Unveiling the Influence of Artificial Intelligence and Machine Learning on Financial Markets: A Comprehensive Analysis of AI Applications in Trading, Risk Management, and Financial Operations
Study explores AI and ML's impact on financial markets, focusing on trading, risk management, and ethical considerations.
What it examines
This study explores the impact of AI and ML on financial markets, focusing on trading, risk management, and financial operations. It uses a mixed-methods approach, including a quantitative survey and qualitative analysis, to understand AI and ML adoption, challenges, and benefits in finance.
What it concludes
The research suggests AI and ML can significantly enhance financial market operations but require careful implementation. Potential applications include improved trading strategies and risk management. Future research should focus on ethical considerations and regulatory frameworks to ensure responsible AI and ML use.
Evidence objects
The research suggests AI and ML can significantly enhance financial market operations but require careful implementation. Potential applications include improved trading strategies and risk management. Future research should focus on ethical considerations and regulatory frameworks to ensure responsible AI and ML use.
key_findings bullet 1 · key_findings · validation V0
Raw abstract and provenance
This study explores the adoption and impact of artificial intelligence (AI) and machine learning (ML) in financial markets, utilizing a mixed-methods approach that includes a quantitative survey and a qualitative analysis of existing research papers, reports, and articles. The quantitative results demonstrate the growing adoption of AI and ML technologies in financial institutions and their most common applications, such as algorithmic trading, risk management, fraud detection, credit scoring, and customer service. Additionally, the qualitative analysis identifies key themes, including AI and ML adoption trends, challenges and barriers to adoption, the role of regulation, workforce transformation, and ethical and social considerations. The study highlights the need for financial professionals to adapt their skills and for organizations to address challenges, such as data privacy concerns, regulatory compliance, and ethical considerations. The research contributes to the knowledge on AI and ML in finance, helping policymakers, regulators, and professionals understand their benefits and challenges.
Source row: 2106 · abstract type: unknown