Financial inclusion remains one of the main obstacles to economic and human development in Africa. For example, across Kenya, Rwanda, Tanzania, and Uganda only 9.1 million adults (or 14% of adults) have access to or use a commercial bank account.
Traditionally, access to bank accounts has been regarded as an indicator of financial inclusion. Despite the proliferation of mobile money in Africa, and the growth of innovative fintech solutions, banks still play a pivotal role in facilitating access to financial services. Access to bank accounts enable households to save and make payments while also helping businesses build up their credit-worthiness and improve their access to loans, insurance, and related services. Therefore, access to bank accounts is an essential contributor to long-term economic growth.
The objective of this competition is to create a machine learning model to predict which individuals are most likely to have or use a bank account. The models and solutions developed can provide an indication of the state of financial inclusion in Kenya, Rwanda, Tanzania and Uganda, while providing insights into some of the key factors driving individuals’ financial security.
If you are new to machine learning and data science or new to Zindi, we recommend that this is the first competition you try. For guidance on how to get started, please see this tutorial: How to enter your first Zindi competition.