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Hidden Risk: Detecting Fraud in Chinese Banks’ Non-performing Loan Data

Author

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  • Mayo, Robert

Abstract

Using self-reported data from banks in mainland China, I apply a technique used in forensic accounting based on Benford’s Law to detect fraudulent manipulation of non-performing loan (NPL) figures. I find large data anomalies consistent with false reporting in mainland banks that do not appear in an identically structured survey of Hong Kong banks. A comparison of different types of data from mainland banks shows no statistically significant anomalies in data for total deposits from customers, operating expenses, net interest income, or non-interest income.

Suggested Citation

  • Mayo, Robert, 2015. "Hidden Risk: Detecting Fraud in Chinese Banks’ Non-performing Loan Data," MPRA Paper 98435, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:98435
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    File URL: https://mpra.ub.uni-muenchen.de/98435/1/MPRA_paper_98435.pdf
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    References listed on IDEAS

    as
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    7. Rauch Bernhard & Göttsche Max & Engel Stefan & Brähler Gernot, 2011. "Fact and Fiction in EU-Governmental Economic Data," German Economic Review, De Gruyter, vol. 12(3), pages 243-255, August.
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    Cited by:

    1. Kauko, Karlo, 2019. "Benford’s law and Chinese banks’ non-performing loans," BOFIT Discussion Papers 25/2019, Bank of Finland, Institute for Economies in Transition.

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    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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