PRINCIPLES OF ARTIFICIAL INTELLIGENCE APPLICATION IN CONTROL OF THE ENTERPRISE
Introduction. the implementation of the tasks of evaluating historical financial information, the control or audit of business activities are based primarily on professional judgments about the object of study of a professional accountant or auditor. Their findings are drawn on the basis of the study of documents, the use of audit evidence, risk assessment, etc. There is always a probability (and rather high) that professional judgment will be based on incomplete information (since the dynamics of information changes is extremely high today), on the misstatements (since it is impossible to trace all the changes in knowledge related to the object of study), regardless of the quality of the performance of these individuals. In addition, the auditor often takes subjective decisions (for example, when choosing individual elements for the assessment from the general population), which also affects the degree of objectivity of his assessments. Artificial intelligence is the tool that could handle the entire set of knowledge, track all changes in the significant and important information, as well as in the insignificant and unimportant (which, however, also has an effect on the object of analysis). It does not have a work schedule or other restrictions on the time of work, so the comparison and analysis of information can be carried out around the clock, and the speed of data processing is determined by the processing power of the information systems, on which it operates, and is stably high. In this case, artificial intelligence is ready to perform the tasks non-stop in real time till receiving the command of termination the process.
Purpose. This article proposes a methodology for the artificial use in the control systems of economic activity, reflects the artificial intelligence concept in the control systems of economic activity, indicated the goals, principles, tasks and its functions when checking an object.
Results. Therefore, unlike most other information systems, artificial intelligence uses probabilistic processes, rather than clear rules and algorithms to obtain results. Unlike auditors, which verify information depending on the expected result, artificial intelligence “does not expect” any result, but only the probabilities of each of the results. Actually, unpredictability of the results creates a risk, creating potential problems for auditors, who use traditional methods. This article describes the concept of the application of artificial intelligence in business control systems, and shows the goals, principles, objectives and functions of the object.
Originality. The role of artificial intelligence in the realization of assurance tasks lies in increasing the effectiveness of the control system. This goal is achieved through the implementation by artificial intelligence in the process of auditing the following functions:
- improving the quality of data processing: considering, apart from important noticeable and significant data, also important imperceptible, secondary noticeable and imperceptible, as well as even insignificant, omissible and imperceptible data for analysing information and identifying the truth;
- increasing the productivity of the audit system by analysis of the information, associated with the object of audit, round-the-clock, without fatigue, distraction, with a stable high speed of data processing;
- acceleration of reaction to changes in the information space and considering all possible factors that influence or have influenced the decision-making associated with the object of audit, reduce the risk of errors caused by obsolete knowledge.
Performing these functions depends on specific tasks according to the type of control object. Thus, before setting the task to artificial intelligence, it is necessary to classify the object according to different features: volume, size, scale, level, etc. For example, the control over the correctness of the calculation and payment of value added tax is appropriate to assign to artificial intelligence, in particular, in part of the comparison of information in the regulations, primary documents, agreements with counterparties, budget movement report for funds in bank accounts, tax returns, etc., when it comes to a separate enterprise. Otherwise, it is advisable to describe the level of information support when it comes to state-level control. In addition, the information from the tax authorities, data from registers of different levels, etc. should be used as well.
Therefore, the tasks of artificial intelligence in cooperation with the auditor in the control systems of economic activity are:
- analysis of complete information about the object of control and its individual elements, including indirect, in particular, Big Data research;
- comparison of the information about object of control with the analysed information;
- identify inconsistencies that lead to misstatements in the financial or other business reporting of the entity.
As a result, the risk of the auditor's failure to detect serious or minor misstatement because of fraud or error will tend to zero.
Conclusion. The implementation of the tasks of evaluating historical financial information, the control or audit of business activities are based primarily on professional judgments about the object of study of a professional accountant or auditor. Their findings are drawn on the review of documents, the use of audit evidence, risk assessment, etc. This article proposes a methodology for the artificial use in the control systems of economic activity, reflects the artificial intelligence concept in the control systems of economic activity, indicated the goals, principles, tasks and its functions when checking an object.
2018 AI Predictions 8 insights to shape business strategy. Retrieved from https://www.pwc.es/es/home/assets/ai-predictions-2018-report.pdf (Accessed: 14.11.2019).
AI in the UK: ready, willing and able? Retrieved from https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf (Accessed: 14.11.2019).
Artificial Intelligence Innovation Report 2018. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/de/Documents/Innovation/Artificial-Intelligence-Innovation-Report-2018-Deloitte.pdf (Accessed: 14.11.2019).
Bochulia, T., & Melnychenko, O. (2019). Accounting and analytical provision of management in the times of information thinking. European Cooperation, 1(41), 52–64.
Bochulia, T., & Yancheva, I. (2017). Scenario maps of management as effective concept for sustainable development of enterprise. European Cooperation, 8(27), 44–52.
Girchenko, T., & Kossmann, R. (2016). Implementation and development of digital marketing in modern banking business. European Cooperation, 12(19), 68–85.
Handbook of International Quality Control, Auditing, Review, Other Assurance, and Related Services Pronouncements (2018). The International Federation of Accountants (IFAC). ISBN: 978-1-60815-389-3.
Ivanov, S., Liashenko, V., Kamińska, B., & Kvilinskyi, O. (2016). A concept of modernization evaluation. European Cooperation, 12(19), 86–101.
Jean-Gabriel Ganascia. (2018). Artificial Intelligence. The promises and the threats. July-September 2018. Retrieved from http://unesdoc.unesco.org/images/0026/002652/265211e.pdf (Accessed: 14.11.2019).
Melnychenko, O. (2019). Application of artificial intelligence in control systems of economic activity. Virtual Economics, 2(3), 30–40. https://doi.org/10.34021/ve.2019.02.03(3).
Melnychenko, O., & Hartinger, R. (2017). Role of blockchain technology in accounting and auditing. European Cooperation, 9(28), 27–34.
Omoteso, K. (2012). The application of artificial intelligence in auditing: Looking back to the future. Expert Systems with Applications, 39, 9, 8490-8495. https://doi.org/10.1016/j.eswa.2012.01.098.
The future of the world: a forecast up to the year 2099. Retrieved from http://earth-chronicles.com/science/the-future-of-the-world-a-forecast-up-to-the-year-2099.html (Accessed: 14.11.2019).
THE RISE OF ARTIFICIAL INTELLIGENCE: FUTURE OUTLOOK AND EMERGING RISKS. ALLIANZ GLOBAL CORPORATE & SPECIALTY. March 2018. Retrieved from https://www.agcs.allianz.com/assets/Insights/Artificial%20Intelligence/Artificial_Intelligence_Outlook_and_Risks.pdf (Accessed: 14.11.2019).
Winston, P. H. (1993). Artificial intelligence. Third edition. ADDISON-WESLEY PUBLISHING COMPANY. ISBN 0-201-53377-4.
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