Bolajoko34/ghana-financial-inclusion-2017-2024

Financial inclusion analysis using Excel, SQL, Power BI, Python & data from BoG, GSS, and World Bank # Ghana_Financial_Inclusion(2017-2024) # Project Overview This project analyzes the evolution of financial inclusion in Ghana between 2017 and 2024. The analysis integrates mobile money usage data, money supply and deposit data, and regional demographic indicators to evaluate access, usage patterns, deposit stability, and borrowing growth. # Project Objective The analysis aimed to: * Examine how financial inclusion evolved in Ghana from 2017 to 2024. * Analyze deposit trends and mobile money usage patterns. * Explore the relationship between interest rates, deposit behavior, and mobile money adoption. * Identify financially underserved regions and explain structural gaps. * Develop data driven recommendations to improve banking access and increase deposit mobilization. # Data Source * Global Findex Database (Mobile money) dataset: Captured ownership and usage rates across regions. * Monthly Monetary Survey(Money supply) dataset: Tracked deposit levels, liquidity patterns, and circulation of funds. * Regional and demographic dataset, (Interest dataset): Linked inclusion indicators to specific regions and demographic groups. Total population of 39M was derived by summing age brackets from this table to serve as the population base. Methodology * Population Base Definition Established a consistent base representing of 39M individuals across the specified age categories using the demographic dataset. * Transaction Segmentation Classified individuals into digital transaction categories to measure depth of financial engagement. * Deposit Structure Analysis Measured composition of demand, savings and time, and foreign currency deposits to assess system stability. * Trend Evaluation Examined deposit trends from 2017 to 2023 and borrowing patterns from selected years between 2017 and 2024. * Regional Assessment Compared mobile money usage and inclusion indicators across regions to identify underserved areas. # Excel * Fix messy multi row headers and renamed …