Dataset: Bank Loan Defualter

About this Dataset

Bank Loan Defualter

Context

In this dataset there are detail about users and in the target column it says whether the user will be a defaulter or not

Content

There are different columns like credit score, age, surname, tenure and other parameters which will help to predict whether a user will be a defaulter or not

Inspiration

This will help us to understand how all parameter contributes to being a defaulter or not. It will help banks to be more efficient.

Tables

Loan Defualter

@kaggle.vatsalkgandhi_churn_modelling.loan_defualter

329.07 KB
10000 rows
14 columns


CREATE TABLE loan_defualter (
  "rownumber" BIGINT,
  "customerid" BIGINT,
  "surname" VARCHAR,
  "creditscore" BIGINT,
  "geography" VARCHAR,
  "gender" VARCHAR,
  "age" BIGINT,
  "tenure" BIGINT,
  "balance" DOUBLE,
  "numofproducts" BIGINT,
  "hascrcard" BIGINT,
  "isactivemember" BIGINT,
  "estimatedsalary" DOUBLE,
  "exited" BIGINT
);