Discovering novel approaches to robust machine learning and visualization for banking applications

The overall objective of this project is to develop approaches to improve rating robustness that are distributionally robust. We will develop techniques to utilize ensemble learning machine learning models with categorical monotonic constraints. Lastly, we will develop novel data visualization tools for business intelligence tasks that will help decision makers at Scotia Bank.

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Feature selection Impact on Models’ Performance

Data is rapidly growing in most of the applications and fields. Thus, data is becoming big data as it meets the 5V model of big data: volume, velocity, variety, veracity, and value. As a result, dimensionality reduction and feature selection become mandatory to overcome ML models’ performance and explainability issues. This project looks at feature […]

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Evaluation of Machine Learning Methods for Portfolio Replication of VIX Futures

During the past two decades, the CBOE Volatility Index (VIX® Index), a key measure of investor sentiment and 30-day future volatility expectations, has generated much investor attention because of its unique and powerful features. The introduction of VIX futures in 2004, VIX options in 2006, and other volatility-related trading instruments provided traders and investors access […]

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Mitigating goose herbivory at Westham Island tidal marsh.

Tidal marshes are essential ecosystems both economically and ecologically. They provide many natural resources, such as filtering pollutants from water and providing flood protection. However, since the 1980s, we have lost about 80% of the world’s wetlands including many tidal marshes. This internship aims to identify the role of goose herbivory on marsh vegetation as […]

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Fraud Detection in Derivatives Market using Deep Unsupervised Anomaly Detection and NLP

In the last few years, a high increase in the interest of traders and investors towards financial instruments directly led to an important augmentation of the information received daily by exchanges. Exchange regulators, who constantly monitor markets to unveil potential infractions, traditionally perform their investigation manually and the notable growth in market activity represents an […]

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Persuasive technology – Guidance to Virtual Relationship Manager (VRM) for effective sales effort basis voice data mining

Voice of the Customer (VoC) is how companies hear and listen to customer feedback about their brand, products, and services. Voice of the Customer solutions convert gathered feedback into valuable data and insights at scale. Data-driven VoC analytics programs are proven to increase customer lifecycle value and lower customer churn. Companies in various industries including […]

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La participation des dirigeants au capital-actions a-t-elle une influence sur la performance de I’entreprise et sur son prix en bourse?

Le projet de recherche qui se tiendra chez Montrusco Bolton Investments tentera de faire la lumiere sur l’influence que les achats et ventes d’actions poses par la direction ont sur Ie prix en bourse de leurs entreprises. Cela tout particulierement au niveau des transactions d’inities, c’est-a-dire lorsqu’une personne a l’interieur de l’entreprise achete ou vend […]

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Automatic Model Risk Management

Regulatory bodies, such as the Office of the Superintendent of Financial Institutions (OSFI) require that financial institutions properly assess and manage risk. Regulatory bodies aim to ensure the stability of financial markets, and the economy at large, and they do so by imposing guidelines on a firm’s risk management practices. Risk management models in general, […]

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Simulation-based decision support system for data analytics deployment

Data has been recognized as one of the most valuable assets of modern business. The capacity to gather, store, analyze and interpret data in great quantities can determine to a large degree the ability of a company to achieve goals and adapt to largely volatile environments. This is especially true for financial institutions where data […]

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Anonymisation et désensibilisation de données

L’enjeu de protection de la confidentialité des données personnelles sensibles et de leur utilisation par le secteur privé pose de plus en plus de défis. L’adoption par le gouvernement du Québec de la loi n°64, pour encadrer les dispositions législatives en matière de protection des renseignements personnels, remet la question au cœur des débats. Le […]

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Loss Given Default Estimation Methods

International Financial Reporting Standards (IFRS) for loss allowances are changing, and financial institutions are proactively adapting existing methodologies and developing new ones to remain compliant. The main ingredient in the myriad of evaluations that banks are required to perform for compliance is risk assessment. The first goal of this research project is to review best […]

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