Abstract

PricewaterhouseCoopers (2020) has reported the highest level of economic crime in their comprehensive annual survey of the issue since it launched more than twenty years ago. Two thirds of respondents indicated that the costs of fraud can reach up to a million dollars each, amounting to approximately ten percent of their annual turnover. Inside perpetrators such as employees commit about 37 percent of these frauds. In this context, a technique known as Benford’s Law can be cost-effectively applied to detect financial fraud which can be invaluable to auditors and other financial professionals. Benford’s technique is founded on the mathematical distribution of integers found in nature and has been shown to be particularly efficient and cost-effective in financial fraud detection. The technique can swiftly flag suspicious transactions from lists of numbers that comprise millions of records when employed as a computer assisted auditing procedure. Despite this, Benford’s Law is not widely used in accounting and finance. One of the key reasons for its limited use is because fraud investigators are often incognizant and unfamiliar with the method, and how it can be implemented in a fraud detection workflow. This paper set forth a concise and organised approach for implementing Benford’s technique as an analytical procedure through the well-known IDEA generalised audit software to flag suspicious transactions, which can then be further investigated. Both the application of the method and its interpretation in situations of both compliance and non-compliance is discussed. The methodology proposed in this paper can be an indispensable aid for fraud investigators in view of the considerable costs associated with economic crime.

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