Grant: Engage Grants Program

The focus of this work is the prediction of future behaviour based on past history for financial transactional data. Much of the transactional data arises out of daily banking activities such as deposits, withdrawals, interest, loan, mortgages and various financial investments. Increasingly, financial institutions are seeking to provide enhanced consumer value as well as create competitive advantage by using transaction history as a foundation for predicting future client behaviour in terms of revenue, cost and margin. Thus, the aim of this Engage Grant is to develop a member-profile driven model for predicting future member behaviour, where the ultimate goal is the prediction of future product and service usage (i.e. customer behaviour) and associated revenue, cost and margin. The outcome of this grant will improve the Manitoban and Canadian economy by giving Canadian financial institutions an edge over their competition in other jurisdictions and create new job opportunities within the financial services sector for data science and business intelligence on predicting member/consumer behaviour.