Bank Credit Card Launch
Objective
Analyze customers' transactions and credit profiles to identify a target group for the launch of the Bank credit card.
Dataset
The dataset contains customer demographic details, credit history, and transaction patterns.
Key columns include:
Age
Annual Income
Spending Score
Credit Utilization
Number of Transactions
Default History
Steps in the EDA
- Data Import & Inspection
- Loaded dataset into Pandas DataFrame
- Checked data types, column info, and basic statistics
- Data Cleaning
- Detected anomalies such as:
- Minimum age of 1 year (invalid)
- Annual income of 0 (likely missing or incorrect data)
- Handled missing values and outliers
- Exploratory Analysis
- Distribution plots for key features
- Correlation matrix to identify relationships between variables
- Segment-wise spending and income analysis
- Customer Segmentation
- Grouped customers based on income, age, and spending behavior
- Identified potential target groups for credit card launch
- Key Insights
- Certain age-income segments show higher spending potential
- Outliers in credit utilization indicate risk factors
- Transaction frequency strongly correlates with spending score
Visualizations
- Histograms & KDE plots for demographic and financial variables
- Boxplots for income vs. spending
- Heatmap for correlation analysis
- Segmentation bar charts