Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks
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- Jans, Mieke & Lybaert, Nadine & Vanhoof, Koen, 2010. "Internal fraud risk reduction: Results of a data mining case study," International Journal of Accounting Information Systems, Elsevier, vol. 11(1), pages 17-41.
- Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
- Debreceny, Roger S. & Gray, Glen L., 2010. "Data mining journal entries for fraud detection: An exploratory study," International Journal of Accounting Information Systems, Elsevier, vol. 11(3), pages 157-181.
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- Ricardo Muller & Marco Schreyer & Timur Sattarov & Damian Borth, 2022. "RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations," Papers 2209.09157, arXiv.org.
- Ahmad Faisal Hayek & Nora Azima Noordin & Khaled Hussainey, 2022. "Machine Learning and External Auditor Perception: An Analysis for UAE External Auditors Using Technology Acceptance Model," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 21(4), pages 475-500, December.
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-ACC-2019-08-19 (Accounting and Auditing)
- NEP-BIG-2019-08-19 (Big Data)
- NEP-CMP-2019-08-19 (Computational Economics)
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