Helping Servus Members Reach Financial Goals via Transfer Learning

In this self-contained project we will investigate how machine learning can be applied to help provide personalized financial advice. Machine learning is a term that designates types of artificial intelligence that rely on learning behaviors from data or experience. Specifically, the goal of this work is to apply machine learning to Servus Credit Union’s Noble […]

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Statistical Machine Learning Framework in Retention and Attrition Modelling

Customer or member retention refers to the ability of a company to retain its customers, and customer attrition, as the counterpart of customer retention, refers to the loss of customers. Developing a more accurate and comprehensible predictive model can help companies like Servus better understand member retention and attrition. This project is aiming at using […]

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Sentiment Analysis for the Assessment of Financial Fitness (SAFF)

We apply Artificial Intelligence (AI) on Sentiment Analysis for the Assessment of Financial Fitness (SAFF), which can help an individual to understand one’s latent feeling and reservation towards money saving, spending and planning. The SAFF framework can be applied to not only financial institutions, but also other sectors, e.g. healthcare, rehabilitation and education. Sentiment analysis […]

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