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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.

This work cites the following items of the Benford Online Bibliography:

Alali, FA and Romero, S (2013). Benford’s Law: Analyzing a decade of financial data. Journal of Emerging Technologies in Accounting Vol. 10, No. 1, pp. 1-39. DOI:10.2308/jeta-50749. View Complete Reference Online information Works that this work references Works that reference this work
Ausloos, M, Cerqueti, R and Mir, TA (2017). Data science for assessing possible tax income manipulation: The case of Italy. Chaos, Solitons and Fractals 104, pp. 238–256. DOI:10.1016/j.chaos.2017.08.012. View Complete Reference Online information Works that this work references Works that reference this work
Badal-Valero, E, Alvarez-Jareño, JA and Pavía, JM (2018). Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case. Forensic Science International 282, pp. 24-34. DOI:10.1016/j.forsciint.2017.11.008. View Complete Reference Online information Works that this work references Works that reference this work
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Carslaw, CAPN (1988). Anomalies in Income Numbers: Evidence of Goal Oriented Behavior. The Accounting Review 63(2), pp. 321-327. View Complete Reference Online information Works that this work references Works that reference this work
Christian, CW and Gupta, S (1993). New evidence on "Secondary Evasion". The Journal of the American Taxation Association 15(1), pp. 72-93. View Complete Reference Online information Works that this work references Works that reference this work
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. DOI:10.1016/j.accinf.2010.08.001. View Complete Reference Online information Works that this work references Works that reference this work
Drake, PD and Nigrini, MJ (2000). Computer assisted analytical procedures using Benford’s law. Journal of Accounting Education 18, pp. 127-146. DOI:10.1016/S0748-5751(00)00008-7. View Complete Reference Online information Works that this work references Works that reference this work
Hales, DN, Sridharan, V, Radhakrishnan, A, Chakravorty, SS and Sihad, SM (2008). Testing the accuracy of employee-reported data: An inexpensive alternative approach to traditional methods. European Journal of Operational Research 189(3), pp. 583-593. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (1996). A taxpayer compliance application of Benford’s law. Journal of the American Taxation Association 18(1), pp. 72-91. View Complete Reference Online information Works that this work references Works that reference this work
Thomas, JK (1989). Unusual Patterns in Reported Earnings. Accounting Review 64(4), 773-787. ISSN/ISBN:0001-4826. View Complete Reference Online information Works that this work references Works that reference this work
Tödter, K-H (2009). Benford's Law as an Indicator of Fraud in Economics. German Economic Review 10(3), 339-351. DOI:10.1111/j.1468-0475.2009.00475.x. View Complete Reference Online information Works that this work references Works that reference this work