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Debreceny, RS and Gray, GL (2010). Data mining journal entries for fraud detection: An exploratory study. International Journal of Accounting Information Systems, Vol. 11, No. 3, pp. 157–181.

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Arslan, U, Calıyurt, KT and Kahyaoglu, SB (2024). Financial statement anomaly detection based on Benford law and Beneish model: Case of a public sector hospital. The EDP Audit, Control, and Security Newsletter Volume 69, 2024, pp 69-87. DOI:10.1080/07366981.2024.2312018. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Cella, RS and Zanolla, E (2018). Benford’s Law and transparency: an analysis of municipal expenditure. Brazilian Business Review, 15(4), pp. 331-347. DOI:10.15728/bbr.2018.15.4.2. View Complete Reference Online information Works that this work references Works that reference this work
Charoenwong, B and Reddy, P (2022). Using forensic analytics and machine learning to detect bribe payments in regime-switching environments: Evidence from the India demonetization. PLoS ONE 17(6): e0268965. DOI:10.1371/journal.pone.0268965. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Coufalová, L, Mikula, S and Žídek, L (2022). Misreporting in financial statements in a centrally planned economy: The case of Czechoslovak state-owned enterprises in late socialism. Accounting History. DOI:10.1177/10323732221109652. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Ergin, E and Erturan, IE (2020). Is Benford’s Law Effective in Fraud Detection for Expense Cycle? . Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 42(2), pp. 316–326. DOI:10.14780.muiibd.854444. View Complete Reference Online information Works that this work references Works that reference this work
Grabski, S (2010). Discussion of 'Data mining journal entries for fraud detection: An exploratory study'. International Journal of Accounting Information Systems, Vol. 11, No. 3, pp. 182–185. DOI:10.1016/j.accinf.2010.07.008. View Complete Reference Online information Works that this work references Works that reference this work
Jianu, Io and Jianu, Iu (2021). Reliability of Financial Information from the Perspective of Benford’s Law. Entropy 23(5), article no. 557. DOI:10.3390/e23050557. View Complete Reference Online information Works that this work references Works that reference this work
Karavardar, A (2014). Benford’s Law and an Analysis in Istanbul Stock Exchange (BIST). International Journal of Business and Management, 9(4), pp. 160-172. DOI:10.5539/ijbm.v9n4p160. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (2016). The Implications of the Similarity between Fraud Numbers and the Numbers in Financial Accounting Textbooks and Test Banks. Journal of Forensic Accounting Research, Vol. 1, No. 1, pp. A1-A26. DOI:10.2308/jfar-51465. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (2017). Audit Sampling Using Benford's Law: A Review of the Literature With Some New Perspectives. Journal of Emerging Technologies in Accounting Vol. 14, No. 2, pp. 29–46. DOI:10.2308/jeta-51783. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (2019). The patterns of the numbers used in occupational fraud schemes. Managerial Auditing Journal 34(5), pp. 606--626. DOI:10.1108/MAJ-11-2017-1717. View Complete Reference Online information Works that this work references Works that reference this work
Pizzi, S, Venturelli, A, Variale, M and Macro, GP (2021). Assessing the impacts of digital transformation on internal auditing: A bibliometric analysis. Technology in Society 67, p. 101738. DOI:10.1016/j.techsoc.2021.101738. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Sadaf, R (2016). Benford’s Law in the Case of Hungarian Whole-Sale Trade Sector. SEA – Practical Application of Science 12, pp. 561-566. View Complete Reference Online information Works that this work references Works that reference this work
Seow, P-S, Pan, G and Suwardy, T (2016). Data Mining Journal Entries for Fraud Detection: A Replication of Debreceny and Gray's (2010) Techniques. Journal of Forensic and Investigative Accounting 8(3), pp. 501-514. View Complete Reference Online information Works that this work references Works that reference this work
Silva, AdeA and Gouvêa, MA (2023). Study on the effect of sample size on type I error, in the first, second and first-two digits excessmad tests. International Journal of Accounting Information Systems 48, p. 100599. DOI:10.1016/j.accinf.2022.100599. View Complete Reference Online information Works that this work references No Bibliography works reference this work