Thursday, August 22nd 2024

2:30 pm: Presentations
4:30 pm: Networking
6:00 pm to 10:00 pm: Méchoui

EXCLUSIVE DISCUSSION

Come and share insight and learning on the pressing issues and challenges arising from significant geopolitical trends and events alongside the rapid advancement of AI and other technologies. Let’s discuss resilience strategies that investment leaders can adopt in the face of systemic risks that could result from the convergence of several unexpected events.

October 23-24, 2024

Past event

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EVENT DETAILS

Hackathon

MECHOUI CONFRENCE 2024

FIAM

Our mission

FIAM is dedicated to establishing Montreal as a pivotal hub in the worldwide network of innovation, emphasizing the advancement and application of artificial intelligence and machine learning within the sphere of finance and the asset management sector. This initiative seeks to unite the contribution of academics, industry professionals, organizations, and government entities, fostering an ecosystem that will encourages collaboration toward this goal.

FIAM’s core mission pillar:

Cultivating Talent for a Data-Driven Era

More data, more information, more knowledge, more intelligence, and more efficient investment strategies.

This statement carried implication for both, the finance and investment community as well as the academic realm. Investors should be prepared to embrace data-driven approaches, consider the ethical and regulatory aspects of data usage, and adapt to the evolving landscape of data-related investment opportunities and risks. Simultaneously, academic institutions and universities must urgently adapt their education programs to prepare students to this data-driven future.
Here are some steps that forward thinking institutions have already incorporated in their curriculums.

Incorporate data analytics and data science courses into their finance and business programs.
Include courses on data ethics and compliance within their data curriculum.
Promote the development of programming and technical skills amongst finance students.
Introduce machine learning and artificial intelligence (AI) concepts in financial programs.
Encourage interdisciplinary collaboration between finance, computer science, and ethics departments.
Incorporate real-world projects and internships into the curriculum to provide students with hand-on experience in using data for financial analysis.
Collaborate with financial institutions and data analytics firms to establish industry partnerships.