What is Algorithmic Trading Governance?
Algorithmic trading governance is the set of policies, controls, and oversight processes used to manage automated trading systems across their lifecycle. It is significant because regulators expect firms to control market, operational, and model risks arising from automated order generation and execution.
In Depth
In practice, algorithmic trading governance covers strategy approval, testing, deployment controls, monitoring, incident handling, and periodic review of trading algorithms and their parameters. It also includes clear accountability for who can change models, thresholds, connectivity, and order logic, as well as documentation showing how the firm prevents disorderly trading and manages conflicts between speed and control.
For compliance teams, the main issue is demonstrating that automated trading systems are not left to operate without effective supervision and safeguards. The concept is reflected in financial market rules and supervisory expectations, including MiFID II in the EU, FCA and PRA expectations in the UK, and similar market-conduct or prudential regimes that require firms to control algorithmic trading risk; it also aligns with broader governance expectations in ISO 27001, ISO/IEC 42001, and NIST AI RMF where AI-enabled trading is used.
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