Transaction aggregation as a strategy for credit card fraud detection
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The transaction aggregation methodology for deriving frequency features was first proposed by Whitrow et al. (2009) and has been used by a number of studies.
“This methodology was first proposed by Whitrow et al. (2009) and has been used by a number of studies (Bhattacharyya et al., 2011; Jha et al., 2012; Dal Pozzolo et al., 2014; Bahnsen et al., 2016).”
From Data engineering for fraud detection (2021) · cites this paper as Whitrow et al. (2009)
The total cost may not always be easy to interpret because there is no reference to which the cost is compared.
“The total cost may not always be easy to interpret because there is no reference to which the cost is compared (Whitrow et al., 2009).”
From Data engineering for fraud detection (2021) · cites this paper as Whitrow et al., 2009
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- Authors
- Whitrow, C., Hand, D. J., Juszczak, P., Weston, D., & Adams, N. M.
- Affiliations
- Imperial College London (GB)
- Corresponding author
- Whitrow, C.
- Venue
- Data Mining and Knowledge Discovery
- Published
- 2008-07-30
- Volume
- 18
- Issue
- 1
- Pages
- 30-55
- ISSN
- 1384-5810 (ISSN-L)
- 1573-756X
- OpenAlex
- W1966493433
- Cited by
- 337
- References
- 31
- Citations by year
- 2026: 42 · 2025: 45 · 2024: 19 · 2023: 28 · 2022: 26 · 2021: 25 · 2020: 26 · 2019: 35 · 2018: 24 · 2017: 15 · 2016: 6 · 2015: 13 · 2014: 7 · 2013: 6 · 2012: 6
- FWCI
- 6.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Data Mining and Knowledge Discovery (publishedVersion)
- BIROn (Birkbeck, University of London) (submittedVersion)
- Funders
- Royal Society
- Engineering and Physical Sciences Research Council
- Division of Mathematical Sciences
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Keywords
- credit card fraud detection, transaction aggregation, fraud classification, high-dimensional data, random forest, cost-sensitive classification, population drift
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