harshalpanchal2000/Canada_Credit_Defaultors

Credit Card Default Predictor Dashboard Project

This project presents a predictive model for credit card defaults using a Tableau dashboard. It includes visualizations to analyze the likelihood of default based on various demographic and repayment attributes.

Table of Contents

• Overview
• Tableau Public Link
• Data Source
• Features
• Visualizations
• Usage
• Author
• License

Overview

The Credit Card Default Predictor Dashboard provides an analytical view of credit card holders and predicts the probability of default. The model aims to help financial institutions identify high-risk customers and make informed decisions.

Tableau Public Link

You can view the interactive dashboard on Tableau Public using the following link: Credit Card Default Predictor Dashboard

Data Source

The data for this project includes records of credit card holders with the following attributes:

• ID
• Age
• Gender
• Marital Status
• Education Level
• Repayment Status
• Default Probability

Features

• Prediction Accuracy: Indicates the accuracy of the model in predicting defaults (82% accurate).
• Model Prediction: Shows whether the model predicts a default or no default.
• Default Probability: Displays the probability of default for each credit card holder.

Visualizations

1. Credit Card Holder Info: Displays filtered information about credit card holders, such as age range, gender, marital status, education, and repayment status.
2. Default Probability: Bar charts showing the probability of default for each credit card holder in the filtered dataset.
3. Model Prediction: Highlights whether the model predicts a default or no default, along with the associated probability.

Usage

To use this dashboard effectively:

1. Filter Credit Card Holder Info: Use the filters to narrow down the dataset by age, gender, marital status, education, and repayment status.
2. Analyze Default Probability: Examine the bar charts to see the predicted probability of default for each credit card holder.
3. Model Prediction Insights: Check the model prediction section to understand if the model predicts a default or no default, along with the confidence probability.

Interactivity

• Filters: Adjust filters to refine the dataset based on specific criteria.
• Hover for Details: Hover over any data point for detailed information on default probability and demographic attributes.

Author

This project was created by Harshal Panchal as Machine Learning Project.

For any questions or further information, please contact:

• Email: [contact@itsmeharshal.com]
• LinkedIn: [https://www.linkedin.com/in/harshal-panchal/]

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

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Feel free to explore the dashboard and gain insights into the probability of credit card defaults to enhance your risk management strategies.