Akosua9/PAYSWIFT-GHANA-BUSINESS-ANALYSIS

# Pay Swift Ghana – Financial Insights Dashboard ## Overview This Power BI dashboard presents a comprehensive view of user behavior, loan distribution, and feature utilization for **Pay Swift Ghana**, a digital financial service platform. It is designed to help stakeholders understand key financial and customer engagement metrics. --- ## Business Challenge 1. **Low adoption rates for new features** 2. **High loan default rates** 3. **Customer churn** --- ## Key Business Questions - **What customer behavior patterns** can be observed in feature usage, transaction frequency, and loan repayments? - **What trends and drivers** are associated with customer churn? Why are users leaving the platform? - **Which user segments** (age group, usage level, repayment history) are at higher risk of **loan defaults**? --- ## Data Cleaning & Preparation - Removed duplicate entries and irrelevant fields - Handled missing values through imputation and exclusion - Standardized date formats and calculated derived columns (e.g., monthly transactions per user) - Created new categorical fields such as age groups and churn indicators --- ## Tools & Techniques Used - **Power BI** – For data modeling, dashboard design, and visualization - **Power Query Editor** – For data cleaning and transformation - **DAX (Data Analysis Expressions)** – For custom calculations and KPIs - **Filters & Slicers** – For dynamic data exploration (churn, repayment status, etc.) - **Data Visualization Best Practices** – To ensure clarity, accessibility, and usability --- ## Key Insights - **Feature Engagement:** Only 3 features—**Investment Advice**, **Budgeting Tools**, and **Savings Tracker**—show high user engagement. - **Behavioral Correlation:** Users who borrow higher loan amounts tend to have more monthly transactions, indicating a positive link between borrowing behavior and overall financial activity. - **User Segment Trends:** **Mid-aged users (36–45)** account for the highest l …