INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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.
"Loan Default Prediction Using Machine Learning Techniques", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 12, page no.b504-b510, December-2022, Available :http://www.ijnrd.org/papers/IJNRD2212156.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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