Financial Fraud and Anomaly Detection Techniques: A Literature Review
Author:
Affiliation:
1. University of Portsmouth, United Kingdom
2. Anqing Vocational and Technical College of Anhui Province, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3644523.3644639
Reference65 articles.
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2. Kirkos E. Spathis C. & Manolopoulos Y. 2007. Data mining techniques for the detection of fraudulent financial statements. Expert systems with applications 32(4) 995-1003.
3. Bhattacharyya S. Jha S. Tharakunnel K. & Westland J. C. 2011. Data mining for credit card fraud: A comparative study. Decision support systems 50(3) 602-613.
4. Hilal W. Gadsden S. A. & Yawney J. 2022. Financial fraud: a review of anomaly detection techniques and recent advances. Expert systems With applications 193 116429.
5. Trade-based money laundering: Risks and regulatory responses;Sullivan C. L.;Australian Institute of Criminology,2012
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