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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Credit Risk Analysis Of Personal Credit Card Default Using Machine Learning Algorithm
Authors
Huzefa Chhatriwala, Bhaskar Vishvakarma, Devendra Kumar Pandey, Nitin Kumar Chaudhry
Keywords
Credit Risk Analysis, Loan Default Prediction, Machine Learning, Classification Models, Predictive Modeling, Financial Risk Management, Supervised Learning, Unsupervised Learning, Logistic Regression, Polynomial Regression, K-means Clustering, Borrower Segmentation, Financial Decision-Making, Accuracy Optimization, Feature Engineering, Risk Profiling.
Abstract
Credit loans are one of the most used loans. Credit loans earn a lot of money for the banking sector. If the loan defaults, it has impact on profit. The precise credit risk analysis is required to manage the defaults of the borrower. With a dataset containing different borrower attributes, the present research has different machine learning methods investigate a multi-model framework that integrates classification, Regression and Clustering methods. This research investigate a hybrid strategy by using a combination of different methods. Model of regression, classification are used in prediction of two target variable default_in_last_6_months and credit_card_default. This Model will aid in improving credit risk assessment and assist financial institution in streamlining loan approval procedures and risk management policies.
IJCRT's Publication Details
Unique Identification Number - IJCRT2506201
Paper ID - 285429
Page Number(s) - b736-b746
Pubished in - Volume 13 | Issue 6 | June 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Huzefa Chhatriwala, Bhaskar Vishvakarma, Devendra Kumar Pandey, Nitin Kumar Chaudhry, "Credit Risk Analysis Of Personal Credit Card Default Using Machine Learning Algorithm", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 6, pp.b736-b746, June 2025, Available at :http://www.ijcrt.org/papers/IJCRT2506201.pdf
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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