Publication:
Possibility of Benford’s Law Application for Diagnosing Inaccuracy of Financial Statements

Дата
2022
Авторы
Suyts, V. P.
Leonov, P. Y.
Rychkov, V. A.
Ezhova, A. A.
Sushkov, V. M.
Kuznetsova, N. V.
Кузнецова, Надежда Владимировна
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Научные группы
Организационные подразделения
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Организационная единица
Институт финансовых технологий и экономической безопасности
Институт финансовых технологий и экономической безопасности (ИФТЭБ) Национального исследовательского ядерного университета "МИФИ" готовит кадры в интересах национальной системы по противодействию легализации (отмыванию) доходов, полученных преступным путем, и финансированию терроризма (ПОД/ФТ). Междисциплинарность образования позволит выпускникам ИФТЭБ НИЯУ МИФИ легко адаптироваться на современном рынке труда и в бизнес-среде.
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Аннотация
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The paper describes a technique for diagnosing data inaccuracy using Benford’s law. The Benford distribution for the first significant digit of a random decimal number is presented graphically and mathematically. The main requirements for data are listed, which are consistent with Benford’s law: the data must refer to one process, there must be no maximum and minimum restrictions in the studied population, artificial introduction of the numbering system is not allowed, and there must be no obvious linking patterns between numbers. When examining the possibility of applying Benford’s law to diagnose inaccuracies in the financial statements of an organization, the costs of two companies for payment of services to suppliers were analyzed. It was found that in the absence of attempts to manipulate reporting, performance indicators are close to theoretically predicted based on Benford’s law. Attempts to manipulate reporting are reflected in corresponding deviations from Benford’s law. The possibility of applying Benford’s law to diagnose unreliability of an organization’s financial statements has been proved.
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Possibility of Benford’s Law Application for Diagnosing Inaccuracy of Financial Statements / Suyts, V.P. [et al.] // Studies in Computational Intelligence. - 2022. - 1032 SCI. - P. 243-248. - 10.1007/978-3-030-96993-6_24
URI
https://www.doi.org/10.1007/978-3-030-96993-6_24
 https://www.scopus.com/record/display.uri?eid=2-s2.0-85127693532&origin=resultslist
 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000833484200024
 https://openrepository.mephi.ru/handle/123456789/28941
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