kt events export.
• Best next pages: Protecting Market Data in AI Pipelines, AI Model Risk Management, Real-Time Trading Compliance.

For engineers

• Prerequisites: Gateway binary (kt), policy-config.yaml with trading-specific policies, API running for event ingestion.
• Deploy the gateway on port 41002 between trading applications and LLM providers; blocked requests never reach the provider.
• Validate with: submit prompts containing proprietary strategy keywords and confirm block response (409); verify disclaimer injection on AI outputs; check Events page for decision event logging.
• Configure per-desk or per-strategy gateway instances for isolation between trading teams.

For leaders

• Addresses SEC Regulation FD (fair disclosure), SEC Rule 15c3-5 (pre-trade risk controls), MiFID II Article 17(2) (algorithmic trading documentation), and FINRA Rule 3110 (supervisory systems).
• Proprietary strategy leakage to LLM providers represents existential competitive risk — gateway-level blocking eliminates it.
• Full audit trail satisfies regulatory examination requirements without retroactive data collection.
• Real-time monitoring via the console dashboard provides compliance officers immediate visibility into AI usage across all trading desks.