Purpose – The purpose of this paper is to provide evidence, from the analysis of 132 fraud risk measurement exercises, of the average costs and rates of fraud. It advocates greater use of more accurate measurement which if monitored and repeated can secure reductions which could amount to a new competitive advantage. Design/methodology/approach – This paper has analysed 132 fraud risk measurement exercises from nine countries in a range of different sectors. Only those which assess a statistically valid sample which have sought and examined information indicating the presence of fraud, error or correctness in each case within that sample; have been completed and reported; have been externally validated; have a measurable level of statistical confidence; and have a measurable level of accuracy were included. Each exercise has been assessed to determine the percentage loss rate (PLR) and the fraud frequency rate (FFR). These data were analysed using Excel to determine average rates and further comparable data. Findings – Fraud and error losses in an organisation should currently be expected to be at least 3 per cent, probably more than 5 per cent and possibly more than 9 per cent. The PLR when first measured has been found to be 5.40 per cent and 4.61 per cent when last measured, representing an average reduction of just under 15 per cent. The paper shows fraud and error can be measured and if regularly this incentivizes action to reduce it reaping financial benefits to the organization. Research limitations/implications – The vast majority of the data are drawn from fraud risk measurement exercises in the public sector in large organizations. Practical implications – The paper advocates greater use of fraud risk measurement and counter fraud strategies tailored to reduce losses. Originality/value – This is the first analysis of fraud risk measurement exercises across the globe.
Journal of Financial Crime – Emerald Publishing
Published: Dec 29, 2011
Keywords: Financial crime; Fraud; Competitive advantage; Risk analysis; Public sector; Measurement; Fraud risk measurement