Beta-Bank

Beta Bank's customers are leaving: little by little, slipping away every month. The bankers have discovered that it's cheaper to save existing customers than to attract new ones. We need to predict whether a customer will leave the bank soon. You have data on past customer behavior and contract terminations with the bank. Build a model with the maximum possible F1 value. To pass the review, you need an F1 value of at least 0.59 for the test data set. Also, measure the AUC-ROC metric and compare it with the F1 value.

Features

• RowNumber - data string index

• CustomerId - unique customer identifier

• Surname - last name

• CreditScore

• Geography - country of residence

• Gender

• Age

• Tenure - length of service for the customer

• Balance - account balance

• NumOfProducts - number of banking products used by the customer

• HasCrCard - client has a credit card (1 - yes; 0 - no)

• IsActiveMember - active customer (1 - yes; 0 - no)

• EstimatedSalary - estimated salary

Objective

• Exited - customer left (1 - yes; 0 - no)