PREDICTION OF MODERNIZED LOAN APPROVAL SYSTEM BASED ON MACHINE LEARNING APPROACH

Abstract

With the enhancement in the banking sector lots of people are applying for bank loans
but the bank has its limited assets which it has to grant to limited people only, so finding out
to whom the loan can be granted which will be a safer option for the bank is a typical process.
So in this paper we try to reduce this risk factor behind selecting the safe person so as to save
lots of bank efforts and assets. This is done by mining the Big Data of the previous records of
the people to whom the loan was granted before and on the basis of these records/experiences
the machine was trained using the machine learning model which give the most accurate
result. The main objective of this paper is to predict whether assigning the loan to particular
person will be safe or not. This paper is divided into four sections (i)Data Collection (ii)
Comparison of machine learning models on collected data (iii) Training of system on most
promising model (iv) Testing.