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πŸ“Š Data Analytics: Identifying Actionable Insights to Improve Financial Inclusion in Kenya

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DataKind: Financial Inclusion & Economic Opportunity in Kenya πŸ‡°πŸ‡ͺ

Libraries: matplotlib, seaborn, geopandas, pandas, numpy
Dataset: 2024 FinAccess Household Survey

What are the key factors driving financial inclusion in Kenya today? To find out, I analysed data from 20,871 interviews from the 2024 FinAccess Household Survey.

πŸ”Ž Key Insights:

  • 🏦 Financial exclusion remains widespread in Kenya
  • Bank account ownership rates vary dramatically, from 92.5% in Nairobi to just 44.1% in West Pokot
  • Youth are especially underserved: only 16.7% of 15–19 year olds have a bank account

A pathway to Inclusion:

  • πŸ“ˆ There is a strong correlation between mobile phone ownership and access to financial services
  • ⚑ A high-impact, scalable strategy: expand mobile access especially in rural areas and among young people

πŸ“– Jupyter Notebook: GitHub | Kaggle | DataBricks


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