Cited by 1,108Imbalanced Data Classification TechniquesPrivacy-Preserving Technologies in DataFinancial Distress and Bankruptcy Prediction

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Data mining for credit card fraud: A comparative study

Bhattacharyya, Siddhartha, Jha, Sanjeev, Tharakunnel, Kurian, Westland, J. Christopher·2011·Decision Support Systems

DOI 10.1016/j.dss.2010.08.008

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“[3] suggests a different way to do things by using the Hidden Markov Model (HMM).”
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“In Data mining for Credit Card Fraud, another example of data mining is present, but this study focuses the previously mentioned subject of data mining with respect to credit card fraud (Bhattacharyya et al., 2011).”
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Authors: Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C.
Affiliations: University of Illinois Chicago (US)
University of New Hampshire (US)
Millikin University (US)
Corresponding author: Bhattacharyya, Siddhartha
ORCID: Bhattacharyya, Siddhartha
Westland, J. Christopher
Venue: Decision Support Systems
Publisher: Elsevier BV
Published: 2011-02
Volume: 50
Issue: 3
Pages: 602-613
ISSN: 0167-9236 (ISSN-L)
DOI: 10.1016/j.dss.2010.08.008
OpenAlex: W2045049630
Cited by: 1,108
References: 52
Citations by year: 2026: 153 · 2025: 142 · 2024: 103 · 2023: 86 · 2022: 98 · 2021: 89 · 2020: 95 · 2019: 83 · 2018: 77 · 2017: 42 · 2016: 34 · 2015: 40 · 2014: 29 · 2013: 17 · 2012: 13
FWCI: 11.76
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Decision Support Systems (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
Social Sciences › Business, Management and Accounting › Accounting › Financial Distress and Bankruptcy Prediction
Keywords: credit card fraud detection, support vector machine, random forest, logistic regression, transaction data

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Data mining for credit card fraud: A comparative study

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