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Accounting fraud detection through textual risk disclosures in annual reports: From the perspective of SEC guidelines

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Listed:
  • Xiaoqian Zhu
  • Huidong Wu
  • Yanpeng Chang
  • Jianping Li

Abstract

This study investigates the use of textual risk disclosures in annual reports to detect accounting fraud. We developed an indicator system based on Securities and Exchange Commission (SEC) guidelines to evaluate the quality of risk disclosures. An analysis of 41,343 financial reports from US listed companies revealed that textual risk disclosures enhance fraud detection accuracy and function as an early warning system. The performance of these disclosures surpasses traditional analyses of the Management Discussion and Analysis section. Our findings highlight the value of textual risk disclosures in identifying accounting fraud and underscore the crucial role of regulatory guidelines in ensuring financial integrity.

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  • Xiaoqian Zhu & Huidong Wu & Yanpeng Chang & Jianping Li, 2025. "Accounting fraud detection through textual risk disclosures in annual reports: From the perspective of SEC guidelines," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 65(2), pages 1837-1862, June.
    • Handle: RePEc:bla:acctfi:v:65:y:2025:i:2:p:1837-1862
    DOI: 10.1111/acfi.13390
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    1. David F. Larcker & Anastasia A. Zakolyukina, 2012. "Detecting Deceptive Discussions in Conference Calls," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 50(2), pages 495-540, May.
    2. Jonathan M. Karpoff & D. Scott Lee & Gerald S. Martin, 2014. "The Consequences to Managers for Financial Misrepresentation," Springer Books, in: Roberto Pietra & Stuart McLeay & Joshua Ronen (ed.), Accounting and Regulation, edition 127, chapter 0, pages 339-375, Springer.
    3. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 54(4), pages 1187-1230, September.
    4. Anne Beatty & Lin Cheng & Haiwen Zhang, 2019. "Are Risk Factor Disclosures Still Relevant? Evidence from Market Reactions to Risk Factor Disclosures Before and After the Financial Crisis," Contemporary Accounting Research, John Wiley & Sons, vol. 36(2), pages 805-838, June.
    5. Vivien Beattie & Bill McInnes & Stella Fearnley, 2004. "A methodology for analysing and evaluating narratives in annual reports: a comprehensive descriptive profile and metrics for disclosure quality attributes," Accounting Forum, Taylor & Francis Journals, vol. 28(3), pages 205-236, September.
    6. Rasha Kassem, 2014. "Detecting asset misappropriation: a framework for external auditors," International Journal of Accounting, Auditing and Performance Evaluation, Inderscience Enterprises Ltd, vol. 10(1), pages 1-42.
    7. Antonio Cabrales & Olivier Gossner & Roberto Serrano, 2013. "Entropy and the Value of Information for Investors," American Economic Review, American Economic Association, vol. 103(1), pages 360-377, February.
    8. Lynnette Purda & David Skillicorn, 2015. "Accounting Variables, Deception, and a Bag of Words: Assessing the Tools of Fraud Detection," Contemporary Accounting Research, John Wiley & Sons, vol. 32(3), pages 1193-1223, September.
    9. Abraham, Santhosh & Shrives, Philip J., 2014. "Improving the relevance of risk factor disclosure in corporate annual reports," The British Accounting Review, Elsevier, vol. 46(1), pages 91-107.
    10. Allen H. Huang & Jianghua Shen & Amy Y. Zang, 2022. "The unintended benefit of the risk factor mandate of 2005," Review of Accounting Studies, Springer, vol. 27(4), pages 1319-1355, December.
    11. Zhang, Yi & Hu, Ailing & Wang, Jiahua & Zhang, Yaojie, 2022. "Detection of fraud statement based on word vector: Evidence from financial companies in China," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Yang Xu & Lijuan Zhao, 2016. "An investigation of financial expertise improvement among CFOs hired following restatements," American Journal of Business, Emerald Group Publishing Limited, vol. 31(2), pages 50-65, June.
    13. Moll, Jodie & Yigitbasioglu, Ogan, 2019. "The role of internet-related technologies in shaping the work of accountants: New directions for accounting research," The British Accounting Review, Elsevier, vol. 51(6).
    14. 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.
    15. Xiong, Feng & Chapple, Larelle & Yin, Haiying, 2018. "The use of social media to detect corporate fraud: A case study approach," Business Horizons, Elsevier, vol. 61(4), pages 623-633.
    16. Hoberg, Gerard & Lewis, Craig, 2017. "Do fraudulent firms produce abnormal disclosure?," Journal of Corporate Finance, Elsevier, vol. 43(C), pages 58-85.
    17. Yu Shen & Di Gao & Di Bu & Lina Yan & Ping Chen, 2019. "CEO hometown ties and tax avoidance‐evidence from China's listed firms," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1549-1580, March.
    18. Papík, Mário & Papíková, Lenka, 2022. "Detecting accounting fraud in companies reporting under US GAAP through data mining," International Journal of Accounting Information Systems, Elsevier, vol. 45(C).
    19. John L. Campbell & Hsinchun Chen & Dan S. Dhaliwal & Hsin-min Lu & Logan B. Steele, 2014. "The information content of mandatory risk factor disclosures in corporate filings," Review of Accounting Studies, Springer, vol. 19(1), pages 396-455, March.
    20. Botosan, Christine A., 2004. "Discussion of a framework for the analysis of firm risk communication," The International Journal of Accounting, Elsevier, vol. 39(3), pages 289-295.
    21. Ibrahim, Awad Elsayed Awad & Hussainey, Khaled & Nawaz, Tasawar & Ntim, Collins & Elamer, Ahmed, 2022. "A systematic literature review on risk disclosure research: State-of-the-art and future research agenda," International Review of Financial Analysis, Elsevier, vol. 82(C).
    22. 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.
    23. Adrian Gepp & Kuldeep Kumar & Sukanto Bhattacharya, 2024. "Taking the hunch out of the crunch: A framework to improve variable selection in models to detect financial statement fraud," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(2), pages 1569-1588, June.
    24. Xiaoqian Zhu & Jianping Li & Yinghui Wang, 2024. "Are risk disclosures in financial reports informative? A text mining-based perspective," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    25. Liguori, Mariannunziata & Steccolini, Ileana, 2018. "The power of language in legitimating public-sector reforms: When politicians “talk” accounting," The British Accounting Review, Elsevier, vol. 50(2), pages 161-173.
    26. 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.
    27. Beyer, Anne & Cohen, Daniel A. & Lys, Thomas Z. & Walther, Beverly R., 2010. "The financial reporting environment: Review of the recent literature," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 296-343, December.
    28. Patricia M. Dechow & Weili Ge & Chad R. Larson & Richard G. Sloan, 2011. "Predicting Material Accounting Misstatements," Contemporary Accounting Research, John Wiley & Sons, vol. 28(1), pages 17-82, March.
    29. Feng Xiong & Yaping Zheng & Zhe An & Si Xu, 2021. "Does internal information quality impact corporate cash holdings? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 2151-2171, April.
    30. 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.
    31. Allen H. Huang & Jianghua Shen & Amy Y. Zang, 2022. "Correction to: The unintended benefit of the risk factor mandate of 2005," Review of Accounting Studies, Springer, vol. 27(4), pages 1356-1356, December.
    32. Duboisée de Ricquebourg, Alan & Maroun, Warren, 2023. "How do auditor rotations affect key audit matters? Archival evidence from South African audits," The British Accounting Review, Elsevier, vol. 55(2).
    33. Wei, Lu & Li, Guowen & Li, Jianping & Zhu, Xiaoqian, 2019. "Bank risk aggregation with forward-looking textual risk disclosures," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    34. Clinton Free, 2015. "Looking through the fraud triangle: a review and call for new directions," Meditari Accountancy Research, Emerald Group Publishing Limited, vol. 23(2), pages 175-196, August.
    35. Lang, Mark & Stice-Lawrence, Lorien, 2015. "Textual analysis and international financial reporting: Large sample evidence," Journal of Accounting and Economics, Elsevier, vol. 60(2), pages 110-135.
    36. Muhammad Nadeem, 2022. "Board Gender Diversity and Managerial Obfuscation: Evidence from the Readability of Narrative Disclosure in 10-K Reports," Journal of Business Ethics, Springer, vol. 179(1), pages 153-177, August.
    37. Beretta, Sergio & Bozzolan, Saverio, 2004. "A framework for the analysis of firm risk communication," The International Journal of Accounting, Elsevier, vol. 39(3), pages 265-288.
    38. Mark Cecchini & Haldun Aytug & Gary J. Koehler & Praveen Pathak, 2010. "Detecting Management Fraud in Public Companies," Management Science, INFORMS, vol. 56(7), pages 1146-1160, July.
    39. Michael E. Bradbury & Pei___Chi Kelly Hsiao & Tom Scott, 2020. "Summary annual reports: length, readability and content," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 2145-2165, September.
    40. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    41. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 58(1), pages 237-291, March.
    42. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    43. Yang Bao & Anindya Datta, 2014. "Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures," Management Science, INFORMS, vol. 60(6), pages 1371-1391, June.
    44. Matthew Grosse & Tom Scott & Zeting Zang, 2024. "Aligning disclosure requirements for managerial assessments of going concern risk: Initial evidence from New Zealand," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(2), pages 1525-1547, June.
    45. Rong Liu & Jujun Huang & Zhongju Zhang, 2023. "Tracking disclosure change trajectories for financial fraud detection," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 584-602, February.
    46. Tzu‐Ting Chiu & Yuyan Guan & Jeong‐Bon Kim, 2018. "The Effect of Risk Factor Disclosures on the Pricing of Credit Default Swaps," Contemporary Accounting Research, John Wiley & Sons, vol. 35(4), pages 2191-2224, December.
    47. Normah Omar & Zulaikha ‘Amirah Johari & Malcolm Smith, 2017. "Predicting fraudulent financial reporting using artificial neural network," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 24(2), pages 362-387, May.
    48. Beretta, Sergio & Bozzolan, Saverio, 2004. "Reply to: Discussions of "A framework for the analysis of firm risk communication"," The International Journal of Accounting, Elsevier, vol. 39(3), pages 303-305.
    49. Shaio Yan Huang & Chi-Chen Lin & An-An Chiu & David C. Yen, 2017. "Fraud detection using fraud triangle risk factors," Information Systems Frontiers, Springer, vol. 19(6), pages 1343-1356, December.
    50. repec:hal:pseose:hal-00812682 is not listed on IDEAS
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