XAI for greener portfolio decisions
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XAI for greener portfolio decisions
This course explores how Explainable Artificial Intelligence (XAI) can enhance transparency, trust, and performance in sustainable finance and ESG investing. It addresses the challenges of using “black-box” AI models in financial decision-making and introduces XAI techniques that make AI-driven portfolio choices interpretable and accountable.
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General Overview
Description
This course explores how Explainable Artificial Intelligence (XAI) can enhance transparency, trust, and performance in sustainable finance and ESG investing. It addresses the challenges of using “black-box” AI models in financial decision-making and introduces XAI techniques that make AI-driven portfolio choices interpretable and accountable.
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Meet the instructors !
Megang is a doctoral candidate in the MSCA Digital Doctoral Network, specializing in agent-based modeling applications for sustainable finance analysis. They hold a BSc in Mathematics and dual master's degrees in Financial Mathematics and Data Science for Business. Their current research focuses on developing computational models to understand complex interactions within sustainable financial systems, bridging quantitative finance with environmental and social impact considerations.
Megang brings a unique interdisciplinary perspective to their work, combining mathematical rigor with practical business applications and cutting-edge data science methodologies. Their research contributes to the growing field of sustainable finance by providing novel analytical frameworks for understanding market dynamics and stakeholder behaviour in environmentally and socially responsible investment contexts.