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Using the Benford Distribution to Reduce the Risk of Undetected Misstatements of Financial Statements
EDN: LTXGRW
Abstract
A set of numerical arrays is considered, each of which describes the economic activities of some companies. For each array, the frequencies of occurrence of each of the possible digits in the first digit and in the second digit of the array elements are determined. The "distances" from the obtained empirical frequencies to the theoretical frequencies of Benford's law are calculated in several ways. Cluster analysis is performed on a set of points whose coordinates are calculated distances, dividing arrays into two groups characterized by varying degrees of "proximity" to Benford's law. The results of cluster analysis are used to train a classifier based on logistic regression, which is then used to predict the presence (or absence) of distortions in financial statements received from new companies.
About the Authors
S. Y. Krivolapov
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
Sergey Y. Krivolapov
125167; Leningradsky av., 49; Moscow
Scopus Author ID: MFZ-7354-2025
A. V. Komissarova
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
Anna V. Komissarova
125167; Leningradsky av., 49; Moscow
D. A. Khamula
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
125167; Leningradsky av., 49; Moscow
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Review
For citations:
Krivolapov S.Y., Komissarova A.V., Khamula D.A. Using the Benford Distribution to Reduce the Risk of Undetected Misstatements of Financial Statements. Issues of Risk Analysis. 2025;22(1):88-95. (In Russ.) EDN: LTXGRW
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