Loan Distribution System Using Machine Learning
Karnati Sai Prashanth, Tsaliki Satya Ganesh Kumar, Garapati Venkata Krishna Rayalu, Svs Dhanush, Chandu Janakiram
INTRODUCTION
1. Loan-Prediction - This is the method a machine learning algorithm uses to determine whether or not a person will be approved for a loan.
2. The first and most important step is to comprehend the problem description. This would enable you to anticipate your challenges in advance. View the problem statement first.
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 issue where we must determine whether or not a loan will be granted. We must forecast discrete values in a classification problem using the set of available independent variables. Two different classifications are possible:
5. Binary Classification: In this classification, we must choose between the two classes that are provided. For instance, identifying a person's gender as male or female, forecasting a win or loss, etc. Multiclass Classification: In this case, the data must be divided into at least three classes. For instance, you may categorise a film's genre as comedy, action, or romantic, or you could categorise fruits as oranges, apples, or pears.
6. Each retail bank encounters the very common challenge of loan projection at least once during its existence. At the conclusion of a retail bank, it can save a lot of man hours if done correctly.
