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Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach

Citations

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Cited by:

  1. Xiaowei Chen & Cong Zhai, 2023. "Bagging or boosting? Empirical evidence from financial statement fraud detection," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 5093-5142, December.
  2. Richardson, Grant & Obaydin, Ivan & Liu, Chelsea, 2022. "The effect of accounting fraud on future stock price crash risk," Economic Modelling, Elsevier, vol. 117(C).
  3. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
  4. Yasheng Chen & Zhuojun Wu, 2022. "Financial Fraud Detection of Listed Companies in China: A Machine Learning Approach," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
  5. Zhou, Ying & Xiao, Zhi & Gao, Ruize & Wang, Chang, 2024. "Using data-driven methods to detect financial statement fraud in the real scenario," International Journal of Accounting Information Systems, Elsevier, vol. 54(C).
  6. Liu, Wanli, 2024. "Digital transformation and earnings opacity:Evidence from China," Finance Research Letters, Elsevier, vol. 69(PA).
  7. Hanyao Gao & Gang Kou & Haiming Liang & Hengjie Zhang & Xiangrui Chao & Cong-Cong Li & Yucheng Dong, 2024. "Machine learning in business and finance: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-35, December.
  8. van der Heijden, Hans, 2022. "Predicting industry sectors from financial statements: An illustration of machine learning in accounting research," The British Accounting Review, Elsevier, vol. 54(5).
  9. Zhao, Qi & Xu, Weijun & Ji, Yucheng, 2023. "Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?," International Review of Financial Analysis, Elsevier, vol. 89(C).
  10. Yousefi, Hamed & Yung, Kenneth & Najand, Mohammad, 2023. "From low resource slack to inflexibility: The share price effect of operational efficiency," International Review of Financial Analysis, Elsevier, vol. 90(C).
  11. Md Jahidur Rahman & Hongtao Zhu, 2023. "Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3455-3486, September.
  12. Xin Xu & Feng Xiong & Zhe An, 2023. "Using Machine Learning to Predict Corporate Fraud: Evidence Based on the GONE Framework," Journal of Business Ethics, Springer, vol. 186(1), pages 137-158, August.
  13. Stephen Walker, 2021. "Critique of an Article on Machine Learning in the Detection of Accounting Fraud," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-61–70, March.
  14. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 237-291, March.
  15. Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2021. "A Response to "Critique of an Article on Machine Learning in the Detection of Accounting Fraud"," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-71–78, March.
  16. Essi Nousiainen & Mikko Ranta & Mika Ylinen & Marko Järvenpää, 2024. "Using machine learning and 10‐K filings to measure innovation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 3211-3239, December.
  17. Vitali, Sonia & Giuliani, Marco, 2024. "Emerging digital technologies and auditing firms: Opportunities and challenges," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).
  18. Miao Liu, 2022. "Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 607-651, May.
  19. Moritz Schneider & Rolf Brühl, 2023. "Disentangling the black box around CEO and financial information-based accounting fraud detection: machine learning-based evidence from publicly listed U.S. firms," Journal of Business Economics, Springer, vol. 93(9), pages 1591-1628, November.
  20. Stephen Walker, 2022. "Erroneous Erratum to Accounting Fraud Article," Econ Journal Watch, Econ Journal Watch, vol. 19(2), pages 190–203-1, September.
  21. Achakzai, Muhammad Atif Khan & Peng, Juan, 2023. "Detecting financial statement fraud using dynamic ensemble machine learning," International Review of Financial Analysis, Elsevier, vol. 89(C).
  22. Wang, Delu & Chen, Fan & Mao, Jinqi & Liu, Nannan & Rong, Fangyu, 2022. "Are the official national data credible? Empirical evidence from statistics quality evaluation of China's coal and its downstream industries," Energy Economics, Elsevier, vol. 114(C).
  23. Nawaf Almaskati, 2022. "Machine learning in finance: Major applications, issues, metrics, and future trends," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-32, September.
  24. So-Jin Yu & Jin-Sung Rha, 2021. "Research Trends in Accounting Fraud Using Network Analysis," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
  25. Gao, Wei & Ju, Ming & Yang, Tongyang, 2023. "Severe weather and peer-to-peer farmers’ loan default predictions: Evidence from machine learning analysis," Finance Research Letters, Elsevier, vol. 58(PA).
  26. Seth Armitage & Ronan Gallagher & Jiaman Xu, 2023. "The elusive relation between pension discount rates and deficits," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(7-8), pages 1101-1127, July.
  27. Yunchuan Sun & Xiaoping Zeng & Ying Xu & Hong Yue & Xipu Yu, 2024. "An intelligent detecting model for financial frauds in Chinese A‐share market," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 1110-1136, July.
  28. Haibo Wang & Lutfu S. Sua & Bahram Alidaee, 2024. "Enhancing supply chain security with automated machine learning," Papers 2406.13166, arXiv.org, revised Dec 2024.
  29. Lukui Huang & Alan Abrahams & Peter Ractham, 2022. "Enhanced financial fraud detection using cost‐sensitive cascade forest with missing value imputation," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 133-155, July.
  30. Jun, So Young & Kim, Dong Sung & Jung, Suk Yoon & Jun, Sang Gyung & Kim, Jong Woo, 2022. "Stock investment strategy combining earnings power index and machine learning," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).
  31. Laure Batz, 2023. "Financial market enforcement in France," European Journal of Law and Economics, Springer, vol. 55(3), pages 409-468, June.
  32. Booker, Adam & Chiu, Victoria & Groff, Nathan & Richardson, Vernon J., 2024. "AIS research opportunities utilizing Machine Learning: From a Meta-Theory of accounting literature," International Journal of Accounting Information Systems, Elsevier, vol. 52(C).
  33. Kexing Ding & Baruch Lev & Xuan Peng & Ting Sun & Miklos A. Vasarhelyi, 2020. "Machine learning improves accounting estimates: evidence from insurance payments," Review of Accounting Studies, Springer, vol. 25(3), pages 1098-1134, September.
  34. Kelton, Andrea Seaton & Murthy, Uday S., 2023. "Reimagining design science and behavioral science AIS research through a business activity lens," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
  35. Li, Guowen & Wang, Shuai & Feng, Yuyao, 2024. "Making differences work: Financial fraud detection based on multi-subject perceptions," Emerging Markets Review, Elsevier, vol. 60(C).
  36. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
  37. Zhou, Ying & Li, Haoran & Xiao, Zhi & Qiu, Jing, 2023. "A user-centered explainable artificial intelligence approach for financial fraud detection," Finance Research Letters, Elsevier, vol. 58(PA).
  38. Li, Jing & Li, Nan & Xia, Tongshui & Guo, Jinjin, 2023. "Textual analysis and detection of financial fraud: Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 126(C).
  39. Ruijie Sun & Feng Liu & Yinan Li & Rongping Wang & Jing Luo, 2024. "Machine Learning for Predicting Corporate Violations: How Do CEO Characteristics Matter?," Journal of Business Ethics, Springer, vol. 195(1), pages 151-166, November.
  40. Vanessa Heinemann-Heile, 2024. "Using Machine Learning to Predict Firms’ Tax Perception," Working Papers Dissertations 128, Paderborn University, Faculty of Business Administration and Economics.
  41. Achakzai, Muhammad Atif Khan & Juan, Peng, 2022. "Using machine learning Meta-Classifiers to detect financial frauds," Finance Research Letters, Elsevier, vol. 48(C).
  42. Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
  43. Zhishuo Zhang & Xinran Liu & Huayong Niu, 2023. "Financial crisis early warning of Chinese listed companies based on MD&A text-linguistic feature indicators," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-23, September.
  44. Bolin Liao & Zhendai Huang & Xinwei Cao & Jianfeng Li, 2022. "Adopting Nonlinear Activated Beetle Antennae Search Algorithm for Fraud Detection of Public Trading Companies: A Computational Finance Approach," Mathematics, MDPI, vol. 10(13), pages 1-14, June.
  45. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  46. Adebayo Oshingbesan & Eniola Ajiboye & Peruth Kamashazi & Timothy Mbaka, 2022. "Model-Free Reinforcement Learning for Asset Allocation," Papers 2209.10458, arXiv.org.
  47. Xi Chen & Yang Ha (Tony) Cho & Yiwei Dou & Baruch Lev, 2022. "Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 467-515, May.
  48. Luigi Rombi, 2024. "Handbook of accounting, accountability and governance edited by Garry D. Carnegie and Christopher J. Napier," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 28(3), pages 943-955, September.
  49. Yasheng Chen & Xian Huang & Zhuojun Wu, 2023. "From natural language to accounting entries using a natural language processing method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 3781-3795, December.
  50. Murphy, Brid & Feeney, Orla & Rosati, Pierangelo & Lynn, Theo, 2024. "Exploring accounting and AI using topic modelling," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
  51. Hanauer, Matthias X. & Kononova, Marina & Rapp, Marc Steffen, 2022. "Boosting agnostic fundamental analysis: Using machine learning to identify mispricing in European stock markets," Finance Research Letters, Elsevier, vol. 48(C).
  52. Wang, Yichen & Hu, Jun & Chen, Jia, 2023. "Does Fintech facilitate cross-border M&As? Evidence from Chinese A-share listed firms," International Review of Financial Analysis, Elsevier, vol. 85(C).
  53. Bhattacharya, Indranil & Mickovic, Ana, 2024. "Accounting fraud detection using contextual language learning," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).
  54. Lars Elend & Sebastian A. Tideman & Kerstin Lopatta & Oliver Kramer, 2020. "Earnings Prediction with Deep Learning," Papers 2006.03132, arXiv.org, revised Oct 2020.
  55. Elias Zavitsanos & Dimitris Mavroeidis & Konstantinos Bougiatiotis & Eirini Spyropoulou & Lefteris Loukas & Georgios Paliouras, 2023. "Financial misstatement detection: a realistic evaluation," Papers 2305.17457, arXiv.org.
  56. Yao, Haixiang & Xia, Shenghao & Liu, Hao, 2022. "Six-factor asset pricing and portfolio investment via deep learning: Evidence from Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
  57. Jeremy Bertomeu & Edwige Cheynel & Eric Floyd & Wenqiang Pan, 2021. "Using machine learning to detect misstatements," Review of Accounting Studies, Springer, vol. 26(2), pages 468-519, June.
  58. Mestiri, Sami, 2024. "Financial applications of machine learning using R software," MPRA Paper 119998, University Library of Munich, Germany.
  59. Meng, Qingbin & Zheng, Xinxing & Wang, Solomon, 2024. "Corporate governance and financial distress in China a multi-dimensional nonlinear study based on machine learning," Pacific-Basin Finance Journal, Elsevier, vol. 88(C).
  60. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
  61. Dennis W. Campbell & Ruidi Shang, 2022. "Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews," Management Science, INFORMS, vol. 68(9), pages 7034-7053, September.
  62. Rahman, Md Jahidur & Zhu, Hongtao, 2024. "Detecting accounting fraud in family firms: Evidence from machine learning approaches," Advances in accounting, Elsevier, vol. 64(C).
  63. Mika Ylinen & Mikko Ranta, 2024. "Employer ratings in social media and firm performance: Evidence from an explainable machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 247-276, March.
  64. Zhang, Chanyuan (Abigail) & Cho, Soohyun & Vasarhelyi, Miklos, 2022. "Explainable Artificial Intelligence (XAI) in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
  65. Mestiri, Sami, 2023. "How to use machine learning in finance," MPRA Paper 120045, University Library of Munich, Germany.
  66. 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.
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