سنجش اعتبار حسابرسان با استفاده از شبکه عصبی مصنوعی

محورهای موضوعی : حسابداری و حسابرسی

عسل بخشیان ¹ , فروغ حیرانی ² , اکرم تفتیان ³

1 - گروه حسابداری، واحد یزد ،دانشگاه آزاد اسلامی، یزد، ایران.
2 - گروه حسابداری، واحد یزد ،دانشگاه آزاد اسلامی، یزد، ایران.
3 - گروه حسابداری، واحد یزد ،دانشگاه آزاد اسلامی، یزد، ایران.

تاریخ دریافت : 1402/06/26 تاریخ پذیرش : 1402/10/20 تاریخ انتشار : 1402/11/07

کلید واژه: اعتبار گزارش حسابرس, الگوریتم بهینه‌سازی علف‌های هرز, الگوریتم بهینه‌سازی توده ذرات, سنجش اعتبار حسابرسان,

چکیده مقاله :

هدف: میزان ارزش‌افزوده اطمینان به ارتباطات بین حسابرسی شونده و مخاطبانش به طور مستقیم با اعتبار حسابرس مرتبط است؛ بنابراین اعتبار حسابرسان باتوجه‌به اهمیت صورت‌های مالی حسابرسی شده در تسهیل معاملات بازار سرمایه در اولویت می‌باشد. هدف پژوهش سنجش اعتبار حسابرسان با استفاده از شبکه عصبی مصنوعی می‌باشد. روش‌شناسی پژوهش: در ابتدا با بکارگیری روش نظریه گرندد، مولفه های پژوهش شناسایی شدند و بااستفاده از تحلیل عاملی به تجزیه‌وتحلیل سوالات پژوهش پرداخته شد و مدل نهایی سنجش اعتبار حسابرسان ارائه، و با استفاده از نرم افزار متلب سنجش اعتبار حسابرسان صورت پذیرفت. این پژوهش در سال 1401 صورت پذیرفته است. یافته‌ها: نتایج نشان داد مولفه‌های بررسی استقلال، پذیرش یا ادامه کار؛ پرونده مکاتباتی؛ پرونده دائمی؛ شناخت واحد مورد رسیدگی و محیط آن شامل کنترل‌های داخلی؛ آزمون‌های محتوا؛ برنامه‌ریزی، کنترل و سرپرستی کار؛ چک‌لیست‌ها و گزارش‌ها؛ نحوه اجرای وظایف مدیر دوم؛ ارزیابی کلی پرونده‌های حسابرسی؛ وضعیت کلی مؤسسه حسابرسی؛ وضعیت منابع انسانی مؤسسه حسابرسی؛ کارکردهای مؤسسه حسابرسی؛ رعایت قوانین و مقررات حرفه حسابرسی و وضعیت ظاهری مؤسسه حسابرسی بر سنجش اعتبار حسابرسان تأثیر دارند. الگوریتم بهینه‌سازی علف‌های هرز قدرت بالاتری نسبت به الگوریتم بهینه‌سازی توده ذرات جهت پیش‌بینی سنجش اعتبار حسابرسان دارد. ‏ اصالت / ارزش‌افزوده علمی: به استناد یافته‌های پژوهش حاضر، فعالان حرفه حسابرسی خصوصاً جامعه حسابداران رسمی ایران که مسئولیت سنجش اعتبار حسابرسان را بر عهده دارد، باید عوامل برشمرده شده در این پژوهش که از نظر خبرگان و فعالین حرفه بر سنجش اعتبار حسابرسان تأثیرگذار هستند را موردتوجه قرار دهند. ‏

چکیده انگلیسی:

Purpose: The credibility of auditors is directly linked to the added value of confidence in communication between the auditee and their audience. Consequently, the credibility of auditors takes precedence due to the significance of audited financial statements in facilitating transactions in capital markets. This research aims to measure auditors' credibility using artificial neural networks. Methodology: Initially, research variables were identified using grounded theory, and factor analysis was employed to analyze research questions. The final model for measuring auditors' credibility was then presented, and MATLAB software was utilized to measure auditors' credibility. This research was conducted in the year 1401 (Solar Hijri calendar, equivalent to 2022-2023 in the Gregorian calendar). Findings: The results revealed that various factors influence the evaluation of auditors' credibility, including examining independence, acceptance or continuation of work, correspondence file, permanent file, understanding the unit under scrutiny and its environment (including internal controls), content tests, work planning, control and supervision, checklists and reports, the execution of duties by the second manager, overall assessment of audit files, the general status of the audit institution, human resource status within the audit institution, functions of the audit institution, compliance with auditing profession rules and regulations, and the external appearance of the audit institution. Conclusion: The weed optimization algorithm outperforms the particle swarm optimization algorithm in predicting auditors' credibility. Based on the findings of this study, stakeholders in the auditing profession, especially the Iranian Institute of Certified Accountants responsible for assessing auditors' credibility, should pay attention to the identified factors that experts and professionals believe to have an impact on evaluating auditors' credibility.

منابع و مأخذ:

Alizadeh, H., Zanjirdar, M., & Haji, G. A. (2023). Ability of Machine Learning Algorithms and Artificial Neural Networks in Predicting Accounting Profit Information Content Before Announcing. Advances in Finance and Investment, 4(2), 1-30. [In Persian]

Andersson, O., Holm, H. J., Tyran, J. R., & Wengström, E. (2013). Risking other people's money: Experimental evidence on bonus schemes, competition, and altruism (No. 989). IFN Working Paper.

Ball, R., Jayaraman, S., & Shivakumar, L. (2012). Audited financial reporting and voluntary disclosure as complements: A test of the confirmation hypothesis. Journal of accounting and economics, 53(1-2), 136-166.

Billings, B. A., Gao, X., & Jia, Y. (2014). CEO and CFO equity incentives and the pricing of audit services. Auditing: A Journal of Practice & Theory, 33(2), 1-25.

Bryan, D. B., & Mason, T. W. (2017). Executive tournament incentives and audit fees. Advances in accounting, 37, 30-45.

Chen, Y., Gul, F. A., Veeraraghavan, M., & Zolotoy, L. (2015). Executive equity risk-taking incentives and audit pricing. The Accounting Review, 90(6), 2205-2234.

Conrads, J., Irlenbusch, B., Rilke, R. M., Schielke, A., & Walkowitz, G. (2014). Honesty in tournaments. Economics Letters, 123(1), 90-93.

DeAngelo, L. E. (1981). Auditor independence,‘low balling’, and disclosure regulation. Journal of accounting and Economics, 3(2), 113-127.

Dopuch, N., & Simunic, D. (1980). The nature of competition in the auditing profession: a descriptive and normative view. Regulation and the accounting profession, 34(2), 283-289.

Friedrich, C., & Quick, R. (2023). Do non-audit service failures impair auditor reputation? An analysis of KPMG advisory service scandals in Germany. Critical Perspectives on Accounting, 102550.

Ghadami, R., Rezaei, F., Khodaparast, A. (2022). The Role of Financial Reporting Quality and the Credibility of the Audit Firm in the Relationship between Managerial Overconfidence and Audit Fees. Presented at the First National Conference on Applied Research in Modern Management and Accounting Sciences, Alborz. [In Persian]

Gunn, J. L., Kawada, B. S., & Michas, P. N. (2019). Audit market concentration, audit fees, and audit quality: A cross-country analysis of complex audit clients. Journal of Accounting and Public Policy, 38(6), 106693.

Habib, A., & Bhuiyan, M. B. U. (2011). Audit firm industry specialization and the audit report lag. Journal of international accounting, Auditing and taxation, 20(1), 32-44.

Hassas Yeganeh, Y., & Ghanbarian, R. (2006). Audit Quality from Theoretical and Empirical Perspectives. Official Accountant, (8-9), 4-39. [ In Persian]

Hong, P. K., & Hwang, S. (2018). Fair value disclosure of pension plan assets and audit fees. Advances in accounting, 41, 88-96.

Kannan, Y. H., Skantz, T. R., & Higgs, J. L. (2014). The impact of CEO and CFO equity incentives on audit scope and perceived risks as revealed through audit fees. Auditing: A Journal of Practice & Theory, 33(2), 111-139.

Karimabadi, M., Jahangirnia, H., Hajiha, Z., & GholamiJamkarani, R. (2022). Evaluating the Criteria of Professional Conduct in the Independent Audit Quality Profession. Financial Accounting and Auditing Research, 14(55), 79-101. [In Persian]

Khalaj Tehrani., M., Haji Ha, Z. (2018). Examining the Relationship between Auditor Credibility and Capital with Income in the Banking Sector. In Proceedings of the First International Conference on New Approaches in Business and Accounting Management with an Emphasis on Value Creation and Resilient Economy. Tehran. [ In Persian]

Krishnan, G. V., Patatoukas, P. N., & Wang, A. Y. (2019). Customer-base concentration: Implications for audit pricing and quality. Journal of Management Accounting Research, 31(1), 129-152.

Mansourian, S., Farhadtouski, O. (2021). Examining the Relationship Between Audit Firm Fees, Audit Firm Reputation, and Audit Quality. Presented at the Seventh International Conference on Management, Accounting, and Economic Development. [In Persian]

Mashhoor Alhosseini, S. M. R., H, M., Ravanan, S. (2018). Audit Objectives (Credibility or Fraud Detection) from the Perspectives of Auditors and Users. New Research in Management and Accounting Quarterly, 4(11). 583-598. [In Persian]

Mohammadnejad, M. (2017). The Relationship Between Auditor Reputation, Earnings Management, and Capital in Interim Financial Statements in Banks and Financial Institutions Listed on the Tehran Stock Exchange. Master's Thesis, Kurdistan University. [In Persian]

Nasle Mosavi, S. H., Enayatpour Shiadeh, E., & Azinfar, A. (2022). Effect of Audit Quality on the Relationship Between Audit committee characteristics and financial reporting quality. Advances in Finance and Investment, 2(5), 23-44. [In Persian]

Salahinejad, M., & Saadat, S. (2014). The effect of audit credibility in attracting grants in non-profit organizations and municipalities. Journal of Management Accounting and Auditing Knowledge, 3(9), 79-90. [In Persian]

Sathiyamurthi, K., Devi, K., & Nirmal Raj, A. (2021). Computational analysis and intelligence for mediating effect of investment knowledge on investment intention and investment behaviors. Materials Today: Proceedings, 40, 1-5.

Wallace, R. O., Naser, K., & Mora, A. (1994). The relationship between the comprehensiveness of corporate annual reports and firm characteristics in Spain. Accounting and business research, 25(97), 41-53.

Yang, S., Lee, W. J., Lim, Y., & Cheong, H. Y. (2021). Audit firm operating leverage and pricing strategy: Evidence from lowballing in audit industry. Journal of Contemporary Accounting & Economics, 17(2), 100254.