Financial Statement Fraud Detection Using Optimized Deep Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8438-1_10
Reference27 articles.
1. Albizri A, Appelbaum D, Rizzotto N (2019) Evaluation of financial statements fraud detection research: a multi-disciplinary analysis. Int J Discl Gov 16(4):206–241
2. Dalnial H, Kamaluddin A, Sanusi ZM, Khairuddin KS (2014) Detecting fraudulent financial reporting through financial statement analysis. J Adv Manag Sci 2(1) (2014).
3. Ye H, Xiang L, Gan Y (2019) Detecting financial statement fraud using random forest with SMOTE. In: IOP conference series: materials science and engineering, vol 612, no 5. IOP Publishing, p 052051
4. Song X-P, Hu Z-H, Du J-G, Sheng Z-H (2014) Application of machine learning methods to risk assessment of financial statement fraud: evidence from China. J Forecast 33(8):611–626
5. Rukmana HS (2021) Determinants of pentagon fraud in detecting financial statement fraud and company value. Majalah Ilmiah Bijak 18(1):109–117
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