This course dives into the integration of big data, artificial intelligence, and machine learning in modern finance. Starting with a high-level overview of AI and machine learning applications, learners are introduced to techniques for evaluating market efficiency in a high-dimensional world and understanding whether more data translates into better financial forecasts.
The course examines potential breakthroughs expected over the next 5–10 years and explores the complexity inherent in financial machine learning. Through interviews with experts from top institutions, participants gain insights into AI applications in household
finance, stock analysis, and firm-level risk assessments.
Practical case studies highlight the use of textual analysis of short-seller research reports, deep learning models to measure inflation exposure, and embedding approaches to assess the societal impact of finance. The course emphasizes the synergy between human expertise and machine intelligence, demonstrating how AI augments decision-making and forecasting in financial services. By the end, learners will have a comprehensive understanding of how AI, big data, and machine learning can drive innovation, efficiency, and insight in the financial sector.
