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Winter, C, Schneider, M and Yannikos, Y (2012). Model-Based Digit Analysis for Fraud Detection overcomes Limitations of Benford Analysis. Availability, Reliability and Security (ARES 2012), Seventh International Conference, August 20–24, 2012, Prague, Czech Republic. IEEE CS volume E4775, pages 255–261. IEEE Computer Society.

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Bannier, C, Ewelt-Knauer, C, Lips, J and Winker, P (2020). Benford’s Law and Its Application to Detecting Financial Fraud and Manipulation. Ch. 18 in: Corruption and Fraud in Financial Markets: Malpractice, Misconduct and Manipulation, C. Alexander and D. Cumming (Eds.), John Wiley & Sons: Chichester, U.K., pp. 473-504. ISSN/ISBN:978-1-119-42177-1. View Complete Reference No online information available Works that this work references Works that reference this work
Bannier, C, Ewelt-Knauer, C, Winker, P and Lips, J (2019). Benford’s law and its application to detecting financial fraud and manipulation. Chapter 5 of Econometric Modelling of Energy & Financial Markets, Doctoral Thesis of Johannes Lips, Justus-Liebig University Gießen . View Complete Reference Online information Works that this work references No Bibliography works reference this work
Joksimović, D, Knežević, G, Pavlović, V, Ljubić, M and Surovy, V (2017). Some Aspects of the Application of Benford’s Law in the Analysis of the Data Set Anomalies. In: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling. New York: Nova Science Publishers, pp. 85–120. ISSN/ISBN:978-1-53610-566-7. View Complete Reference Online information Works that this work references Works that reference this work
McCarville, D (2021). A data transformation process for using Benford’s Law with bounded data. Preprint [version 1; peer review: awaiting peer review], Emerald Open Research 3(29). DOI:10.35241/emeraldopenres.14374.1. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Poekl, G (2016). Newcomb-Benford's Law ohne Limits. 03.16 ZRFC Risk, Fraud & Compliance, Erich-Schmid-Verlag, Berlin, Germany, pp. 115-120. GER View Complete Reference Online information Works that this work references No Bibliography works reference this work
Wei, L, Sundararajan, A, Sarwat, AI, Biswas, S and Ibrahim, E (2017). A distributed intelligent framework for electricity theft detection using benford's law and stackelberg game. IEEE Proceedings of 2017 Resilience Week (RWS), pp. 5-11. DOI:10.1109/RWEEK.2017.8088640. View Complete Reference Online information Works that this work references Works that reference this work