Name: E-Signing Of Loan-Based On Financial History
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

E-Signing Of Loan-Based On Financial History

Content:-
The file contains user details who are willing to complete esigning process

Details:-
Except all columns class column denotes following:-
Class 0 --> Does not completed esigning process
class 1 --> Completed e_signing process.

Goal:-
The main goal is to build various different algos & predict whether applicant completed e-signing process or not

Solving method:-
The given problem statement is comes under binary classification
We have to solve problem using different machine learning algorithm as well as deep learning algorithms

Tables

Financial Data

@kaggle.yashpaloswal_esigning_of_loanbased_on_financial_history.financial_data

1.23 MB
17,908 rows
21 columns

CREATE TABLE financial_data (
  "entry_id" BIGINT,
  "age" BIGINT,
  "pay_schedule" VARCHAR,
  "home_owner" BIGINT,
  "income" BIGINT,
  "months_employed" BIGINT,
  "years_employed" BIGINT,
  "current_address_year" BIGINT,
  "personal_account_m" BIGINT,
  "personal_account_y" BIGINT,
  "has_debt" BIGINT,
  "amount_requested" BIGINT,
  "risk_score" BIGINT,
  "risk_score_2" DOUBLE,
  "risk_score_3" DOUBLE,
  "risk_score_4" DOUBLE,
  "risk_score_5" DOUBLE,
  "ext_quality_score" DOUBLE,
  "ext_quality_score_2" DOUBLE,
  "inquiries_last_month" BIGINT,
  "e_signed" BIGINT
);