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International Econometric Conference of Vietnam

ECONVN 2018: Econometrics for Financial Applications pp 648–655Cite as

Application of Statistical Methods for Tax Inspection of Enterprises: A Case Study in Vietnam

  • 2017 Accesses

Part of the Studies in Computational Intelligence book series (SCI,volume 760)

Abstract

In this study, we apply statistical methods based on Benford’s Law for checking accuracy of tax reports. Specifically, instead of the usual practice of randomly selecting documents for detailed scrutiny, the proposed method selects the most suspicious document. Our experience of using this method has shown that its application has drastically increased the probability of detecting tax fraud. This method is relatively easy to use, it is based on a simple Excel-based algorithm.

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Author information

Authors and Affiliations

  1. Department of Accounting and Auditing, Banking University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Nguyen Thi Loan & Le Dinh Hac

  2. Binh Thanh District Tax Department, Ho Chi Minh City, Vietnam

    Nguyen Viet Hong Anh

Authors
  1. Nguyen Thi Loan
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  2. Le Dinh Hac
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  3. Nguyen Viet Hong Anh
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Corresponding author

Correspondence to Nguyen Thi Loan .

Editor information

Editors and Affiliations

  1. Banking University HCMC, Ho Chi Minh City, Vietnam

    Ly H. Anh

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Le Si Dong

  3. Computer Science Department, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  4. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

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Loan, N.T., Hac, L.D., Anh, N.V.H. (2018). Application of Statistical Methods for Tax Inspection of Enterprises: A Case Study in Vietnam. In: Anh, L., Dong, L., Kreinovich, V., Thach, N. (eds) Econometrics for Financial Applications. ECONVN 2018. Studies in Computational Intelligence, vol 760. Springer, Cham. https://doi.org/10.1007/978-3-319-73150-6_51

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  • DOI: https://doi.org/10.1007/978-3-319-73150-6_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73149-0

  • Online ISBN: 978-3-319-73150-6

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