Predicting Bank Customer Churn
Problem Statement
Which factors are causing the customer to close their bank account?
Dataset
Data Source
The dataset is downloaded from Kaggle.
Thanks :slightly_smiling_face: to the Data Science community out there.
Data Dictionary
| Column | Description |
|---|---|
| RowNumber | Row Numbers from 1 to 10000 |
| CustomerId | Unique Ids for bank customer identification |
| Surname | Customer's last name |
| CreditScore | Credit score of the customer |
| Gender | Male or Female |
| Age | Age of the customer |
| Tenure | Number of years for which the customer has been with the bank |
| Balance | Bank balance of the customer |
| NumOfProducts | Number of bank products the customer is utilising |
| HasCrCard | Binary Flag for whether the customer holds a credit card with the bank or not |
| IsActiveMember | Binary Flag for whether the customer is an active member with the bank or not |
| EstimatedSalary | Estimated salary of the customer in Dollars |
| Exited | Binary flag 1 if the customer closed account with bank and 0 if the customer is retained |
Defining variable type
| Column | Type |
|---|---|
| CreditScore | Discrete |
| Gender | Nominal |
| Age | Discrete |
| Tenure | Discrete |
| Balance | Continuous |
| NumOfProducts | Discrete |
| HasCrCard | Nominal |
| IsActiveMember | Nominal |
| EstimatedSalary | Continuous |
Notebooks
- EDA of the dataset *WIP