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 statistical machine learning methods to find the members with high-level leaving risk from the existing members of Servus, and then using even more advanced methods to analyze the influence of targeted offers on member retention and attrition. In the end, a final operationalized model on increasing member retention and reducing member attrition will be built up and can be used by business intelligence team for ongoing campaigns in Servus.

Faculty Supervisor:

Linglong Kong


Xi Hu


Servus Credit Union Ltd




Information and communications technologies




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