Abstract

The implementation of Machine Learning (ML) and Artificial Intelligence (AI) in the financial sector has led to a transformative shift in the industry which redefines traditional practices. These modern technologies have enabled financial institutions to make use of large amounts of data for accurate predictive modeling, personalized customer experiences, and automated decision-making processes. Among the dramatic changes we witnessed were the adoption of AI-driven robot advisors for personalized investment strategies, ML algorithms for real-time fraud detection, and AI-based credit scoring systems that improve lending accuracy. Naturally, advancements in sentiment analysis and risk measurement through natural language processing do enhance predictive market abilities. When these technologies progress, they promote increased efficiency, minimize costs, and provide more options in reaction to changes in financial markets. This study aims to point out the latest patterns being observed regarding ML and AI applications within finance.