You are allowed to use only the datasets that are provided here by Zindi and any features extracted from the contextual layers data accessed from the Africa GeoPortal described below.

Financial Inclusion Survey Data

The main dataset contains demographic information and what financial services are used by approximately 10,000 individuals across Tanzania. This data was extracted from the FSDT Finscope 2017 survey and prepared specifically for this challenge. More about the Finscope survey here.

The data have been split between training and test sets. The test set contains all information about each individual except for what types of financial services he or she uses.

Your goal is to accurately classify each individual into four mutually exclusive categories:

1. No_financial_services: Individuals who do not use mobile money, do not save, do not have credit, and do not have insurance
2. Other_only: Individuals who do not use mobile money, but do use at least one of the other financial services (savings, credit, insurance)
3. Mm_only: Individuals who use mobile money only
4. Mm_plus: Individuals who use mobile money and also use at least one of the other financial services (savings, credit, insurance)

Financial Access Map

This dataset is the geospatial mapping of all cash outlets in Tanzania in 2012. Cash outlets in this case included commercial banks, community banks, ATMs, microfinance institutions, mobile money agents, bus stations and post offices. This data was collected by FSDT. More about this dataset here.