Hidden Risk
Open Access
- 22 January 2022
- journal article
- Published by Center for Strategic Studies in Business and Finance SSBFNET in International Journal of Finance & Banking Studies (2147-4486)
- Vol. 11 (1), 98-106
- https://doi.org/10.20525/ijfbs.v11i1.1550
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.Keywords
This publication has 7 references indexed in Scilit:
- Comparing China’s GDP statistics with coincident indicatorsJournal of Comparative Economics, 2011
- Fact and Fiction in EU-Governmental Economic DataGerman Economic Review, 2011
- Benford’s Law Strikes Back: No Simple Explanation in Sight for Mathematical GemThe Mathematical Intelligencer, 2011
- Deconstructing China's GDP statisticsChina Economic Review, 2004
- Accuracy and reliability of China's energy statisticsChina Economic Review, 2001
- A Statistical Derivation of the Significant-Digit LawStatistical Science, 1995
- Note on the Frequency of Use of the Different Digits in Natural NumbersAmerican Journal of Mathematics, 1881