BIG DATA PROCESSING TECHNIQUES IN FINANCIAL CONTROL TASKS
https://doi.org/10.26583/vestnik.2022.5
Abstract
Every year the volume of corporate data to be analysed in financial controls increases, which makes it relevant to introduce Big Data processing techniques into the practice of control subjects. The purpose of the study is to develop and test three techniques of Big Data processing in order to solve the problems of public and private sector organisations carrying out activities in the field of financial control. As research methods, we have chosen three most promising and effective means of processing Big Data, which at the same time do not require the use of complicated mathematical apparatus or significant computer power for their implementation, namely, a statistical tool for detecting errors in financial data Benford's law, clustering method of K-means and the means BI-system Power BI. The result of the study is the confirmation of the effectiveness and cost efficiency of the considered techniques of processing Big Data and the justification of the practical possibility of their implementation as financial control tools. The research was conducted in the student Financial Intelligence Laboratory of NRNU MEPhI.
About the Authors
V. M. Sushkov
National Nuclear Research University MEPhI
Russian Federation
Russian Federation
P. Y. Leonov
National Nuclear Research University MEPhI
Russian Federation
Russian Federation
References
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Review
For citations:
Sushkov V.M., Leonov P.Y. BIG DATA PROCESSING TECHNIQUES IN FINANCIAL CONTROL TASKS. Vestnik natsional'nogo issledovatel'skogo yadernogo universiteta "MIFI". 2022;11(5):348-357. (In Russ.) https://doi.org/10.26583/vestnik.2022.5
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