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Rad, M, Amiri, A, Ranjbar, MH and Salari, H (2021). Predictability of financial statements fraud-risk using Benford’s Law. Cogent Economics & Finance 9(1), p. 1889756 .

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Balcıoğlu, YS, Merter, AK, Cerez, S and Özer, G (2024). Analysis of Annual Reports of Firms Listed on Borsa Istanbul Using Benford’s Law. In: Ozatac, N., Taspinar, N., Rustamov, B. (eds) Sustainable Development in Banking and Finance. ICBFP 2023. Springer Proceedings in Business and Economics. Springer, Cham.. DOI:10.1007/978-3-031-65533-3_7. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Gepp, A, Kumar, K and Bhattacharya, S (2023). Taking the hunch out of the crunch: A framework to improve variable selection in models to detect financial statement fraud. Accounting & Finance 2023, pp.1–20.. DOI:10.1111/acfi.13192 . View Complete Reference Online information Works that this work references No Bibliography works reference this work
Shahana, T, Lavanya, V and Bhat, AR (2023). State of the art in financial statement fraud detection: A systematic review. Technological Forecasting and Social Change 192, p. 122527 . DOI:10.1016/j.techfore.2023.122527. View Complete Reference Online information Works that this work references Works that reference this work
Sushkov, VM, Leonov, PY, Nadezhina, OS and Blagova, IY (2023). Integrating Data Mining Techniques for Fraud Detection in Financial Control Processes. International Journal of Technology 14(8), pp. 1675-1684. DOI:10.14716/ijtech.v14i8.6830. View Complete Reference Online information Works that this work references No Bibliography works reference this work