Interactive Power BI dashboard analyzing Ghana's banking sector performance, including loans, deposits, assets, liabilities, equity, and non-performing loan (NPL) indicators from 2021–2024.
Ghana Banking Sector Analysis
An interactive Power BI dashboard analyzing key financial indicators and performance trends across 15 banks in Ghana from 2021 to 2024.
Table of Contents
OVERVIEW
DATA SOURCE
TOOLS
DATA PROCESSING
SKILLS DEMONSTRATED
OBJECTIVES/PROBLEM STATEMENT
DATA ANALYSIS AND VISUALIZATION
INSIGHTS
RECOMMENDATIONS
OVERVIEW
The Ghana Banking Sector Dashboard is an interactive Power BI project developed to analyze the financial position, lending activity, funding structure, and credit-risk indicators of banks in Ghana between 2021 and 2024.
The dataset contains annual observations for 15 banks and includes indicators such as Total Assets, Total Loans, Deposits, Total Liabilities, Total Equity, Current Assets, Current Liabilities, and Non-Performing Loans (NPL).
The dashboard converts these financial records into interactive visualizations that allow users to compare banks and examine sector-level trends over time.
Overall KPIs from the dataset
Indicator
2021–2024 Total
Total Assets
GH₵526.28bn
Total Loans
GH₵355.98bn
Total Deposits
GH₵270.74bn
Total Liabilities
GH₵711.10bn
Total Equity
GH₵329.37bn
Total NPL
GH₵72.57bn
Aggregate NPL Ratio*
20.39%
DATA SOURCE
The dataset contains annual financial information for 15 banks covering 2021–2024.
The banking variables were compiled from annual reports of the various banks used for banking-sector analysis.
Banks represented in the dataset
GCB
Societe General Ghana
Stanbic Bank Ghana
Zenith Bank Ghana
Access Bank Ghana
Fidelity Bank Ghana
Bank of Africa
Ecobank Ghana
Consolidated Bank
Republic Bank Ghana
Cal Bank
First Atlantic Bank
Prudential Bank Ghana
Absa Bank Ghana
First National Bank
TOOLS
Microsoft Power BI – Dashboard development and interactive visualization
Power Query – Data cleaning and transformation
DAX – Measures and KPI calculations
Microsoft Excel – Data storage, preparation, and validation
DATA PROCESSING
The raw Excel dataset …