Economic implications of AI-driven financial markets: Challenges and opportunities in big data integration

Foluke Ekundayo *

Department of IT& Computer Science, University of Maryland Global Campus, USA.
 
Review
International Journal of Science and Research Archive, 2024, 13(02), 1500–1515.
Article DOI: 10.30574/ijsra.2024.13.2.2311
Publication history: 
Received on 17 October 2024; revised on 24 November 2024; accepted on 26 November 2024
 
Abstract: 
The integration of Artificial Intelligence [AI] and Big Data into financial markets has revolutionized their dynamics, offering unprecedented opportunities and posing complex challenges. This article examines the transformative impact of AI-driven financial systems on market operations, with a focus on algorithmic trading, market efficiency, and economic stability. AI-powered models enable rapid decision-making and data-driven strategies, enhancing liquidity and reducing transaction costs. However, these advancements also introduce volatility, systemic risks, and ethical concerns, necessitating a balanced approach to adoption. The discussion explores the regulatory challenges arising from the widespread use of AI in financial markets, including issues of transparency, accountability, and market fairness. The unpredictable behaviour of algorithmic trading systems and the potential for market manipulation present significant concerns for regulators. Moreover, the ability of AI to analyse vast datasets raises questions about data privacy and governance, demanding robust policy frameworks to mitigate risks. Amid these challenges, the article highlights opportunities for policymakers to leverage AI and Big Data for sustainable economic growth. Integrating advanced analytics into macroeconomic planning, regulatory oversight, and financial inclusion initiatives can drive innovation and stability. By fostering collaboration between regulators, financial institutions, and technology providers, governments can ensure that AI-driven financial markets align with broader economic goals. This article underscores the dual-edged nature of AI and Big Data in financial markets, emphasizing the need for strategic regulation and innovation to maximize benefits while minimizing risks. It offers actionable insights for stakeholders seeking to navigate the evolving financial ecosystem and harness the potential of AI for economic progress.
 
Keywords: 
AI in Financial Markets; Big Data Integration; Algorithmic Trading; Market Efficiency; Regulatory Challenges; Economic Growth
 
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