A Multi-Stakeholder Recommender System for Rewards Recommendations

Anna Leontjeva

Abstract:

Australia’s largest bank, Commonwealth Bank (CBA) has a large
data and analytics function that focuses on building a brighter
future for all using data and decision science. In this work, we focus
on creating better services for CBA customers by developing a
next generation recommender system that brings the most relevant
merchant reward offers that can help customers save money. Our
recommender provides CBA cardholders with cashback offers from
merchants, who have different objectives when they create offers.
This work describes a multi-stakeholder, multi-objective problem
in the context of CommBank Rewards (CBR) and describes how
we developed a system that balances the objectives of the bank, its
customers, and the many objectives from merchants into a single
recommender system.