English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113822/144841 (79%)
Visitors : 51790094      Online Users : 508
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/36946
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/36946


    Title: 財務報表舞弊之探索研究
    Exploring financial reporting fraud
    Authors: 徐國英
    Contributors: 蔡瑞煌
    馬秀如

    徐國英
    Keywords: 財務報表舞弊
    成長階層式自我組織圖
    知識擷取
    Financial Reporting Fraud
    Growing Hierarchical Self-Organizing Map (GHSOM)
    Knowledge Extraction
    Date: 2007
    Issue Date: 2009-09-18 20:14:38 (UTC+8)
    Abstract: Financial reporting fraud leads to not only significant investment risks for external stockholders, but also financial crises for the capital market. Although the issue of fraudulent financial reporting has drawn much attention, relevant research is much less than issues of predicting financial distress or bankruptcy. Furthermore, one purpose of exploring the financial reporting fraud with various forms is to obtain a better understand of the corporate through investigating its financial and corporate governance indicators. This study addresses the challenge with proposing an approach with the following four phases: (1) to identify a set of financial and corporate governance indicators that are significantly correlated with the financial reporting fraud; (2) to use the Growing Hierarchical Self-Organizing Map (GHSOM) to cluster the normal and fraud listed corporate data; (3) to extract knowledge about the financial reporting fraud through observing the hierarchical relationship displayed in the trained GHSOM; and (4) to make the justification of the extracted knowledge. The proposed approach is feasible because researchers claim that the GHSOM can discover the hidden hierarchical relationship from data with high dimensionality.
    Reference: Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
    American Institute of Certified Public Accountants[AICPA]. (2002). Statement on Auditing Standards No. 99 : Consideration of Fraud in a Financial Statement Audit [Electronic Version]. Retrieved November 20, 2007 from http://www.aicpa.org/download/members/div/auditstd/AU-00316.PDF.
    Association of Certified Fraud Examiners[ACFE]. (2006). Report to the nation on occupational fraud & abuse [Electronic Version]. Retrieved November 20, 2007 from http://www.acfe.com/documents/2006-rttn.pdf.
    Beasley, M. S. (1996). An Empirical Analysis of the Relation Between the Board of Director Composition and Financial Statement Fraud. Accounting Review, 71(4), 443-465.
    Beasley, M. S., Carcello, J. V., & Hermanson, D. R. (1999). Fraudulent financial reporting: 1987-1997 an analysis of U.S. public companies [Electronic Version]. Retrieved November 20, 2007 from http://www.coso.org/publications/FFR_1987_1997.PDF.
    Beasley, M. S., Carcello, J. V., Hermanson, D. R., & Lapides, P. D. (2000). Fraudulent Financial Reporting: Consideration of Industry Traits and Corporate Governance Mechanisms. Accounting Horizons, 14(4), 441-454.
    Bell, T. B., & Carcello, J. V. (2000). A Decision Aid for Assessing the Likelihood of Fraudulent Financial Reporting. Auditing, 19(1), 169-184.
    Berle, A. A., & Means, G. C. (1932). The modern corporation and private property (Rev. ed.). New York: Harcourt, Brace & World.
    Bonner, S. E., Palmrose, Z.-V., & Young, S. M. (1998). Fraud type and auditor litigation: An analysis of SEC accounting and auditing enforcement releases. Accounting Review, 73(4), 503-532.
    Claessens, S., Djankov, S., & Lang, L. H. P. (2000). The separation of ownership and control in East Asian Corporations. Journal of Financial Economics, 58(1-2), 81-112.
    Davia, H. R. (2000). Fraud 101:techniques and strategies for detection. New York: John Wiley & Sons.
    Dechow, P. M., Ge, W., Larson, C. R., & Sloan, R. G. (2007). Predicting Material Accounting Manipulations [Electronic Version]. Retrieved December 13, 2007 from http://ssrn.com/abstract=997483.
    Dechow, P. M., & Skinner, D. J. (2000). Earnings Management: Reconciling the Views of Accounting Academics, Practitioners, and Regulators. Accounting Horizons, 14(2), 235-250.
    Dittenbach, M., Merkl, D., & Rauber, A. (2000). The Growing Hierarchical Self-Organizing Map. Paper presented at the Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000. IJCNN 2000.
    Dittenbach, M., Rauber, A., & Merkl, D. (2002). Uncovering hierarchical structure in data using the growing hierarchical self-organizing map. Neurocomputing, 48(1-4), 199-216.
    Fama, E. F., & Jensen, M. C. (1983). Separation of Ownership and Control. Journal of Law and Economics, 26(2), 25.
    Fanning, K. M., & Cogger, K. O. (1998). Neural network detection of management fraud using published financial data. International Journal of Intelligent Systems in Accounting, Finance & Management, 7(1), 21-41.
    Farber, D. B. (2005). Restoring trust after fraud: does corporate governance matter? Accounting Review, 80(2), 539-561.
    Green, B. P. (1997). Assessing the risk of management fraud through neural network technology. Auditing, 16(1), 14.
    Hoogs, B., Kiehl, T., Lacomb, C., & Senturk, D. (2007). A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud. Intelligent Systems in Accounting Finance and Management, 15(1/2), 41-56.
    Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data Mining techniques for the detection of fraudulent financial statements. Expert Systems with Applications, 32(4), 995-1003.
    Kiviluoto, K. (1998). Predicting bankruptcies with the self-organizing map. Neurocomputing, 21(1-3), 191-201.
    Kiviluoto, K., & Bergius, P. (1998a). Maps for Analyzing Failures of Small and Medium-sized Enterprises. In G. Deboeck & T. Kohonen (Eds.), Visual Explorations in Finance with Self-Organizing Maps (pp. 59-71). Berlin;New York: Springer.
    Kiviluoto, K., & Bergius, P. (1998b). Two-level self-organizing maps for analysis of financial statements. Paper presented at the IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on Neural Networks Proceedings, 1998.
    Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43, 59-69.
    La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (1999). Corporate ownership around the world. Journal of Finance, 54(2), 471.
    Lee, T. S., & Yeh, Y. H. (2004). Corporate Governance and Financial Distress: evidence from Taiwan. Corporate Governance: An International Review, 378-388.
    Loebbecke, J. K., Eining, M. M., & Willingham, J. J. (1989). Auditors` experience with material irregularities: frequency, nature, and detectability. Auditing, 9(1), 1-28.
    Magdi, I., & Nadereh, C. (1999). Corporate Governance: A Framework for Implementation-Overview [Electronic Version]. Retrieved April 2, 2008 from http://www.systemiclogic.net/artifacts/PUB/governance/gcgfbooklet.pdf.
    Monks, R. A. G., & Minow, N. (1995). Corporate Governance. Cambridge, Massachusetts: Blackwell Publishers.
    Organization for Economic Co-operation and Development. (2004). Principles of Corporate Governance [Electronic Version]. Retrieved November 20, 2007 from http://www.oecd.org/dataoecd/32/18/31557724.pdf.
    Persons, O. S. (1995). Using financial statement data to identify factors associated with fraudulent financial reporting. Journal of Applied Business Research, 11(3), 38-46.
    Rauber, A., Merkl, D., & Dittenbach, M. (2002). The Growing Hierarchical Self-Organizing Map:Exploratory Analysis of High-Dimensional Data. IEEE Transactions on Neural Networks, 13(6), 1331-1341.
    Rezaee, Z. (2002). Financial statement fraud: prevention and detection. New York: John Wiley & Sons.
    Schilit, H. M. (2002). Financial shenanigans: how to detect accounting gimmicks & fraud in financial reports (2nd ed.). New York: McGraw-Hill.
    Securities and Futures Investors Protection Center[SFIPC]. (2007). Annual Report 2007 [Electronic Version], 51. Retrieved July 1, 2008 from http://220.130.32.146/webdata/2007年報.pdf.
    Shih, J.-Y., Chang, Y.-J., & Chen, W.-H. (2008). Using GHSOM to construct legal maps for Taiwan’s securities and futures markets. Expert Systems With Applications, 34(2), 850-858.
    Stice, J. D. (1991). Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. Accounting Review, 66(3), 516.
    Summers, S. L., & Sweeney, J. T. (1998). Fraudulently Misstated Financial Statements and Insider Trading: An Empirical Analysis. Accounting Review, 73(1), 131.
    Tipgos, M. A. (2002). Why management fraud is unstoppable. CPA Journal, 72(12), 34-41.
    Virdhagriswaran, S., & Dakin, G. (2006). Camouflaged fraud detection in domains with complex relationships. Paper presented at the Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining.
    Yeh, Y. H., Lee, T. S., & Woidtke, T. (2001). Family Control and Corporate Governance: Evidence from Taiwan. International Review of Finance, 2(1/2), 21.
    周文賢. (民91). 多變量統計分析: SAS/STAT使用方法. 台北市: 智勝文化.
    柯承恩. (民89). 我國公司監理體系之問題與改進建議(上). 會計研究月刊, 173, 75-81.
    馬秀如. (民95). 會計師揭發舞弊之責任:審計準則公報第43號導讀. 會計研究月刊, 253, 44-61.
    康榮寶, 陳美娥, & 羅吉台. (民92). 以財務預警模式強化公司治理價值. 會計研究月刊, 212, 105-111.
    黃俊英. (民89). 多變量分析. 台北市: 中國經濟企業研究所.
    葉銀華. (民94). 蒸發的股王 : 領先發現地雷危機. 臺北市: 商智文化.
    蔡瑞煌. (民84). 類神經網路概論. 台北市: 三民書局.
    Description: 碩士
    國立政治大學
    資訊管理研究所
    95356022
    96
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095356022
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    602201.pdf46KbAdobe PDF2866View/Open
    602202.pdf91KbAdobe PDF2734View/Open
    602203.pdf14KbAdobe PDF2654View/Open
    602204.pdf166KbAdobe PDF2693View/Open
    602205.pdf217KbAdobe PDF21442View/Open
    602206.pdf386KbAdobe PDF26418View/Open
    602207.pdf349KbAdobe PDF21185View/Open
    602208.pdf435KbAdobe PDF2902View/Open
    602209.pdf261KbAdobe PDF2849View/Open
    602210.pdf210KbAdobe PDF21302View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback