AUDITING ANALYSIS TO ESTIMATE ERROR AND RISK OF MATERIAL MISSTATEMENT OF ACCOUNTING ITEMS BASED ON THE BASIS OF BENFORD LAW

Abstract

Benford Law is known as an analytical tool to detect errors in the accounting data of the business. The paper presents the results of a combination of Benford's law and statistical probability theory to construct a model for estimating error rates and the risk of material misstatement of accounting items. At the same time, use Bayesian statistical theories to identify areas (or sets of numbers) with the potential for errors (or fraud) and to show out some specific information to instruct the auditors to check quickly, optimal time to ensure accuracy. In terms of meaning, the results of this research will help the auditor to estimate errors (both relative and absolute) for comparison with the materiality level of the accounting items. At the same time, indicate potential areas of fraud as shown in the posterior probability table associated with the results of the Benford analysis. Such information will help the auditor to formulate auditing opinions or make detailed auditing decisions to achieve optimum reliability in terms of time and auditing costs.