Analysis of Loan Eligibility for a Prospective Retail Borrower

Authors

  • Sanjay Basu  Department of Artificial Intelligence and Machine Learning, New Horizon College of Engineering, Bengaluru, India
  • Divyesh Jaiswal  Department of Artificial Intelligence and Machine Learning, New Horizon College of Engineering, Bengaluru, India
  • Sai Danoosh  Department of Artificial Intelligence and Machine Learning, New Horizon College of Engineering, Bengaluru, India
  • Dr. Prianka RR  Sr Asst.Professor, New Horizon College of Engineering Bengaluru, India

DOI:

https://doi.org//10.32628/IJSRST229693

Keywords:

Loan-prediction, Prospective borrower, Financial Literacy, Logistic regression, Python Flask

Abstract

This project aims to offer an individual a general estimate or idea as to the viability of home loan repayment for the loan amount incurred. This is achieved by taking into consideration the individuals qualitative and quantitative parameters. As a thumb rule, one's insurance pay out shouldn't exceed more than thirty-five percent of their income. An individual's probable EMI amount can amount to fifty percent of one's salary as per the general bank standard.

References

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  4. A. Goyal and R. Kaur, “Accuracy Prediction for Loan Risk Using Machine Learning Models”.
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  6. https://machinelearningmastery.com/types-of-classification-in-machine-learning/ computer applications
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Published

2022-12-30

Issue

Section

Research Articles

How to Cite

[1]
Sanjay Basu, Divyesh Jaiswal, Sai Danoosh, Dr. Prianka RR, " Analysis of Loan Eligibility for a Prospective Retail Borrower, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 6, pp.625-629, November-December-2022. Available at doi : https://doi.org/10.32628/IJSRST229693