این مقاله علمی پژوهشی (ISI) به زبان انگلیسی از نشریه الزویر مربوط به سال ۲۰۲۱ دارای ۱۵ صفحه انگلیسی با فرمت PDF می باشد در ادامه این صفحه لینک دانلود رایگان مقاله انگلیسی و بخشی از ترجمه فارسی مقاله موجود می باشد.
کد محصول: H715
سال نشر: ۲۰۲۱
نام ناشر (پایگاه داده): الزویر
نام مجله: International Journal of Accounting Information Systems
نوع مقاله: علمی پژوهشی (Research articles)
تعداد صفحه انگلیسی: ۱۵ صفحه PDF
عنوان کامل فارسی:
مقاله انگلیسی ۲۰۲۱ : گنجاندن “فرآیند کاوی” در حسابرسی صورت های مالی
عنوان کامل انگلیسی:
Embedding process mining into financial statement audits
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The audit of financial statements is a complex and highly specialized process. Digitalization and the increasing automation of transaction processing create new challenges for auditors who carry out those audits. New data analysis techniques offer the opportunity to improve the auditing of financial statements and to overcome the limitations of traditional audit procedures when faced with increasingly large amounts of financially relevant transactions that are processed automatically or semi-automatically by computer systems. This study discusses process mining as a novel data analysis technique which has been receiving increased attention in the audit practice. Process mining makes it possible to analyse business processes in an automated manner. This study investigates how process mining can be integrated into contemporary audits by reviewing the relevant audit standards and incorporating the results from a field study. It demonstrates the feasibility of embodying process mining within financial statement audits in accordance with contemporary audit standards and generally accepted audit practices. Implementation of process mining increases the reliability of the audit conclusions and improves the robustness of audit evidence by replacing manual audit procedures. Process mining as novel data mining technique provides auditors the means to keep pace with current technological developments and challenges.
Keywords: Process mining, Data analytics, Audit of financial statements, Big data, Data science, Business intelligence, Business process modelling, Enterprise resource planning systems ,Field study
This study concerns the application of data science in the profession of auditing and explores how the technique of process mining can conceptually be embedded into the audit of financial statements. This paper answers the call from Appelbaum et al. (2017) for more research in the context of big data and analytics in modern audit engagements. Guidance and evidence on how this can be done to meet the requirements of contemporary International Standards on Auditing (ISA) are provided.
Companies have automated their increasingly complex operations using advanced computer systems. This development has also affected the accounting and audit profession. Public accountants face new challenges because of this increase in automated transaction processing, the growing heterogeneity of source systems, the greater complexity of business processes and the increasing volumes and variety of created data. International and national audit standards do not directly specify how data analysis techniques can or should be employed in contemporary audits (IFAC, 2016). Historically, computer assisted audit tools (CAATs) have seldom been used as technological support in external audits (Braun and Davis, 2003; Debreceny et al., 2005). The acceptance of advanced data analysis techniques like regression or classification has generally been low in the audit profession (Kim et al., 2009), although these are particularly important in the context of big data (Chen et al., 2012)…
External auditors face new challenges due to the increasing integration of computer technology for the processing of business transactions. Traditional audit procedures become inefficient and ineffective in audit environments that are characterized by a high degree of integration of information systems for transaction processing. Process mining is a novel data analysis technique that can support the auditor in carrying out necessary audit procedures in a manner that overcomes contemporary challenges. With process mining auditors can analyse business processes and relevant internal controls effectively and efficiently. The entirety of recorded business transactions can be analysed and deviations identified automatically to guide further substantive audit procedures. Process and related internal controls can be analysed and assessed in a quantitative manner which makes it possible to determine the impact of control deficiencies on the financial accounts quantitatively. Audit firms have started to react to market demands and have developed proprietary software tools and first solutions to implement process mining into existing audit approaches. Although the potential benefits are significant for the audit profession, little guidance exists related to the question of how process mining techniques can be conceptually embedded into financial statement audits and how this can be done to meet the requirements of contemporary audit standards. This study has discussed how process mining can be embedded throughout the different phases of an audit to support the auditor by considering the requirements formulated in the ISA and using illustrative examples from a field study.
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