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A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits

Citations

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Cited by:

  1. Yuan Song & Hongwei Wang & Maoran Zhu, 2018. "Sustainable strategy for corporate governance based on the sentiment analysis of financial reports with CSR," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-14, December.
  2. Anastassia Fedyk & James Hodson & Natalya Khimich & Tatiana Fedyk, 2022. "Is artificial intelligence improving the audit process?," Review of Accounting Studies, Springer, vol. 27(3), pages 938-985, September.
  3. Adriana Tiron-Tudor & Widad Atena Faragalla & Anca Pianoschi, 2025. "The role of the accountancy professionals in detecting and preventing fraud, in a digital landscape: a systematic literature review," Digital Finance, Springer, vol. 7(4), pages 745-786, December.
  4. Rabeea SADAF, 2016. "Benford’S Law In The Case Of Hungarian Whole-Sale Trade Sector," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 12, pages 561-566, December.
  5. Sonika Gupta & Sushil Kumar Mehta, 2024. "Data Mining-based Financial Statement Fraud Detection: Systematic Literature Review and Meta-analysis to Estimate Data Sample Mapping of Fraudulent Companies Against Non-fraudulent Companies," Global Business Review, International Management Institute, vol. 25(5), pages 1290-1313, October.
  6. Dilla, William N. & Raschke, Robyn L., 2015. "Data visualization for fraud detection: Practice implications and a call for future research," International Journal of Accounting Information Systems, Elsevier, vol. 16(C), pages 1-22.
  7. Earley, Christine E., 2015. "Data analytics in auditing: Opportunities and challenges," Business Horizons, Elsevier, vol. 58(5), pages 493-500.
  8. Matei Andreea-Nicoleta Liţă & Stoica Silviu Ionel & Grigorescu Petronela-Alice & Radu Valentin, 2025. "Forensic Accounting in the Knowledge and Innovation Society: A Bibliometric Approach," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 5627-5647.
  9. Chen, Yuh-Jen & Liou, Wan-Ching & Chen, Yuh-Min & Wu, Jyun-Han, 2019. "Fraud detection for financial statements of business groups," International Journal of Accounting Information Systems, Elsevier, vol. 32(C), pages 1-23.
  10. Mushang Lee & Yu-Lan Huang, 2020. "Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
  11. Huidong Sun & Mustafa Raza Rabbani & Muhammad Safdar Sial & Siming Yu & José António Filipe & Jacob Cherian, 2020. "Identifying Big Data’s Opportunities, Challenges, and Implications in Finance," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
  12. Alles, Michael & Gray, Glen L., 2016. "Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors," International Journal of Accounting Information Systems, Elsevier, vol. 22(C), pages 44-59.
  13. Federica De Santis, 2018. "Big Data e revisione contabile: uno studio esplorativo nel contesto italiano," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 129-154.
  14. Andrea Cardoni & Evgeniia Kiseleva & Francesco De Luca, 2020. "Continuous auditing and data mining for strategic risk control and anticorruption: Creating “fair” value in the digital age," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3072-3085, December.
  15. Aglaya Batz & David F. D’Croz-Barón & Carlos Jesús Vega Pérez & Carlos A. Ojeda-Sanchez, 2025. "Integrating machine learning into business and management in the age of artificial intelligence," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-20, December.
  16. Ruhnke, Klaus, 2023. "Empirical research frameworks in a changing world: The case of audit data analytics," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 51(C).
  17. Fábio Albuquerque & Paula Gomes Dos Santos, 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools," FinTech, MDPI, vol. 2(2), pages 1-27, April.
  18. Mirjana Pejić Bach & Živko Krstić & Sanja Seljan & Lejla Turulja, 2019. "Text Mining for Big Data Analysis in Financial Sector: A Literature Review," Sustainability, MDPI, vol. 11(5), pages 1-27, February.
  19. Laskai András, 2019. "AI foundations of the international business planning and the AI consciousness model," International Journal of Science and Business, IJSAB International, vol. 3(1), pages 17-28.
  20. Craja, Patricia & Kim, Alisa & Lessmann, Stefan, 2020. "Deep Learning application for fraud detection in financial statements," IRTG 1792 Discussion Papers 2020-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  21. Saxton, Gregory D. & Guo, Chao, 2020. "Social media capital: Conceptualizing the nature, acquisition, and expenditure of social media-based organizational resources," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
  22. Abdullah Albizri & Deniz Appelbaum & Nicholas Rizzotto, 2019. "Evaluation of financial statements fraud detection research: a multi-disciplinary analysis," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 16(4), pages 206-241, December.
  23. Freiman, Jamie W. & Kim, Yongbum & Vasarhelyi, Miklos A., 2022. "Full population testing: Applying multidimensional audit data sampling (MADS) to general ledger data auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
  24. Jacqueline Birt & Maryam Safari & Vincent Bicudo de Castro, 2023. "Critical analysis of integration of ICT and data analytics into the accounting curriculum: A multidimensional perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4037-4063, December.
  25. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
  26. Maria Tragouda & Michalis Doumpos & Constantin Zopounidis, 2024. "Identification of fraudulent financial statements through a multi‐label classification approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
  27. Jean Robert Kala Kamdjoug & Hyacinthe Djanan Sando & Jules Raymond Kala & Arielle Ornela Ndassi Teutio & Sunil Tiwari & Samuel Fosso Wamba, 2024. "Data analytics-based auditing: a case study of fraud detection in the banking context," Annals of Operations Research, Springer, vol. 340(2), pages 1161-1188, September.
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