Algorithmic Symmetry in Securities Markets: Toward a Legal Duty to Manage Common-Reliance Risk in AI Models

Abstract

This study examines whether securities regulation should move beyond firm-level artificial-intelligence governance and recognise a legal duty to manage common-reliance risk. The study defines algorithmic symmetry as material reliance by multiple market participants on the same or materially similar artificial-intelligence (AI) models, training data, vendors, cloud infrastructure, benchmarks, optimisation constraints, or model updates, such that their investment or trading decisions can move in the same direction. The legal problem is not a defective recommendation at one institution. It is the market-level externality that may arise when individually lawful and technically sound systems generate correlated selling, liquidity withdrawal, valuation changes, or risk-limit actions during stress. The result can be disorderly price formation without an agreement to manipulate the market and without a demonstrable technical defect in any one model. Using doctrinal, comparative, and policy-oriented legal research, the paper analyses binding securities, operational-resilience, market-abuse, and AI rules alongside authoritative reports from the Financial Stability Board (FSB), International Organization of Securities Commissions (IOSCO), International Monetary Fund (IMF), Bank for International Settlements (BIS), and leading market regulators. The evidence establishes that common models, common data, provider concentration, rapid automation, and information gaps are recognised potential vulnerabilities. It does not establish that modern AI has already caused a securities-market crash, nor does it show that existing law creates a universal duty to diversify models or measure cross-firm output correlation. Existing regimes regulate individual governance, outsourcing, order controls, resilience, and manipulation. They do not generally create system-wide observability of correlated reliance. The paper proposes a proportionate, non-strict-liability administrative duty. Covered firms should identify, assess, monitor, confidentially report, and mitigate material common-reliance risk; regulators should aggregate dependency information and lead collective stress tests. The proposed regime includes tiered applicability, a confidential model-reliance register, correlation and concentration screens, shared-update and liquidity stress scenarios, human intervention and fallback arrangements, targeted duties for critical providers, graduated sanctions, and a narrow compliance safe harbour. The duty should treat commonality as a reason for assessment rather than a per se violation. It should preserve market-abuse requirements, protect trade secrets, and avoid a universal diversification mandate. The paper concludes that this design offers a legally cleaner and more innovation-sensitive response than stretching fiduciary, market-abuse, or operational-resilience doctrines beyond their existing predicates.