Financial fraud detection through the application of machine learning techniques: a literature review
Author:
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41599-024-03606-0.pdf
Reference129 articles.
1. Abdallah A, Maarof MA, Zainal A (2016) Fraud detection system: a survey. J Netw Comput Appl 68:90–113. https://doi.org/10.1016/j.jnca.2016.04.007
2. Achakzai MAK, Juan P (2022) Using machine learning meta-classifiers to detect financial frauds. Financ Res Lett 48:102915. https://doi.org/10.1016/j.frl.2022.102915
3. Ahmed M, Mahmood AN, Islam MdR (2016) A survey of anomaly detection techniques in financial domain. Future Gener Comput Syst 55:278–288. https://doi.org/10.1016/j.future.2015.01.001
4. Al Ali A, Khedr AM, El-Bannany M, Kanakkayil S (2023) A powerful predicting model for financial statement fraud based on optimized XGBoost ensemble learning technique. Appl Sci 13(4):2272. https://doi.org/10.3390/app13042272
5. Alarfaj FK, Malik I, Khan HU, Almusallam N, Ramzan M, Ahmed M (2022) Credit card fraud detection using state-of-the-art machine learning and deep learning algorithms. IEEE Access 10:39700–39715. https://doi.org/10.1109/ACCESS.2022.3166891
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