Audit Risk Assessment Model in Automated Accounting Systems of Enterprises in Ukraine
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Date
2021
Authors
Пономаренко, Оксана Григорівна
Канцедал, Наталія Анатоліївна
Остапчук, Сергій Миколайович
Аранчій, Валентина Іванівна
Aranchiy, V. I.
Kantsedal, N. A.
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Abstract
The topicality of searching tools to minimize (neutralize) the probable consequences of information risk of financial reporting users in data processing computing environment requires components’ revision of the traditional multiplicative risk assessment model by auditor. The result of the research is confirmed by two inter-complemented hypotheses: theoretical (about the necessity to expand the classical model of audit risk assessment) and empirical (about the expediency of using intellectual analysis methods of reporting in audit). The aim of the study is to substantiate the needs and formalize the procedures of expanding the components of traditional multiplicative model of audit risk assessment in computer systems processing accounting data of audit’s client to reduce the level of information risk for financial reporting users.
Practical value of the authors’ approach consists in increasing formalization level of auditor’s professional opinion and substantiating the size of audit samples. This enables to reduce information uncertainty of interested users of financial statements.
It is proven that using multifactor models of correlation-regression analysis will make it possible for auditor to predict the values of report items that can be an instrument of manipulation and distortion of enterprises’ financial statements
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Keywords
облік, аудит, автоматизовані системи обліку, фінансова звітність, аудиторський ризик, інформаційний ризик, ризик невиявлення
Citation
Ponomarenko O., Kantsedal N., Aranchiy V., Ostapchuk S. (2021) Audit Risk Assessment Model in Automated Accounting Systems of Enterprises in Ukraine. In: Alareeni B., Hamdan A., Elgedawy I. (eds) The Importance of New Technologies and Entrepreneurship in Business Development: In The Context of Economic Diversity in Developing Countries. ICBT 2020. Lecture Notes in Networks and Systems, vol. 194. Springer, Cham. pp. 1192-1204. https://doi.org/10.1007/978-3-030-69221-6_90