Access to banking services is a crucial aspect of financial inclusion, enabling individuals to save, invest, and manage their finances more effectively. However, in many regions, including Africa, a significant portion of the population remains unbanked. The lack of access to banking services can hinder economic growth and development, perpetuating cycles of poverty and inequality.

Therefore, there is a pressing need to identify factors that contribute to financial exclusion and develop strategies to promote greater access to banking services among underserved populations. 

• Develop a machine learning model to predict which individuals are most likely to have or use a bank account in African countries.

• Explore key socio-economic factors that contribute to financial inclusion, such as education level, job type, and access to mobile phones.

• Provide actionable insights to policymakers, organizations, and stakeholders to facilitate targeted interventions aimed at promoting financial inclusion.

• Evaluate the effectiveness of the machine learning model in predicting financial inclusion and its potential impact on policy planning and resource allocation.