DEBENTURE BANKRUPT PREDICTION USING MACHINE LEARNING TECHNIQUES

In Debenture bankrupt prediction using machine learning techniques many people take loan from different bank and companies like India Bulls but the authority of that company decide whether to sanction the loan for the loan seeker or not based on certain criterion. But nowadays technology become so powerful that using machine leaning techniques we can decide whether it would be good decision to sanction the loan or not based on the individual’s transaction history. And here four techniques CNN, Naives-Bayes Classifier, CVM(Support Vector Machine) is used to determine the loan seeker is a good returner or not and also it see’s which method’s among the used four methods is best on the basis of efficiency. A strong ability to predict the factors affecting repayment is of great importance to mitigate information asymmetry among borrowers, lending platforms and lenders should be displayed on the borrowing webpage

Authors

Publication Details

Journal
International Journal of Apllied Mathematics
Published
2025-09-27
DOI
https://doi.org/10.12732/ijam.v38i4s.267
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

DEBENTURE BANKRUPT PREDICTION USING MACHINE LEARNING TECHNIQUES

Vani Marc
International Journal of Apllied Mathematics
Financial Distress and Bankruptcy Prediction
article

DEBENTURE BANKRUPT PREDICTION USING MACHINE LEARNING TECHNIQUES

Vani Marc
article en

Abstract

In Debenture bankrupt prediction using machine learning techniques many people take loan from different bank and companies like India Bulls but the authority of that company decide whether to sanction the loan for the loan seeker or not based on certain criterion. But nowadays technology become so powerful that using machine leaning techniques we can decide whether it would be good decision to sanction the loan or not based on the individual’s transaction history. And here four techniques CNN, Naives-Bayes Classifier, CVM(Support Vector Machine) is used to determine the loan seeker is a good returner or not and also it see’s which method’s among the used four methods is best on the basis of efficiency. A strong ability to predict the factors affecting repayment is of great importance to mitigate information asymmetry among borrowers, lending platforms and lenders should be displayed on the borrowing webpage

International Journal of Apllied MathematicsVol. 38(4s)
Openalex Percentile: Top 62%
Financial Distress and Bankruptcy Prediction
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