Machine Learning Use Cases in Finance

Overview

The success of machine learning, especially deep learning in image recognition and natural language processing, has created high expectations, rapidly spreading to various areas, including the financial sector. Over the past six years, financial, banking, and insurance contexts have increasingly adopted these models.

Data science and advanced analytics teams in the financial and insurance sectors are regularly implementing these models, integrating them into their toolkits.

This course offers an in-depth review of machine learning and deep learning applications, illustrating their use in finance with concrete examples that have sparked industry interest. Examples include the ad hoc construction of architectures, adding value beyond merely replacing classical models with complex ones like multi-layer networks.

Key topics include:

• Neural network architectures on graphs to integrate new information dimensions in financial markets and Bitcoin transactions
• Portfolio design using reinforcement learning
• Natural Language Processing and information extraction methods from financial disclosures within the ESG and sustainable finance context

Developed by IVADO and Fin-ML, this course is part of an annual workshop held in Montreal since 2018.

Participants will benefit from concrete examples provided by six international experts from both Academia and Industry.

Designed for industry professionals and academics with intermediate knowledge in mathematics and programming (ideally Python), this course will also be beneficial for graduate students in data science and quantitative finance. Those not yet familiar with machine learning and deep learning will find the content particularly instructive and compelling.

Prior experience in the financial industry is not required.

The course is brought to you by:

• IVADO:

  A Québec-wide collaborative institute in the field of digital intelligence.

• Fin-ML:

  A nationwide network of researchers working at the intersection of data science, quantitative finance, and business analytics.

• Université de Montréal:

  One of the world’s leading research universities.

Taught by

Manuel Morales, Rheia Khalaf, Alexandre Nguyen, Frederik Wenkel, Elham Kheradmand and Marie-Ève Malette

Subjects

canada