Fidelis
Bank Credit Card EDA

Bank Credit Card EDA

Bank Credit Card Launch

Objective

Analyze customers' transactions and credit profiles to identify a target group for the launch of the Bank credit card.

🔗 View on GitHub

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

  1. Data Import & Inspection
    • Loaded dataset into Pandas DataFrame
    • Checked data types, column info, and basic statistics
  2. 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
  3. Exploratory Analysis
    • Distribution plots for key features
    • Correlation matrix to identify relationships between variables
    • Segment-wise spending and income analysis
  4. Customer Segmentation
    • Grouped customers based on income, age, and spending behavior
    • Identified potential target groups for credit card launch
  5. 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