Increasingly autonomous algorithmic agents in financial trading may involve significant risks to market integrity. This study explores how such algorithmic traders may independently exploit manipulative and collusive tactics. Using the proprietary trading industry as a case study, we explore new emerging threats to the application of established legal concepts of liability for algorithmic market abuse, taking an interdisciplinary stance between financial regulation, law & economics, and computational finance. We show how the ‘black box’ nature of specific artificial intelligence (AI) trading systems can subvert existing market abuse laws, which are based upon traditional liability concepts and tests such as ‘intent’ and ‘causation’. To address the shortcomings of the present legal framework, we develop a number of guiding principles for legal reform.
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Front Matter
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Part I: FOUNDATIONS OF AI AND AI GOVERNANCE
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Part II: OPPORTUNITIES AND REGULATORY CHALLENGES OF AI IN THE BANKING INDUSTRY
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Part III: OPPORTUNITIES AND REGULATORY CHALLENGES OF AI IN CAPITAL MARKETS
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Part IV: OPPORTUNITIES AND REGULATORY CHALLENGES OF AI IN THE INSURANCE INDUSTRY
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Part V: CROSS-SECTORAL ISSUES ON THE USE OF AI IN THE FINANCIAL SECTOR
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Back Matter
