Loan Distribution System using Supervised Machine Learning

Author Name : Kata Venkata Sai Krishna, Rahul Vemula, Harsha Rapuru, Abhirup Sahoo, Bhupinder Kaur, Alphy Benny, Chadalawada Amarnath

INTRODUCTION

1. Loan-Prediction – It is the process by which a machine learning algorithm can predict whether a person will get loan or not.

2. Understanding the problem statement is the first and foremost step. This would help you give an intuition of what you will face ahead of time. Let us see the problem statement.

3. Dream Housing Finance company deals in all home loans. They have presence across all urban, semi urban and rural areas. Customer first apply for home loan after that company validates the customer eligibility for loan. Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customer segments, those are eligible for loan amount so that they can specifically target these customers.

4. It is a classification problem where we have to predict whether a loan would be approved or not. In a classification problem, we have to predict discrete values based on a given set of independent variable(s). Classification can be of two types:

5. Binary Classification : In this classification we have to predict either of the two given classes. For example: classifying the gender as male or female, predicting the result as win or loss, etc. Multiclass Classification : Here we have to classify the data into three or more classes. For example: classifying a movie's genre as comedy, action or romantic, classify fruits as oranges, apples, or pears, etc.

6. Loan prediction is a very common real-life problem that each retail bank faces atleast once in its lifetime. If done correctly, it can save a lot of man hours at the end of a retail bank.