Machine Learning and Sustainable Finance
Overview
Machine Learning and Sustainable Finance is a five-day program that combines practical training and discussions centered on applying machine learning (ML) techniques to sustainable finance. This workshop integrates theoretical sessions in the mornings with hands-on problem-solving workshops, followed by afternoon panel discussions exploring challenges and opportunities for innovation in sustainable finance.
The goal of the Machine Learning and Sustainable Finance event is to provide a venue for discussing critical challenges and opportunities at the intersection of machine learning and financial innovation in driving the transition to a sustainable future. Achieving carbon neutrality by 2050 requires an unprecedented mobilization of resources and annual investments of approximately $3.5 trillion, highlighting the financial sector’s vital role as a catalyst for transformation.
Investors are increasingly expected to go beyond traditional financial metrics, incorporating environmental, social, and governance (ESG) criteria, key pillars of responsible investment and drivers of meaningful societal impact. However, significant challenges persist, such as limited access to reliable data, inconsistent ESG indicators, and the growing need for near-real-time metrics to address emerging challenges effectively, particularly in areas like climate change, biodiversity, societal impact, and cultural preservation.
This conference aims to explore how advancements in machine learning, natural language processing, and real-time analytics can equip the financial sector with innovative tools to objectively evaluate ESG performance, enhance decision-making, and accelerate the transition toward a more equitable and sustainable global economy.
Who Should Attend?
This program is ideal for professionals, academics, and researchers with a quantitative background interested in:
- Advancing their knowledge in machine learning, natural language processing, and reinforcement learning.
- Applying these techniques to specific use cases in finance.
- Participants should have a basic understanding of Python programming and foundational knowledge in mathematics, including linear algebra and statistics.
Learning Objectives
By the end of the workshop, participants will:
- Acquire a robust understanding of key ML techniques and their applications in sustainable finance.
- Learn to navigate the challenges of applying data science to ESG-focuse financial projects.
- Build connections with a network of professionals and researchers dedicated to sustainability initiatives.
Program Structure
The five-day program features:
- Morning Sessions: Theoretical lectures covering core concepts in machine learning and sustainable finance, supplemented with case studies.
- Afternoon Workshops: Practical problem-solving sessions and pane discussions addressing sustainable finance challenges in Montreal and Mexico.
- Supplementary Activities: Networking events and collaborative opportunities to discuss project ideas.
Key Dates
- Registration Deadline: February 14, 2025
- Notification of Acceptance: February 21, 2025
- Workshop Dates: March 3-7, 2025
Location
Guanajuato, Gto., Mexico
Organizing Committee
Manuel Morales - FinML, University of Montreal
Ivete Sánchez Bravo - CIMAT
This workshop offers a unique opportunity to bridge the gap between theory and practical applications of machine learning in the ESG finance domain. Join us to enhance your skills, collaborate with like-minded professionals, and contribute to innovative solutions for sustainability challenges.
Apply Now and secure your spot before the deadline.
