|
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter
Copyright Infringement Claims
Indexing Partner
|
Published Paper Details
|
|
| Paper Title: | Predicting the level of Income Qualification for Bank loan Approval |
| Authors Name: | B.Gnana Prasuna , M.Swathi Sree , K.srilatha |
| Unique Id: | IJSDR2307051 |
| Published In: | Volume 8 Issue 7, July-2023 |
| Abstract: | Every person relies on banks and the loans offered by national and domestic banking sectors due to the banking and financial sector's rapid growth. In India 67% people are rely on loans to meet their financial needs. Banks receive numerous loan applications daily from customers and other people, but not all of them are approved. Banks often handle loan applications after confirming and assessing the applicant's eligibility, which is a difficult and time-consuming process. The majority of lenders use their credit score and risk assessment algorithms when reviewing loan applications and deciding whether to approve loans. In spite of this, some applicants miss payments on their bills every year, costing financial institutions a sizable sum of money. In this work, machine learning (ML) algorithms are used to identify trends in a dataset of loans that have been granted and make predictions to find the deserving loan applicants. Customers' prior information, including age, income type, loan annuity, most recent credit bureau report, employer type, length of employment, and family history, will be used to conduct the study. In this paper, we primarily concentrate on determining the family's level of poverty as well as the applicant's credit score and risk assessment to determine whether they are eligible or not. |
| Keywords: | Random forest, cross validation, Machine Learning |
| Cite Article: | "Predicting the level of Income Qualification for Bank loan Approval", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 7, page no.377 - 380, July-2023, Available :http://www.ijsdr.org/papers/IJSDR2307051.pdf |
| Downloads: | 000338536 |
| Publication Details: | Published Paper ID: IJSDR2307051 Registration ID:207667 Published In: Volume 8 Issue 7, July-2023 DOI (Digital Object Identifier): Page No: 377 - 380 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijsdr.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
Track Paper
Important Links
Conference Proposal
ISSN
 |
 |
DOI (A digital object identifier)
  Providing A digital object identifier by DOI How to GET DOI and Hard Copy Related |
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
 |
 |
 |
Social Media
Indexing Partner |
|||
| Copyright © 2024 - All Rights Reserved - IJSDR | |||
Facebook Twitter Instagram LinkedIn