The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Intelligent financial fraud detection: A comprehensive review
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Citations
Cites
Forecasting with artificial neural networks:
Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229
Statistical Fraud Detection: A Review
Bolton, R. J., & Hand, D. J. (2002) · Statistical Science · doi:10.1214/ss/1042727940 · Cited by 1,450
Ngai, E. W. T., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.08.006 · Cited by 1,361
The Detection of Earnings Manipulation
Beneish, M. D. (1999) · Financial Analysts Journal · doi:10.2469/faj.v55.n5.2296 · Cited by 1,284
Data mining for credit card fraud: a comparative study
Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.08.008 · Cited by 1,108 · cited 10×
“Fraudsters are continually refining their methods, and as such there is a requirement for detection methods to be able to evolve accordingly [7].”
InfluentialYeh, I.-C., & Lien, C.-H. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2007.12.020 · Cited by 885
Data Mining techniques for the detection of fraudulent financial statements
KIRKOS, E., SPATHIS, C., & MANOLOPOULOS, Y. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.02.016 · Cited by 722
The effects of audit committee activity and independence on corporate fraud
Abbott, L. J., Park, Y., & Parker, S. (2000) · Managerial Finance · doi:10.1108/03074350010766990 · Cited by 635
Detection of financial statement fraud and feature selection using data mining techniques
Ravisankar, P., Ravi, V., Raghava Rao, G., & Bose, I. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.11.006 · Cited by 582
Identifying the signs of fraudulent accounts using data mining techniques
Li, S.-H., Yen, D. C., Lu, W.-H., & Wang, C. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.01.002 · Cited by 505
Cited by
The role of artificial intelligence in achieving the Sustainable Development Goals
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020) · Nature Communications · doi:10.1038/s41467-019-14108-y · Cited by 3,294
Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019
Al-Hashedi, K. G., & Magalingam, P. (2021) · Computer Science Review · doi:10.1016/j.cosrev.2021.100402 · Cited by 375
Hajek, P., & Henriques, R. (2017) · Knowledge-Based Systems · doi:10.1016/j.knosys.2017.05.001 · Cited by 334
Akasheh, M. A., Malik, E. F., Hujran, O., & Zaki, N. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121794 · Cited by 78
Yang, J., Amrollahi, A., & Marrone, M. (2024) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2024.101864 · Cited by 59
Metadata
- Authors
- West, J., & Bhattacharya, M.
- Venue
- Computers & Security
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 57
- Pages
- 47-66
- ISSN
- 0167-4048 (ISSN-L)
- OpenAlex
- W2172852798
- Cited by
- 592
- References
- 54
- FWCI
- 14.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Intelligent financial fraud detection: A comprehensive review. https://app.cochat.ai/papers/10.1016/j.cose.2015.09.005
- The paper
- West, J., & Bhattacharya, M. (2016). Intelligent financial fraud detection: A comprehensive review. Computers & Security. https://doi.org/10.1016/j.cose.2015.09.005
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
