Welcome to the Credit Card Customer Attrition Analysis repository!
In this project, I worked with a public dataset extracted from Kaggle.com, which can be found in the next link: https://www.kaggle.com/datasets/sakshigoyal7/credit-card-customers/data. The objective was to understand the characteristics of customers who were leaving the bank's services and to create a multiple regression model that predicts the probability of a customer leaving the bank based on certain significant variables. The dataset comprised over 10,000 observations and 21 variables.
The model had a 90% success rate and an AUC(Area under the ROC curve) of 93%.
-Data Cleaning and Exploratory Analysis: The data cleaning and exploratory analysis were conducted using BigQuery.
-Visualizations: Visualizations about the exploratory analysis were created using Tableau. If you want to get in touch with the main charasteristics of the database before seeing the model, it is recommended to see the 'exploratory analysis' file first.
-Multiple Regression Model Building: The multiple regression model was built using R Studio to analyze the relationship between various predictors and customer attrition.
-Presentation: The project findings were presented using Canva to create a visually appealing and informative presentation.
Questions and comments to enhance the project are welcome! Feel free to reach out with any suggestions or improvements.