بررسی تاثیر فشار محدودیت زمان، رفتار ناکارآمد حسابرس، تشخیص تقلب و نقش فناوری اطلاعات در فرآیند حسابرسی (مطالعه ی موردی بانک پارسیان)

•   آرشیو : نسخه تابستان 1399-جلد دوم
•   نوع مقاله : پژوهشی
•   کد پذیرش : 11944
• نویسنده/گان : وحید محمد پور ورقه، مجید مرادی، فرزین خوشکار
•   کلید واژه : محدودیت زمان، پیچیدگی وظیفه، فناوری اطلاعات، رفتار حسابرسی، تشخیص تقلب.
•   Abstract :
  Today, auditors are facing a more difficult task than ever before as banks grow, and this responsibility continues to grow positively, as people have more access to and awareness of banking services. Auditors will have far more ethical decisions and behaviors when they are under time pressure, legal requirements, strict oversight by supervisors and owners. In the present study, we intend to investigate the impact of time constraint pressure, inefficient auditor behavior, fraud detection, and the role of information technology in the audit process (Parsian Bank Case Study). The type of applied research work and the research method used in this study is a descriptive survey. The statistical population of this study includes all Parsian Bank auditors, which are about 60 people. Due to the limited population of the statistical population we do not have sampling. In this study, library and questionnaire methods with 25 questions with face validity and reliability of 0.814 were used and finally analyzed by two software SPSS and lisrel. Was.
•   key words :
  Time constraint, task complexity, information technology, audit behavior, fraud detection
•   مراجع :
  [1] ادهمی، کریم و حسین خواجوی، (1390)، تقلب و حسابرسی تقلب، فصلنامه حسابدار رسمی، سال هشتم، شماره 15، ضض 33-39.
  [2] برزیده، فرخ و خیراللهی، مرشید (1390)، مسئولیت پاسخگویی، فشار زمانی و کتمان شواهد حسابرسی. دانش حسابرسی: سـال یازدهم، شـماره 45 ،از صفحه 4 تا صفحه 27. 3.
  [3] جانی، اکبر و محمود محمودزاده (1387)، "نقش فناوری اطلاعات و ارتباطات در رشد اقتصادی ایران (رهیافت حسابداری رشد)"، فصلنامه پژوهشنامه اقتصادی، شماره پیاپی 29 ،صص 107-75.
  [4] رهنمای رودپشتی ، فریدون، 1391، داده كاوي و كشف تقلب هاي مالي، فصلنامه علمي پژوهشي دانش حسابداري و حسابرسي مديريت سال اول / شماره سوم/ پائيز 1391.
  [5] سيراني،محمد و خواجوي، شكراله و نوشادي، ميثم ،(1388)، تاثير تجربه و پيچيدگي موضوعات حسابرسي بر قضاوت حسابرس، بررسي هاي حسابداري و حسابرسي، دوره 16 ، شماره 55 ، از صفحه 35 تا 50، 5.
  [6] عرب مازار یزدی، محمد و سحر سپاسی، (1389) ، کاربرد شبکه های عصبی مصنوعی در حسابرسی، مجله دانش حسابرسی، سال دهم، شماره 2، صفحات 58-40.
  [7] علی خان، محمدحسين و مران جوری، مظفر ، (1390)، "بررسي وجود محافظه كاري درگزارشگري مالي شركت هاي پذيرفته شده در بورس اوراق بهادار "،تهران مجله پيشرفت هاي حسابداري دانشگاه شيراز، دوره دوم، شماره اول، پياپي58.3: 119-85.
  [8] محمودزاده، محمود، اسدی، فرخنده، (1386) ، آثار فناوری اطلاعات و ارتباطات بر رشد بهره وری نیروی کار در اقتصاد ایران"، فصلنامه پژوهشنامه بازرگانی، شماره 43 ،صص 184-153.
  [9] محمودی، مجید، محمودی، الهه، (1390)، تأثیر فناوری اطلاعات و ارتباطات روی اشتغال بخش خدمات در ایران، فصلنامه پژوهش ها و سیاست های اقتصادی سال نوزدهم، شماره 58 ،تابستان 1390 ،صفحات 236 – 215.
  [10] مهدوی، غلامحسین و سامان محمدی، (1389) ، کاربرد سامانه های خبره در حسابرسی، مجله دانش حسابرسی، سال دهم، شماره 3، صفحات 22-38.
  [11] مهدوی، غلامحسین و محمدرضا بهمنش، (1383) ، (طراحی مدل پیش بینی قیمت سهام)، شرکت های سرمایه گذاری با استفاده از شبکه عصبی (تحقیق موردی: شرکت سرمایه گذاری البرز) ، فصلنامه پژوهش نامه اقتصادی، شماره 19 ، صفحات 211-233.
  [12] مهرانی، ساسان و آمنه بذرافشان، (1382) " ،تئوري اخلاقی و تاثیر فشار بودجه زمانی بر رفتار حسابرسان مستقل"، بررسی هاي حسابداري و حسابرسی، شماره 32 ،ص 43-6.
  [13] مهرانی، کاوه و رضا حصارزاده (1387)، مروری بر تئوری ها و مدل های کشف تقلب، فصل نامه دانش و پژوهش حسابداری، سال چهارم، شماره 15 ، صفحات 60-65.
  [14] هوشمند، عبدالحميد. (1386) بررسي تأثير استانداردهاي ملي حسابرسي بر كيفيت اظهارنظر حسابرسان، پاياننامه كارشناسي ارشد حسابداري، دانشگاه شيراز.
  [15] Alissa, W, Capkun, V, Jeanjean, T and Suca, N (2014), “An Empirical Investigation of the Impact of Audit and Auditor Characteristics on Auditor Performance”. Accounting, Organizations and Society, Forthcoming. ssrn. June 2014.
  [16] Anya, A. O. (2003). Corporate governance as an effective tool for combating financial and economic crimes. The Nigerian Banker, October – December, 32 – 36.
  [17] Association of Certified Fraud Examiners (ACFE) (2012). Report to the Nation on Occupational Fraud and Abuse. Austin, TX: ACFE.
  [18] Axelsson, S. (2000). The Base-Rate Fallacy and the Difficulty of Intrusion Detection. ACM Trans .Information and System Security. 3(3): 186-205. Kohonen, T. (1990). The self-organizing map. In Proceedings of the IEEE, 78 (9): 1464-1480.
  [19] Bao, D , Files, R and Radhakrishnan, S.(2015), “Industry-Specialist Audit Fee Premium and Financial Statement Complexity”. Electronic copy available at: http://ssrn.com/ abstract=2648745.
  [20] Barlaup, K.; Dronen, H. I.; and I. Stuart (2009). “Restoring Trust in Auditing: Ethical Discernment and the Adelphia Scandal.” Managerial Auditing Journal, Vol. 24, No. 2, pp. 183-203.
  [21] Bassey Ina, IBOR, 2016,an empirical investigation of the human resoureces nexus to frauds in the Nigerian banking sector, International Journal of Scientific and Research Publications, Volume 6, Issue 6, June 2016 231 ISSN 2250-3153.
  [22] Bishop, T. J. F. and F. E. Hydoski (2009). Corporate Resiliency: Managing the Growing Risk of Fraud and Corruption, 1st Edition, Hoboken, New Jersey: John Wiley & Sons.
  [23] Busta, B. and R. Weinberg (1998). “Using Benford’s Law and Neural Networks as An Review Procedure”, Managerial Auditing Journal, Vol. 13, pp. 356-366.
  [24] Chi, W., Huang, H. (2005), «Discretionary accruals, audit firm tenure and auditpartner tenure: empirical evidence from Taiwan», Journal of Contemporary Accounting and Economics, Vol. 1 No. 1, pp: 65-92.
  [25] Christensen, B. E., S. M. Glover, T. C. Omer, and M. K. Shelley (2014), “Understanding audit quality: Insights from audit professionals and investors”. Working paper, Texas A&M University, Brigham Young University, and the University of Nebraska–Lincoln.
  [26] Dal Pozzolo, A., Caelen, O., Le Borgne, Y. A., Waterschoot, S. & Bontempi, G. (2014). Learned lessons in credit card fraud detection from a practitioner perspective. Expert Systems with Applications, 41(10): 4915-4928.
  [27] Dorminey, J. W.; Fleming, A. S.; Kranacher, M.; and R. A. Riley (2012). “Financial Fraud: A New Prespective to an Old Problem.” The CPA Journal, Vol. 8, pp. 61-65.
  [28] Dorminey, J. W.; Fleming, A. S.; Kranacher, M.; and R. A. Riley (2012). “Financial Fraud: A New Prespective to an Old Problem.” The CPA Journal, Vol. 8, pp. 61-65.
  [29] Gaganis, C.; Pasiouras, F.; and M. Doumpos (2007). “Probabilistic Neural Networks for the Identification of Qualified Audit Opinions” Expert Systems with Applications, Vol. 32, pp. 114-124.
  [30] Glover, S.M, Hansen, J.C and Seidel, T.A (2015), “The Effect of Deadline Imposed Time Pressure on Audit Quality”. Ssrn. February 6, 2015.
  [31] Halvaiee, N.S. & Akbari, M.K. (2014). A novel model for credit card fraud detection using Artificial Immune Systems. Applied soft computing, 24: 40- 49.
  [32] Hyatt , T.A and Taylor , M. H (2013) , “ The Effects of Time Budget Pressure and Intentionality on Audit Supervisors’ Response to Audit Staff False Sign-Off “ , International Journal of Auditing, Vol. 17, Issue 1, pp. 38-53 . 18.
  [33] Idolor, E. J. (2010). Bank frauds in Nigeria: underlying causes, effects and possible solution. African Journal of Accounting, Economics, Finance and Banking Research, 6 (6), 62 – 80.
  [34] Ikpefan, O. A. & Odularu, G.O. (2007). Using money laundering Act as a tool for monitoring deposits and frauds in the Nigerian banking industry: An empirical approach. The Nigerian Banker, April – June.
  [35] INDUSTRY, International Academic Publishing Group. International Journal of Academic Research in Management and Business| vol:1,No:2,2016 Page 1.
  [36] Johnson-Moreno, H. and M. Hayes. 2003. To your health. Journal of Accountancy 196 (3): 65-68.
  [37] Kedia, S., Philippon, T. ,(2009), "The Economics of Fraudulent Accounting", The Review of Financial Studies, Vol. 22 (6),PP. 2169-2199.
  [38] Kelley. T., and L. Margheim. 1990. The impact oftime budget pressure, personality, and leadership variables on dysfunctional auditor behavior. Auditing: A Journal of Practice and Theory 9 (Spring): 21-41.
  [39] Kobbeltvedt, T., Brun, W. and Laberg, J.C. (2005), “Cognitive processes in planning and judgments under sleep deprivation and time pressure”, Organizational Behaviour and Human Decision Processes, Vol. 98, pp. 1-14
  [40] Kranachar, M. (2013). “The Role of Research in the Prevention of Fraud”, CPA Journal, Vol. 9, p. 80.
  [41] Kroll (2014). 2013/2014 Global Fraud Report. New York: Kroll/Economist Intelligence Unit.
  [42] Malone, C.F., and R.W. Roberts. (1996). Factors Associated with the Incidence of Reduced Audit Quality Behaviors. Auditing: A Journal of Practice and Theory 15 (2).
  [43] Minegishi, T. & Niimi, A. (2011). Proposal of Credit Card Fraudulent Use Detection by Online-type Decision Tree Construction and Verification of Generality. International Journal for Information Security Research, 1(4): 229-235.
  [44] Mishra, J. S., Panda, S. & Mishra, A. K. (2013). A Novel Approach for Credit Card Fraud Detection Targeting the Indian Market. International Journal of Computer Science Issues, 10(3): 172-179.
  [45] Nasiri, N. & Minayi, B. (2011). Data mining methods for credit card fraud detection. 1st International conference on E-Citizen & Cellphone. Tehran: Frb 28-29. (in Persian)
  [46] Nasiri, N. & Minayi, B. (2011). Data mining methods for credit card fraud detection. 1st International conference on E-Citizen & Cellphone. Tehran: Frb 28-29. (in Persian)
  [47] Ogunleye, G. A. (2010). Perspectives on the Nigerian Financial safety-net: An NDIC Book. Abuja: Nigeria Deposit Insurance Corporation.
  [48] Peytcheva, M. (2008). Accountability, Reputation costs, and opportunistic auditor behavior. University of New jersey
  [49] Pierce, B.J., and B. Sweeney. (2006). Perceived adverse consequences of quality threatening behavior in audit firms. International Journal of Auditing 10:19-39.
  [50] Qibei, L. & Chunhua, J. (2011). Research on Credit Card Fraud Detection Model Based on Class Weighted Support Vector Machine. Journal of Convergence Information Technology, 6(1): 62-68.
  [51] Raymond A. Ezejiofor,Nwakoby, Nkiru Peace, Okoye, F. N. Jane ,2016, IMPACT OF FORENSIC ACCOUNTING ON COMBATING FRAUD IN NIGERIAN BANKING
  [52] Robertson, J.C.( 2007). Staff Auditor Reporting Decisions Under Time Deadline Pressure. Managerial Auditing Journal 22 (4):340-353.
  [53] Schubert, J. (2015). Social control: definition, theory and examples. Retrieved from study.com/academy/lesson/social-control-definition-theory-examples.html
  [54] Srivastava, A., Kundu, A., Sural, S. & Majumdar, A. K. (2008). Credit Card Fraud Detection Using Hidden Markov Model. IEEE transactions on dependable and secure computing, 5(1): 37-48.
  [55] Stuart , I and Prawitt , D.F (2004) , “ The Influence of Audit Structure on Auditors’ Performance in High and Low Complexity Task Settings.
  [56] Tan, B.S. (2015), “The Value of Audit and the Economic History of Market. International Journal of Economics and Accounting”, Forthcoming. March 16, 2015.
  [57] Titman S, Trueman B.(1986) «Information quality and the valuation of new issues». Journal of Accounting & Economics 1986; 8: 159621-.
  [58] Topi, H., Valacich, J.S. and Hoffer, J.A. (2005), “The effects of task complexity and time availability limitations on human performance in database query tasks”, International Journal of Human-Computer Studies, Vol. 62 No. 3, pp. 349-79.
  [59] Usenideh, E. A. (2014). The linkage between financial infrastructure, macro-prudential policies and financial crisis: Its (financial crisis) adverse impact on financial stability and international business. The Nigerian Banker, January – March, 11 – 25.
  [60] Vatz, B. (2003). "The Conservatism Principle and The Asymmetric Timeliness of Earnings", Journal Of Accounting and Economics, PP. 24 – 337.
  [61] Vatz, B. (2010). “Earnings management and market liquidity”. Rev Quant Finan Acc.10. 9.
  [62] Vosough, M., Taghavifard, M.T. & Alborzi, M. (2015). Bank card fraud detection using artificial neural network. Journal of Information Technology Management, 6(4): 721-746. (in Persian)
  [63] Whitrow, C., Hand, D.J., Juszczak, P. & Weston, D. (2008). Transaction aggregation as a strategy for credit card fraud detection. Data mining and knowledge discovery, 18(1): 30-55.
  [64] Zareapoor, M. & Shamsolmoali, P. (2015). Application of credit card fraud detection: based on bagging ensemble classifier. Procedia computer science, 48: 679-685.
  [65] Zareapoor, M., Seeja, K.R. & Alam, M. A.(2012). Analysis of credit card fraud detection techniques: based in certain design criteria. International journal of computer applications, 52(3): 35-42.
  [66] Zaslavsky, V. & Strizhak, A. (2006). Credit card fraud detection using self organizing maps. International Journal of Information & Security, 18: 48-63.
•  صفحات : 14-31
•   دانلود فایل ( 972.55 KB )