Using Sparse Modeling to Detect Accounting Fraud (Japanese)

Teppei Usuki, Satoshi Kondo, Kengo Shiraki, Takahiro Masada, Kosuke Suzaki and Daisuke Miyakawa

Discussion Papers (Japanese) from Research Institute of Economy, Trade and Industry (RIETI)

Abstract: In this paper, we implement anomaly detection on listed firms' accounting items. Using a type of sparse modeling, i.e., Graphical Lasso, we confirm that our accounting fraud detection has achieved a practically admissible level of detection capability. We also find that the method of sparse modeling contributes to detection capability.

Pages: 19 pages
Date: 2021-10
New Economics Papers: this item is included in nep-acc, nep-big, nep-iue and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:eti:rdpsjp:21049

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