Detecting Accounting Fraud in Global Corporations: An Audit-Based Analysis Using Benford's Law | Zenodo Skip to main Communities My dashboard Log in Sign up Published April 11, 2026 | Version v1 Publication Open Detecting Accounting Fraud in Global Corporations: An Audit-Based Analysis Using Benford's Law Authors/Creators Sneha Manigandan, Dr. Kiran Kumar M Description This paper focuses on the problem of Benford Law as the effective statistical method which can help to discover the presence of accounting anomalies among large non-banking MNCs. The data used to perform the study are the initial decimal place distributions of six financial variables using 593 financial items with data retrieved through SEC 10-K filings of 20 global companies over five fiscal years (20202024) namely Revenue, Cost of Goods Sold (COGS), Operating Expenses, Total Assets, Net Income, and Accounts Receivable. These findings suggest that there are statistically significant departures of the data in terms of the distribution of Benford, achieving the chi-square value of 23.642 and the Mean Absolute Deviation (MAD) of 0.0195 highly exceed the critical value of 15.507 and 0.015, respectively. COGS and Total Assets have the most significant degrees of deviation, whereas Accounts Receivable has the least number of deviations. Sectoral analysis shows that the firms in the energy sector have the highest structural divergence; this is associated majorly with the volatility of the commodity prices. Moreover, there was also a steady increase in conformity levels in 2021-24, which can be attributed to post-pandemic regulatory changes. The research findings are that Benford Law although it is a good preliminary audit screening can never be utilized alone as evidence of fraud. When used in conjunction with more general forensic accounting methods, its usefulness improves greatly. Files Detecting Accounting Fraud in Global Corporations.pdf Files (1.8 MB) Name Size Download all Detecting Accounting Fraud in Global Corporations.pdf md5:428e9dc84251a26ea8b2adb28686a301 1.8 MB Preview Download Additional details Dates Submitted 2026-04-11 One of the most threatening and harmful threats in the capital markets across the world is the financial statement fraud. The high-profile collapse of Enron, WorldCom and Wirecard showed that, it is possible that several years of modified financial statement records can go unnoticed, including via formal audits. The scope of the old conventional sampling-based auditing becomes more evident as multinational corporations are becoming bigger and more complex, thus producing huge volumes of the transaction data in multiple countries. Even the most determining effort by auditors cannot be computerized to go through all the records of hundreds of thousands of records, and therefore, small manipulations which are deeply integrated in large datasets will just pass unnoticed. This poses an actual necessity of complementary, data methods that are capable of sweeping huge amounts of financial information in a very short period of time and identify any suspicious trends to be investigated further. This is what Benford in his Law provides. It is a scientific fact established through mathematics, which explains the distributions of the digits in the first place of numbers extracted out of natural processes. Instead of the even distribution of smaller digits, smaller numbers are found in the front of the numbers much more frequently than it was previously. In particular, the number 1 is the leading one with estimated 30.1 percent of leading cases, and the number 9 only has 4.6 percent of leading cases. The full table on the probability of any one of the first digit's d is as follows: References - Benford, F. (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, 78(4), 551–572. - Carslaw, C. A. P. N. (1988). Anomalies in income numbers: Evidence of goal-oriented behaviour. The Accounting Review, 63(2), 321–327. - Dechow, P., Ge, W., Larson, C., & Sloan, R. (2011). Predicting material accounting misstatements. Contemporary Accounting Research, 28(1), 17–82. - Drake, P. D., & Nigrini, M. J. (2000). Computer assisted analytical procedures using Benford's Law. Journal of Accounting Education, 18(2), 127–146. - Durtschi, C., Hillison, W., & Pacini, C. (2004). The effective use of Benford's Law to assist in detecting fraud in accounting data. Journal of Forensic Accounting, 5(1), 17–34. - Hill, T. P. (1995). A statistical derivation of the significant-digit law. Statistical Science, 10(4), 354–363. - Jianu, I., Jianu, I., & Ghiță, S. (2021). Benford's Law and financial reporting accuracy. Economic Research, 34(1), 1876–1894. - Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data mining techniques for fraud detection in financial statements. Expert Systems with Applications, 32(4), 995–1003. - Leonov, V. (2022). Multi-digit Benford analysis for financial irregularity detection. Journal of Applied Statistics, 49(8), 1921–1937. - Newcomb, S. (1881). Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics, 4(1), 39–40. - Nigrini, M. J. (1996). A taxpayer compliance application of Benford's Law. Journal of the American Taxation Association, 18(1), 72–91. - Nigrini, M. J. (2012). Benford's Law: Applications for forensic accounting, auditing, and fraud detection. John Wiley & Sons. - Rauch, B., Göttsche, M., Brähler, G., & Engel, S. (2011). Fact and fiction in EU-governmental economic data. German Economic Review, 12(3), 243–255. - Sharma, A., & Panigrahi, P. K. (2013). A review of financial accounting fraud detection based on data mining techniques. International Journal of Computer Applications, 39(1), 37–47. - Thomas, J. K. (1989). Unusual patterns in reported earnings. The Accounting Review, 64(4), 773–787. 59 Views 27 Downloads Show more details All versions This version Views Total views 59 59 Downloads Total downloads 27 27 Data volume Total data volume 61.9 MB 61.9 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords Benford Law; Detection Accounting Frauds; Forensic Accounting; Chi-square test; Mean Absolute Deviation; Multinationals; Audit analytics; Financial reporting; SEC10-K; digit distribution. 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