Credit card defaulters

Brief Overview

📊 Completed a Power BI Desktop project focused on analyzing credit card defaulters. The project involved creating an interactive dashboard to visualize and analyze default patterns based on various demographics and financial metrics.

Problem Statement

🛠️ The project aimed to solve several key business challenges:

• Data Cleaning and Preprocessing: Using Power BI Query to clean and preprocess the data for accurate analysis.
• Visualizing Default Patterns: Creating visualizations to understand default rates by marital status, gender, education level, and age.
• Developing Key Performance Indicators (KPIs): Calculating KPIs such as default ratio, latest average bill amount, and latest average pay amount using DAX commands.
• Interactive Data Analysis: Implementing slicers based on education level for dynamic data analysis.

🔍 This project provided insights into credit card default trends, aiding in better risk management and decision-making.

Project Structure

The project on credit card defaulters included the following tasks:

1. Introduction
2. Overview of the Rhyme Interface
3. Importing the Data
4. Fixing the Column Names
5. Cleaning and Preprocessing Data: Using Power BI Query
6. Transforming the Data
7. Getting Started with Reports
8. Defaults by Marital Status and Gender
9. Defaults by Education Level and Sex
10. Defaults by Age and Gender
11. Creating KPIs: Default ratio, latest average bill amount, and latest average pay amount
12. Creating Slicers: Based on education level
13. Using DAX Commands: To create measures for KPIs

Key Achievements

📈 Successfully completed a comprehensive credit card defaulter analysis project using Power BI Desktop. 📊 Created various visualizations, including bar plots for defaults by marital status, gender, and education level, and area charts for defaults by age and gender. 📉 Developed key performance indicators (KPIs) using DAX commands to measure default ratio, latest average bill amount, and latest average pay amount. 🎛️ Implemented interactive slicers based on education level to enhance data exploration. 🛠️ Cleaned and preprocessed data using Power BI Query for accurate analysis. 🌟 This hands-on project provided practical experience in using Power BI for financial data analysis, equipping me with valuable skills for professional data analysis roles.

GitHub repository : Dashboard