Paper Title
Loan Default Prediction Using Machine Learning Techniques
Article Identifiers
Authors
Shaistha Tabassum , Dr. Shylaja K R
Keywords
Loan Prediction, KNN, Naïve Bayes, Logistic Regression.
Abstract
Technology has made a lot of improvements, and the banking industry is no exception. Every day, there are more applications to approve loans. While evaluating an application for getting approved, they must take into consideration a few bank policies. The bank is required to determine what is ideal for approval based on a few criteria. To meticulously check out each individual prior recommending them for loan approval is challenging and risky. Based on the cibil score and history of the individual to whom the loan amount was previously accredited, we utilise machine learning in this study to identify who may be trusted for a loan. The main goal of this approach is to forecast whether or not the loan will be sanctioned.
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How To Cite (APA)
Shaistha Tabassum & Dr. Shylaja K R (December-2022). Loan Default Prediction Using Machine Learning Techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(12), b504-b510. https://ijnrd.org/papers/IJNRD2212156.pdf
Issue
Volume 7 Issue 12, December-2022
Pages : b504-b510
Other Publication Details
Paper Reg. ID: IJNRD_184943
Published Paper Id: IJNRD2212156
Downloads: 000121976
Research Area: Engineering
Country: Bangalore , Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2212156.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2212156
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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