AI-Powered Wealth Management: Transforming Financial Literacy, Personalized Investments, and Risk Assessment Through Robo-Advisors and Predictive Analytics for the Future of Finance
The review article examines the transformative role of Artificial Intelligence (AI) in wealth management, with a particular focus on robo-advisors and their integration with big data and algorithmic trading strategies. The growing global need for efficient, personalized, and data-driven financial advisory services is highlighted, as traditional methods struggle to meet the demands of modern investors. The objective of the review is to explore how AI technologies, including machine learning, predictive analytics, and automation, are reshaping portfolio management, risk assessment, and investment strategies. The review’s novelty lies in its comprehensive analysis of recent advancements in AI-driven wealth management, offering a synthesis of emerging trends and technologies. A qualitative methodology was employed, analyzing studies, conference papers, and articles from leading sources such as IEEE and IGI Global. The findings indicate that AI-powered robo-advisors significantly enhance financial literacy, improve decision-making efficiency, and deliver personalized investment strategies. AI's capacity to process large datasets and predict market movements has been proven to optimize investment portfolios and mitigate risks. However, challenges such as data privacy, algorithm transparency, and regulatory concerns remain. The discussion underscores the need for more transparent AI systems and the integration of blockchain for greater security and trust. The conclusion suggests that AI in wealth management has the potential to revolutionize personal finance, but its widespread adoption requires overcoming key technical and ethical barriers. The review highlights the implications for financial institutions, investors, and policymakers, while identifying limitations in the research, particularly the need for more empirical data and long-term studies. Future research should focus on refining AI models, addressing transparency issues, and exploring the intersection of AI and blockchain in wealth management.