Artificial Intelligence Applications in Financial Markets and Corporate Finance: Technologies, Challenges, and Opportunities

Abstract

This study examines the transformative impact of artificial intelligence (AI) on financial markets and corporate finance, highlighting its role in enhancing analytical precision, operational efficiency, and strategic decision-making. It explores the historical evolution of AI integration, from early automation to advanced machine learning and deep learning applications, emphasizing their contributions to market analysis, risk management, and portfolio optimization. The paper discusses key AI techniques, including natural language processing, reinforcement learning, and generative models, and their deployment across trading, credit assessment, and corporate governance. Attention is given to data management challenges, ethical considerations such as bias mitigation and transparency, and regulatory compliance in AI-driven financial systems. The work also addresses organizational and cultural factors influencing AI adoption, as well as the societal implications related to financial inclusion and workforce transformation. Methodological approaches encompass quantitative modeling, qualitative insights, and bibliometric analyses, providing a comprehensive overview of AI’s integration within finance. Finally, the study identifies opportunities and challenges associated with AI implementation, underscoring the need for responsible governance and continuous innovation to realize sustainable benefits in the financial sector.

Keywords: Artificial Intelligence in Finance, Financial Technology (FinTech), Algorithmic Trading, Deep Learning, Explainable AI (XAI), Regulatory Technology (RegTech), AI-driven Risk Management, Generative AI, Corporate Finance, Ethical AI in Finance