Abstract: A lot of individuals are applying for bank loans but the bank has its limited assets which it's to grant to limited people only, so checking out to whom the loan is granted could be able to be a safer option for the bank is a typical process. So here we attempt to reduce this risk factor behind selecting the safe person so as to save many bank efforts and assets. This is done by mining the large Data of the previous records of the people to whom the loan was granted before and on the premise of these records/experiences the machine was trained using the machine learning model which gives the foremost accurate result. The foremost objective of this paper is to predict whether assigning the loan to a particular person is safe or not. This paper is split 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.
Keywords: Loan, Prediction, Safe Person, Machine Learning.
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DOI:
10.17148/IJARCCE.2022.11227
