Dataset: Loan Default Prediction Dataset

About this Dataset

Loan Default Prediction Dataset

Introduction

Financial loan services are leveraged by companies across many industries, from big banks to financial institutions to government loans. One of the primary objectives of companies with financial loan services is to decrease payment defaults and ensure that individuals are paying back their loans as expected. In order to do this efficiently and systematically, many companies employ machine learning to predict which individuals are at the highest risk of defaulting on their loans, so that proper interventions can be effectively deployed to the right audience.

Description

This dataset has been taken from Coursera's Loan Default Prediction Challenge and will provide you the opportunity to tackle one of the most industry-relevant machine learning problems with a unique dataset that will put your modeling skills to the test. The dataset contains 255,347 rows and 18 columns in total.

Features

Image credits: Image by vectorjuice on Freepik

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Tables

Loan Default

@kaggle.nikhil1e9_loan_default.loan_default

7.27 MB
255347 rows
18 columns


CREATE TABLE loan_default (
  "loanid" VARCHAR,
  "age" BIGINT,
  "income" BIGINT,
  "loanamount" BIGINT,
  "creditscore" BIGINT,
  "monthsemployed" BIGINT,
  "numcreditlines" BIGINT,
  "interestrate" DOUBLE,
  "loanterm" BIGINT,
  "dtiratio" DOUBLE,
  "education" VARCHAR,
  "employmenttype" VARCHAR,
  "maritalstatus" VARCHAR,
  "hasmortgage" VARCHAR,
  "hasdependents" VARCHAR,
  "loanpurpose" VARCHAR,
  "hascosigner" VARCHAR,
  "default" BIGINT
);