Automation Audit: Trust Code, Verify Logs

Automation removes human error and hides new ones. Code that acts without oversight can drift from intent or fail silently.

Routine audits—log reviews, reconciliation, and policy checks—ensure automation behaves as designed.

Why it matters

Automated systems amplify mistakes at machine speed. Audits provide a feedback loop that catches divergences before they become losses or compliance breaches.

Common mistakes

• Assuming logs are fine because no errors surface.
• Keeping audit steps manual and sporadic.
• Failing to compare executions against policy expectations.

Implementation steps

Centralize logs

Archive, index, and checksum execution logs daily.

Automate reconciliation

Cross-check orders, fills, and risk events against policies.

Escalate anomalies

Route discrepancies to humans with context for rapid resolution.

LiquidityAI tie-in

• Immutable log storage with search and retention policies.
• Policy engine cross-checks executions automatically.
• Alerting framework assigns follow-ups to operators.

Case sketch (composite)

An unattended script mispriced orders for weeks. A LiquidityAI audit job caught the discrepancy, saving thousands and prompting tighter review cycles.

Takeaways

• Automation needs monitoring like any operator.
• Automated audits scale vigilance.
• Documented reviews satisfy regulators and investors.

LiquidityAI provides tools and education for systematic trading. This article is for informational purposes only and does not constitute investment advice. Trading involves risk, including possible loss of principal.