Sponsored by Women at the Table
Phase-1 paper found here
Jupyter Notebook found here
Financial inclusion is paramount for economic stability and resilience, particularly in diverse regions like Sub-Saharan Africa, spanning low to high-income countries and encompassing both resource-intensive and non-resource-intensive economies. This study focuses on a crucial aspect of financial resilience: the accessibility of emergency funds, defined as having access to 1/20 of Gross National Income (GNI) per capita in local currency within 30 days. Leveraging previous colleagues' exploratory work on the Global Financial Inclusion Database 2021, our objective is to mitigate inherent gender biases in the dataset by rebalancing it with synthetic data, thereby enhancing fairness in predicting emergency fund accessibility. Through predictive machine learning modeling, we aim to contribute to the economic empowerment of individuals in Sub-Saharan Africa, ultimately fostering resilience and reducing disparities in access to essential financial resources.