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Detection of Anomalies in Accounting Data Using Benford¡¯s Law: Evidence from India

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  • Ramesh Chandra Das
  • Chandra Sekhar Mishra
  • Prabina Rajib

Abstract

This study uses the financial accounting data to examine if they depart from Benford¡¯s Law. Using large sample of Indian public listed companies, the study conducts an analysis of the ¡°first digit analysis¡±, ¡°second digit analysis¡±, and ¡°first two digit analysis ¡°of test variables such as total assets, receivables, fixed assets, property, plant and equipment, inventory, current assets, current liabilities, sales, selling and distribution expenses, cost of goods sold, cash, EBIT, direct tax, indirect tax. The initial results find that most of the variables have significant deviation from Benford¡¯s Law distribution. Further analyses indicate that business group firms indulge more data anomalies than standalone firms and small size firms have more data anomalies than large size firms in Indian context.

Suggested Citation

  • Ramesh Chandra Das & Chandra Sekhar Mishra & Prabina Rajib, 2017. "Detection of Anomalies in Accounting Data Using Benford¡¯s Law: Evidence from India," Journal of Social Science Studies, Macrothink Institute, vol. 4(1), pages 123-139, January.
    • Handle: RePEc:mth:jsss88:v:4:y:2017:i:1:p:123-139
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    References listed on IDEAS

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    1. Umme Kulsoom Zaidi & Javaid Akhter & Asif Akhtar, 2018. "Window Dressing of Financial Statements in the Era of Digital Finance: A Study of Small Cap Indian Companies," Metamorphosis: A Journal of Management Research, , vol. 17(2), pages 67-75, December.

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