Transforming Financial Management With Ai: Opportunities, Challenges, And Regulatory Implications

Abstract

The study paper delves into the transformative impact of Artificial Intelligence (AI) on financial management, highlighting the significant opportunities, challenges, and regulatory implications involved. AI technologies like machine learning, natural language processing, and robotic process automation are transforming financial sectors by enhancing decision-making, operational efficiency, and customer personalization. The study employs a mixed-methods approach, integrating or connecting quantitative data from surveys with qualitative insights from semi-structured interviews with financial industry stakeholders. The results indicate a positive correlation between AI adoption and operational efficiency, with AI-driven automation and advanced analytics leading to improved profitability and customer satisfaction. However, challenges such as data privacy, algorithmic bias, and the opacity of AI systems pose significant hurdles. Regulatory concerns focus on ensuring transparency, fairness, and data protection in AI applications, with a call for updated governance models to keep pace with technological advancements. The paper emphasizes the need for ongoing research into AI's long-term effects on the financial industry, advocating for robust AI governance frameworks and a deeper exploration of AI’s impact on market dynamics and employment within the sector. This comprehensive analysis aims to provide a balanced perspective on the potential and limitations of AI in financial management.