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

Раскрытие влияния искусственного интеллекта и машинного обучения на финансовые рынки: комплексный анализ применения ИИ в торговле, управлении рисками и финансовой деятельности
Mohammad El Hajj, Jamil Hammoud
2023-10-05

algorithmic tradingcredit scoringfraud detectionregulatory compliancerisk management
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.
1
AI and machine learning adoption is growing across financial institutions, with applications in algorithmic trading, risk management, fraud detection, credit scoring, and customer service.
2
AI and machine learning are transforming the financial workforce, creating a need for professionals to adapt their skills.
3
Effective adoption requires attention to regulation, ethical governance, and organizational strategies addressing implementation challenges.
4
Key barriers to adoption include data privacy concerns, regulatory compliance requirements, and ethical and social considerations.
5
The study uses a mixed-methods design combining a quantitative survey with qualitative analysis of prior research, reports, and articles to examine AI’s influence on finance.

Artificial intelligence and machine learning applications in financial markets and financial institutions

Adoption, impacts, applications, and challenges of AI and ML across trading, risk management, and financial operations

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Publication Date
2023-10-05
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Authors
Mohammad El Hajj
Jamil Hammoud
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