Book of Short Papers, Proceedings of the 12th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), pp. 75-78.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: The main goal of the article is to discuss methods based on the Euclidean distance which can be used during the identification of financial frauds. The methods enable assessing data conformity to Benford's Law, within the primary tests of this law. After discussing techniques based on the Euclidean distance, an example of accounting fraud detection is presented.
Bibtex:
@inproceedings{,
AUTHOR={Mateusz Baryła and Józef Pociecha},
TITLE={Euclidean distance as a measure of conformity to Benford's law in digital analysis for fraud detection},
BOOKTITLE={12th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS)},
MONTH={September},
YEAR={2019},
PAGES = {75--78},
URL={http://cladag2019.unicas.it/download-files/cladag-book-abstract-pre-print.pdf},
}
Reference Type: Conference Paper
Subject Area(s): Accounting, Analysis