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

Ramesh Chandra Das, Chandra Sekhar Mishra and Prabina Rajib

Journal of Social Science Studies, 2017, vol. 4, issue 1, 123-139

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.

Date: 2017
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