Predicting Credit Card Frauds in India: An Empirical Investigation

This study attempts to predict credit card fraud and to know the factors responsible for credit card fraud. Using primary data of 7,500 credit card holders, collected using a questionnaire, this study conducts statistical analysis using discriminant analysis method. It is observed that variables, such as distance from home, distance from the last transaction, ratio to the median purchase price, used chip, used PIN for the transaction, and online order are significant factors in contributing to credit card fraud.

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Publication Details

Journal
International Journal of Economics and Financial Issues
Published
2024-12-06
DOI
https://doi.org/10.32479/ijefi.17666
Citations
2
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.69
Controls
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article

Predicting Credit Card Frauds in India: An Empirical Investigation

Lokendra Puri, Ranjit Singh, Rafiqul Bhuyan
2 citations
International Journal of Economics and Financial Issues
Imbalanced Data Classification Techniques
0.69
article

Predicting Credit Card Frauds in India: An Empirical Investigation

Lokendra Puri, Ranjit Singh, Rafiqul Bhuyan
article en
2 citations

Abstract

This study attempts to predict credit card fraud and to know the factors responsible for credit card fraud. Using primary data of 7,500 credit card holders, collected using a questionnaire, this study conducts statistical analysis using discriminant analysis method. It is observed that variables, such as distance from home, distance from the last transaction, ratio to the median purchase price, used chip, used PIN for the transaction, and online order are significant factors in contributing to credit card fraud.

International Journal of Economics and Financial IssuesVol. 15(1)
Alabama Agricultural and Mechanical University (US), Indian Institute of Information Technology Allahabad (IN)
Reduced inequalities
Openalex Percentile: Top 23%
Imbalanced Data Classification Techniques
0.69
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