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کد محصول: H375
سال نشر: ۲۰۱۸
نام ناشر (پایگاه داده): الزویر
نام مجله: International Journal of Accounting Information Systems
نوع مقاله: علمی پژوهشی (Research articles)
تعداد صفحه انگلیسی: ۱۸ صفحه PDF
تعداد صفحه ترجمه فارسی: ۲۵ صفحه word
قیمت فایل ترجمه شده: ۲۱۰۰۰ تومان
عنوان فارسی:
مقاله ترجمه شده : درک استفاده و ارزش تحلیل حسابرسی برای حسابرسان داخلی: رویکرد سازمانی
عنوان انگلیسی:
Understanding usage and value of audit analytics for internal auditors: An organizational approach
چکیده فارسی:
اگرچه حسابرسان داخلی از اهمیت و ارزش تحلیل حسابرسی به طور فزاینده ای آگاه هستند، تحقیقات قبلی نشان می دهد که استفاده از تحلیل حسابرسی کمتر از انتظار است. این مقاله از چارچوب فناوری – سازمان-محیط (TOE) برای شناسایی و بررسی عواملی در سطح سازمانی استفاده می کند که تأثیر پذیری پس از اتخاذ تحلیل حسابرسی را بررسی می کند. و همچنین اینکه آیا با استفاده از تجزیه و تحلیل حسابرسی عملکرد فرآیند ممیزی داخلی را بهبود می بخشد و همچنین اینکه آیا استفاده از تحلیل حسابرسی عملکرد فرآیند حسابرسی داخلی را بهبود می بخشد . داده ها از مشتریان یک فروشنده بزرگ نرم افزار حسابرسی جمع آوری شد. نتایج نشان می دهد که استفاده در سطح کاربردی تحت تاثیر پشتیبانی مدیریت، شایستگی فنی و استانداردها قرار دارد. در حالی که کمک رسانی حرفه ای، شایستگی فنی و استفاده در سطح کاربردی، استفاده در سطح ویژگی را رو به جلو پیش می برد. در نهایت، استفاده از تحلیل حسابرسی در سطح کاربردی و سطح ویژگی ، عملکرد فرایند حسابرسی داخلی را بهبود می بخشد.
کلیدواژه: تحلیل حسابرسی، اتخاذ تکنولوژی حسابرسی، فناوری- سازمان-محیط
Abstract
Although internal auditors are increasingly aware of the importance and value of audit analytics, prior research indicates that the use of audit analytics is below expectation. This paper uses the Technology-Organization-Environment (TOE) framework to identify and examine factors at the organizational level that influence post adoption usage of audit analytics, as well as whether using audit analytics improves the performance of the internal audit process. Data were collected from clients of a major audit software vendor. Results indicate that application-level usage is influenced by management support, technological competence, and standards, while professional help, technological competence, and application-level usage drive feature-level usage. Finally, both application-level and feature-level audit analytics usages improve the performance of the internal audit process.
Keywords : Audit analytics,Audit technology adoption,TOE
Introduction
The use of analytics in the auditing domain has been emphasized by both practitioners and academia (Audimation, 2011, PWC, 2012, Wang and Cuthbertson, 2014, Cao et al., 2015). Audit analytics is defined as a science of “discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling, and visualization for the purpose of planning or performing the audit” (AICPA, 2015). Audit software vendors1 have developed many analytics tools to improve audit quality and enhance assurance. Some general data analytics software packages2 are also being employed in the audit process. The usage of audit analytics not only increases operational efficiency by reducing costs (KPMG, 2012), but also helps quickly identify potential fraud and anomalies, thereby providing a higher level of assurance (EY, 2014).
Audit analytics provides benefits to both external and internal auditors. However, it creates unique opportunities for internal auditors to assess potential risks, identify operational inefficiency, and provide insights (PWC, 2012, Schneider et al., 2015). First, internal auditors conduct much broader tasks than external auditors, such as investigation on financial and operational matters, fraud risk evaluation, etc. (Araj, 2015, Carcello et al., 2017). Therefore, internal auditors should have more demands on the use of audit analytics in order to accomplish those tasks in an efficient and effective manner. Second, internal auditors usually have more frequent access to business accounting data, to which audit analytics can be employed to quickly detect anomalies and fraud.
Finally, although current regulations for external auditors neither encourage nor prohibit the use of analytics, external auditors are likely to focus on the procedures that are explicitly required to satisfy regulatory requirements. By contrast, regulations for internal auditors are less strict than those for external auditors, allowing more flexibility in exploring various audit analytics tools. Not surprisingly, analytics are expected to become a core capability of internal auditors (Deloitte, 2016), and many researchers have devoted much effort into incorporating analytics to internal audit. For example, Thiprungsri and Vasarhelyi (2011) developed an analytical model to detect outliers from group life insurance claims. Kim and Vasarhelyi (2012) used analytics to identify potential fraud in the wire transfer payment process. Jans et al. (2014) demonstrated how internal auditors could use process mining of event logs as a new type of analytical procedure to detect deficient controls.
Although internal auditors are increasingly aware of the importance and value of audit analytics (Teammate, 2012, KPMG, 2015), surveys show that audit analytics is not being fully utilized by the majority of companies (AuditNet, 2012, EY, 2014, KPMG, 2015). Many auditors are not able to effectively incorporate audit analytics in their work and therefore only use it on an ad-hoc basis. While some articles (EY, 2014, KPMG, 2015) attempted to explore the barriers to the adoption of audit analytics, limited academic research has examined the actual usage level and the factors that result in the differences in its use.