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Using Sparse Modeling to Detect Accounting Fraud (Japanese)

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Listed:
  • USUKI Teppei
  • KONDO Satoshi
  • SHIRAKI Kengo
  • MASADA Takahiro
  • SUZAKI Kosuke
  • MIYAKAWA Daisuke

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.

Suggested Citation

  • USUKI Teppei & KONDO Satoshi & SHIRAKI Kengo & MASADA Takahiro & SUZAKI Kosuke & MIYAKAWA Daisuke, 2021. "Using Sparse Modeling to Detect Accounting Fraud (Japanese)," Discussion Papers (Japanese) 21049, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:rdpsjp:21049
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