| Abstract [eng] |
Big Data (BD) is one of the most commonly used terms in the modern world of business and information technology. The main features of BD (quantity, speed, and variety) introduce to unique processing of large information amounts, regardless of their scale, storage and computational complexity, analytical and statistical correlation. The significant emergence and potential use of BD has affected business accounting and financial auditing by replacing the long-used mechanical data collection and completion processes with automatic ones, comparing and searching for correlations between different structure and nature data. Research objects are Big Data analytics tools and financial audit procedures. The Aim of the Study is to investigate the impact of Big Data Analytics (BDA) tools for financial audit procedures. According to theoretical analysis, the main advantages of applying Big Data Analytics in the audit process are related to: faster and more efficient execution of procedures, obtaining more detailed results, performing automatic selections in large databases, grouping, sorting and comparing data according to selected criteria. In the meantime, cons of Big Data application are related to the additional professional supervision requirements and the proper data analysis in order for the correct results interpretation. There is a need for ongoing financial costs for the maintenance and renewal of BDA equipment as well. Also BDA tools should be adapted to companies, which have signed long-term audit contracts and have sufficiently innovative information systems. It is very important that high competence of the audit team is required for the application and evaluation of BDA in specific financial procedures. Further research is conducted by analyzing the operation of the conceptual model, traditional and BDA audit tools application in evidence-gathering procedures. The effectiveness of the traditional and BDA audit tools application is assessed in terms of productivity, completeness, clarity, traceability and continuity. Research results show that BDA tools are mainly characterized by productivity and completeness criteria. In the case studies, the criterion of clarity is common to almost all BDA tools, except for classification and regression, time series analysis. It means that most of BDA tools generate auditing results clearly without the necessity for additional comments or specific expertise to understand the information provided. Meanwhile, criterion of traceability is not acceptable to the association rules, word processing methods, because verification procedure of General Ledger records testing is standardized and does not require additional grouping or filtering actions. One of the least common criteria of BDA tools application is continuity, which is important for comparing company’s accounting activities with the information provided for last year’s audit. While automated continuity is one of the BDA disadvantages, implementing this criterion in clustering, association rules, word processing, and visualization tools would make another big opportunity for innovative financial audit testing. Most of BDA tools have changed traditional audit methods with automatic ones: manual data filtering and grouping are changed to data governance by source codes, manual calculations and testing are changed to standardized functions, testing observations and results are generated automatic in the common report. Research have showed that all BDA tools helps to improve effectiveness in term of productivity and completeness, 60% of methods give more clarity in the audit results and traceability of repeating the testing process, only 20% of BDA tools give the opportunity to compare and use information provided for current and last year’s audit. |
