DIGITAL AUDIT ANALYTICS: APPLYING BENFORD'S LAW TO MITIGATE RISK AND DETECT MATERIAL MISSTATEMENT IN FINANCIAL STATEMENTS: A CASE STUDY OF LUCKY CEMENT FACTORY

Abstract

The main purpose of this study is to use Benford's Law as a tool for fraud detection and prevention in different corporate organizations in Pakistan. This law is based on the principle of relative frequency distribution of the leading digits of the numbers in datasets, which would help in ensuring conformity to this law. The data used were historical data of the quoted company DG Khan Cement Company Limited (DGKC) with an observed frequency count of 1215 digit observations, which demonstrates practically the usefulness of Benford's Law. The respondents for the questionnaires were accountants, auditors, and accounting tutors representing various localities of Karachi. The digit analysis was done using Benford's Law V2.0 software, and the questionnaire responses were analyzed using Two-Way Analysis of Variance. Two hypotheses were generated and tested. The findings showed that Benford's Law was useful in empirical data analysis for fraud detection and that the Law was a statistical tool that can be used in audit analytical procedures. The respondents indicated that statistical techniques were much more satisfactory than intuition-based red flags techniques and financial ratio techniques. This research advocates the addition of more advanced statistical techniques to audit fraud-detection schemes. Such a design of audit analytical procedures could be helpful for auditors in mitigating the risk of fraud and exposing material misstatement inherent in financial statements.