Cost-sensitive Fraud Detection
Cost-Sensitive Fraud Detection is a fraud detection approach that belongs to the class of classification methods in machine learning and is specifically distinguished by its explicit integration of asymmetric cost structures to minimize the total expected cost of misclassification, particularly in the underwriting context where false negatives and false positives entail unequal financial consequences.
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2.4K
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94
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44
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2017–2026
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Cost Sensitive Credit Card Fraud Detection Using Bayes Minimum Risk
Alejandro Correa Bahnsen, Aleksandar Stojanović, Djamila Aouada et al. · 2013 · 163 citations · Full text
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Özyeğin University
Istanbul, Türkiye
2 h-index
2 publications
401 citations
Maastricht University
Maastricht, The Netherlands
2 h-index
2 publications
83 citations
Indiana University
Bloomington, United States
2 h-index
3 publications
151 citations
Central Bank of the Republic of Turkey
Ankara, Turkey
2 h-index
4 publications
132 citations

Maastricht School of Management
Maastricht, The Netherlands
2 h-index
2 publications
83 citations
University of Luxembourg
Luxembourg, Luxembourg
2 h-index
6 publications
702 citations

National Institute of Technology Tiruchirappalli
Tiruchchirappalli, India
2 h-index
4 publications
168 citations
Georgia State University
Atlanta, United States
1 h-index
1 publications
76 citations
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3 publications · 650 citations
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Repository · 2 publications · 40 citations
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1 publications · 76 citations
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TKDE · 1 publications · 22 citations
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1 publications · 54 citations
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