Journal Article Summaries

Measuring the cost of fraud: an opportunity for the new

competitive advantage Mark Button

Centre for Counter Fraud Studies, University of Portsmouth, Portsmouth, UK

Jim Gee Counter Fraud Services Department, MacIntyre Hudson LLP, London, UK, and

Graham Brooks Centre for Counter Fraud Studies, University of Portsmouth, Portsmouth, UK

Abstract

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.

Keywords Financial crime, Fraud, Competitive advantage, Risk analysis, Public sector, Measurement, Fraud risk measurement

Paper type Research paper

Introduction In an era of tighter budgets and more competitive markets organisations are looking for innovative ways to reduce costs. Many strategies and innovative ideas have been pursued, from contracting out to flatter management structures; to achieve what is often described as “competitive advantage” (Porter, 2004; Briggs and Edwards, 2006). One measure which has not been on the “radar” of the vast majority of organisations to achieve this aim is investing in measures to counter fraud. This paper will show that

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Measuring the cost of fraud

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Journal of Financial Crime Vol. 19 No. 1, 2012

pp. 65-75 q Emerald Group Publishing Limited

1359-0790 DOI 10.1108/13590791211190731

drawing upon 132 fraud risk measurement exercises from nine countries that fraud and error are generally a major cost and vary significantly in size. The authors contend that introducing the appropriate strategies to measure fraud and then counter it effectively can reduce it, which in organizations with substantial budgets a few percentage points reduction in fraud losses can reap substantial financial returns, as will be shown later in this paper. In the public sector this could be released for greater resources for services or avert cuts in budgets and in the private sector, provide the source of competitive advantage.

This paper will start by examining the broad challenges of measuring crime in general and fraud in-particular. It will then move on to set out the methodology used for this paper. Before setting out the results, the paper will briefly examine professional approaches to countering fraud, highlighting the importance of accurate measurement and some of the guidance and debate surrounding it. The paper will then present the key findings from the assessment of 132 fraud risk measurement exercises before concluding on the key issues and areas for further research.

The measurement of crimes and fraud Crimes in general pose challenges in measurement which evoke debates over the merits of different methods used to gauge them. Generally the recorded crime statistics are criticised as not been accurate because of the attrition from non-reports and reports which are not recorded in the statistics (Maguire, 2007). The British Crime Survey is generally seen as more accurate because it is based upon a large statistically valid sample of the British population and records their experience of crime victimization (Maguire, 2007). The situation with fraud is even more contested (Hoare, 2007; Levi et al., 2007). Until 2006 and the passage of the Fraud Act there was no codified set of offences in England and Wales (Farrell et al., 2007). There has (and still is) much more debate over what constitutes fraud (Doig, 2006). Many organisations and individuals are reluctant to report frauds and many also pursue it through the civil courts (Higson, 1999; Button etal., 2009). Perhaps most importantly, many frauds are undiscovered and therefore hidden from official returns. This means recorded statistics of fraud presented by the police and related bodies only capture the tip of the iceberg.

As with general crime there are also alternatives to measure fraud. There are many surveys which ask the person responsible for fraud in an organisation what they perceive to be the level of fraud, such as the Association of Certified Fraud Examiners (ACFE) Report to the Nation, which asks the key counter fraud professional in the organization what their percentage and actual losses from occupational fraud are (ACFE, 2007). For some this is pure a guestimate and for this reason surveys such as this are not rooted in methodologically sound principles. There are also measures such as the KPMG fraud barometer which assesses the number of cases of fraud over £100,000 which have reached the criminal or civil courts. Clearly all frauds under £100,000 are not covered and it only reflects detected frauds which are prosecuted or pursued in the civil courts. There are many which are not detected or there is a decision not to pursue through the courts (KPMG, 2009).

The most accurate measures are fraud risk measurement exercises. The central premise of this approach is that within a total number of transactions there will be a number of fraudulent and mistaken cases (contractors paid twice, wrong salary paid, etc. as a result of error rather than fraud), which have not been discovered.

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Figure 1 shows this further via a pyramid. At the very top are the small number of detected cases of fraud and error which the organization knows about. Below that are the cases of fraud and error the organization does not know about and at the bottom is the vast majority of cases which are not fraud or error. The fraud risk measurement exercise focuses upon a specific area of activity, such as procurement, staff payrolls, expense claims to name some. A statistically valid sample is then reviewed and from this they are usually classified as fraudulent, an error or acceptable. The important difference in this type of measurement is that by assessing a range of transactions in greater detail, those undertaking the review are able to discover a sample of cases of fraud and error which otherwise would not have been discovered. From this it is then possible to extrapolate on the actual levels of fraud (to a specific statistical confidence level). To return to the pyramid in Figure 1 the aim is to uncover the size of the top two tiers of the pyramid. It is this latter type of measurement which will be the focus of this paper.

Methodology This paper has reviewed 132 exercises to accurately measure fraud and error losses, covering 32 different types of expenditure totalling almost £800 billion, in 44 organisations from nine countries. Including the types of expenditure where exercises have been repeated, they have examined a total of expenditure valued at £3 trillion, sterling equivalent. The value of the expenditure examined has not been uprated to 2009 values. The paper has excluded guesstimates, figures derived from detected fraud losses, and figures resulting from surveys of opinion. It has also excluded some loss measurement exercises where it is clear that they have not met the standards described below. It has included exercises which have considered a statistically valid sample of income or expenditure:

. which have sought and examined information indicating the presence of fraud, error or correctness in each case within that sample;

. which have been completed and reported;

. which have been externally validated;

. which have a measurable level of statistical confidence; and

. which have a measurable level of accuracy.

There are a number of caveats that need to be noted before we consider the results. Some of the exercises have resulted in estimates of the fraud frequency rate (FFR), some of the percentage of expenditure lost to fraud, and some have measured both.

Figure 1. The fraud and error pyramid

Normal Transactions

Undetected Fraud and Error

Detected Fraud and Error

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It is also the case that some exercises have separately identified measured fraud and error and some have not. In some cases, there have been repeated exercises to measure fraud and error losses in a single area of expenditure. To avoid skewing the overall results by including a disproportionate quantity of data from one source, only the results from the first and most recent exercises have been included. In most of these instances, fraud and error losses have been significantly reduced since the initial measurement exercises. Sometimes, once such exercises have been completed, the organisations concerned have, mistakenly in the view of the authors of this paper, decided not to publish their results. In some cases, those directly involved in countering fraud have decided, confidentially, to provide this information for wider consideration. In those cases, while the overall figures have been included in the findings of this paper, no specific reference has been made to the organisations concerned. The authors of this paper are also aware of a very small number of other exercises which have been completed, but which have not been published and where nothing is known of the findings. Finally, it is important to emphasise that this research will never be complete. More evidence becomes available each year. However, the preponderance of the evidence does point clearly in one direction, as is explained later.

While it is necessary to make these caveats clear, the importance of the evidence collated in this paper should not be underestimated. The evidence shows fraud and error losses can be measured – when they have been successfully measured so many times, in respect of so many different types of expenditure, in many different organisations and across the world, to assert otherwise is the modern day equivalent of arguing that the world is flat! However, even more important is that the evidence shows that losses to fraud and error represent a significant, damaging and, crucially, unnecessary business cost.

Countering fraud: a professional approach Organisational responses to fraud vary significantly from sector to sector and country to country. Generally in most areas of commerce the commitment to countering fraud is not high enough. For example, a study of UK FTSE 100 companies found a significant number of those surveyed (ten of 32) did not have a counter fraud strategy. There was also found to be gaps in terms of having a designated person responsible for counter fraud, regular fraud risk assessments, employment of staff to counter fraud, pursuing sanctions and the development of an anti-fraud culture (Brooks et al., 2009). Research on measures to develop anti-fraud culture in the public sector in the UK have also highlighted gaps with limited staff awareness training and screening of staff and contractors (Button and Brooks, 2009). Using the core requirements of the Chartered Institute of Public Finance and Accountancy (CIPFA) guidance on countering fraud research on central government bodies and the FTSE 100 companies has highlighted limited standards in the latter with companies amounting to £180 billion of turnover at significant risk from fraud (Gee et al., 2009). Other surveys have also highlighted gaps in organisations’ strategies to counter fraud (Bussmann and Werle, 2007; Fraud Review Team, 2006; Ernst & Young, 2006) and some of the most common issues include:

. a reluctance to accurately measure the size of the problem;

. a reluctance to report cases of fraud when they are discovered;

. the lack of a counter fraud strategy which includes the key areas expected;

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. lack of resources to counter the problem; and

. lack of capacity of staff to counter fraud.

To address the gap countering fraud effectively a number of best practice guides have been produced. The three most significant in the UK are the HM Treasury’s (2003) Managing the Risk of Fraud, A Guide for Managers, the joint National Audit Office (2004) Good Practice in Tackling External Fraud and the CIPFA Better Governance Forum’s Managing the Risk of Fraud Actions to Counter Fraud and Corruption Red Book 2. There is not scope to explore all the strategies advocated, but one key criteria is for the organisation “[. . .] to identify accurately the nature and scale of losses to fraud and corruption’ (CIPFA, 2006). This is something the Fraud Review Team (2006) and the European Healthcare Fraud and Corruption Network (2004) have also advocated. In the USA it has also been mandated in legislation through the Improper Payments Information Act (IPIA), which will be explored shortly.

The nine countries in which the authors are aware that fraud loss analysis exercises have taken place are: the UK, the USA, France, Belgium, The Netherlands, Ireland, Canada, Australia, and New Zealand. By value of income or expenditure measured, the USA has undertaken the greatest amount of work in this area. This is a direct reflection of the IPIA of 2002 which requires designated major US public authorities to estimate the annual amount of payments made where fraud and error are present, and to report the estimates to the President and Congress with a progress report on actions to reduce them. The guidance relating to the IPIA states:

The estimates shall be based on the equivalent of a statistical random sample with a precision requiring a sample of sufficient size to yield an estimate with a 90% confidence interval of plus or minus 2.5% (White House, n.d.).

Many US agencies undertake work to the higher standard often found in the UK and Europe – 95 per cent statistical confidence and ^1 per cent.

In other countries, while there has not hitherto been any legal requirement, there is a growing understanding that the key to successful loss reduction is to understand the nature and scale of the problem. For example, in Europe, the European healthcare fraud and corruption declaration of 2004, agreed by organisations from 28 countries states that:

The development of a European common standard of risk measurement, with annual statistically valid follow up exercises to measure progress in reducing losses to fraud and corruption throughout the EU (European Healthcare Fraud and Corruption Network, 2004).

The range of types of income and expenditure where losses have been measured include: payroll, procurement, housing, education, social security, healthcare, insurance, tax credits, pensions, transport, and construction. Two types of figures have been produced:

(1) a percentage loss rate (PLR, i.e. the proportion of expenditure lost to fraud and error); and

(2) an FFR (i.e. frequency of fraud and error).

The same exercise can produce different PLR and FFR figures. This is because the items of expenditure where fraud is found to be present may be either greater or lesser than the average value of all of the items of expenditure. For example, it may be that fraud tends to affect items of expenditure that are higher than the average value – this will result

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in the PLR being higher than the FFR. Indeed, to some extent the findings of this research, in general, show just that. An analysis of the figures has also been produced for where losses in the same area of expenditure have been measured and re-measured. This outlines:

. the level of losses when first measured and the level of losses when last measured after efforts to reduce them.

Finally, sector-based analysis shows: . the level of losses in key sectors where the most data exists: healthcare and social

security.

There is more research still to be done and it is intended that this paper will be updated on a regular basis to show trends in fraud losses.

Fraud and error losses It would now seem appropriate to explore some of the findings from the analysis of the fraud measurement exercises studied. The first area is the PLR. The 132 exercises found the PLR was found to be between 0.13 and 10.60 per cent with an average PLR of 4.57 per cent as shown in Figure 2. To further analyse this the authors broke this down into exercises showing less than 3, 3-8 and over 8 per cent. As Figure 3 shows 66 per cent

Figure 3. Percentage losses by amount

PERCENTAGE LOSS < 3%

PERCENTAGE LOSS > 8%

PERCENTAGE LOSS 3-8% 46.88%

18.75% 34.38%

Figure 2. Average percentage losses to fraud and error

12.00%

10.00%

8.00%

6.00%

4.00%

2.00%

0.00% 0.13%

4.57%

10.60%

LOWEST PERCENTAGE LOSS

AVERAGE PERCENTAGE LOST

HIGHEST PERCENTAGE LOSS

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of the exercises showed PLR figures of more than 3 per cent with almost 19 per cent with a PLR over 8 per cent.

The next criteria assessed was the FFR. The range of FFR was found to be between 0.47 and 9.6 per cent with an average FFR of 4.28 per cent as shown in Figure 4. There was a much more common grouping on this criteria with 90 per cent of exercises assessed recording an FFR of 3-8 per cent, only 1.67 per cent over 8 per cent as shown in Figure 5. Given the dominance of the 3-8 per cent this may suggest that a fraud and error rate of between 3 and 8 per cent is the norm.

A significant finding was that organizations that repeated the fraud measurement exercises tended to a show a reduction in the PLR. The average PLR when first measured has been found to be 5.40 per cent; the average PLR when last measured was found to be 4.61 per cent as shown in Figure 6. This represents an average reduction of just under 15 per cent. The authors would argue that once an organization discovers an accurate measure of fraud losses this acts as an incentive and spur to introduce measures to reduce fraud losses. It also shows fraud can be reduced and that in many organizations a saving of 15 per cent fraud losses would amount to a significant sum of money.

Figure 4. Average FFRs

12.00%

10.00%

8.00%

6.00%

4.00%

2.00%

0.00% 0.47%

4.28%

9.60%

LOWEST FRAUD RATE AVERAGE FRAUD RATE HIGHEST FRAUD RATE

Figure 5. FFRs by amount

90.00%

1.67% 8.33%

FRAUD RATE <3%

FRAUD RATE 3-8%

FRAUD RATE >8%

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There is also considerable data available from two area of public expenditure – healthcare and social security. In respect of healthcare, the average PLR is 5.59 per cent and the average FFR is 4.23 per cent. As discussed above this does tend to show that healthcare fraud involves higher than average value items of expenditure. A paper with a detailed analysis of the healthcare fraud data will be published subsequently. In respect of social security, the average PLR is 5.57 per cent and the average FFR is 2.1 per cent. Like healthcare, this does tend to show that social security fraud also involves higher than average value items of expenditure.

On the basis of the evidence, it is clear that fraud and error losses in any 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. However, it would be wrong to go too much further in terms of predicting where in this range, losses for each type of expenditure measured, will be. This is because, other than in respect of healthcare and social security, the volume of data does not warrant this. Also, each organisation will have either relatively stronger or relatively weaker counter fraud arrangements. This factor will affect where within the range of expected losses, a particular organisation will find itself. The authors intend to publish further research assessing the effectiveness of organizations to counter fraud based upon 28 key aspects of a counter fraud strategy as advocated by the CIPFA guidance.

Most organizations do not undertake regular fraud risk measurement exercises (Brooks et al., 2009). There are therefore lots of bodies who do not know the true extent of their fraud losses. This means there is expenditure been made which does not need to be, which if discovered and dealt with could be released for other services or provide greater profitability. If organizations accurately measure the costs of fraud and error on a regular basis it clearly incentivizes an organization to manage that cost, like any other cost. Fraud and error are clearly problems that any organization would want to reduce. Therefore, the papers finding that those who do regularly measure fraud tend to show a reduction in it is not surprising. Accurately measuring fraud and error clearly provides a basis for reaping a competitive advantage. There are examples,

Figure 6. Average losses compared from first to last measurement

5.60%

5.40%

5.40%

4.61%

5.20%

5.00%

4.80%

4.60%

4.40%

4.20% AVERAGE LOSSES WHEN FIRST

MEASURED AVERAGE LOSSES WHEN LAST

MEASURED

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especially in the UK and the USA, where this approach has been proven to reap benefits. These include:

. the UK’s National Health Service (the second largest organisation in the world) between 1998 and 2006 where losses were reduced by up to 60 per cent, and by up to 40 per cent over a shorter period (NHSCFSMS, 2007);

. the US Department for Education, which reduced its losses across a $12 billion grant program by 35 per cent between 2001 and 2005 (United States Department of Education, 2001, 2005);

. the US Department of Agriculture, which reduced its losses across a $12 dollar program by 28 per cent between 2002 and 2004 (United States Department of Agriculture, 2002, 2003, 2004); and

. the UK’s Department of Work and Pensions which has successfully reduced its losses in Income Support and Job Seekers Allowance by more than 50 per cent since 1997/1998 (Department for Work and Pensions, 2007).

Conclusion This is the first paper in an area where, for too long, the accurate measurement of losses has been considered either impossible or too difficult. It proves that this is wrong. Losses to fraud and error can now be treated as a business cost like any other – to be tracked and reduced. It is also the case that work to measure losses can be highly cost effective. The extent to which efforts to reduce losses are helped by greater knowledge about the problem is shown by the significantly lower (15 per cent) average level of losses where they have been re-measured over a period of time, in the same area of expenditure.

There are a number of key findings which emerge from this research. First, losses to fraud and error can be measured – and cost effectively. Second, on the basis of the evidence it is likely that losses in any organisation and any area of expenditure will be at least 3 per cent, probably more than 5 per cent and possibly more than 9 per cent. Finally, with the benefit of accurate information about their nature and extent, fraud and error can be reduced significantly. In a troubled economic climate, not to consider the financial benefits of making relatively painless reductions in losses to fraud and error seems rather foolhardy. Fraud should be treated like any other cost a holistic approach introduced to counter it and this can reap financial benefits which in some sectors could amount to a new competitive advantage.

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About the authors Mark Button is a Reader in Criminology and Director of the Centre for Counter Fraud Studies at the University of Portsmouth. He holds a degree from Exeter University, a Master’s from Warwick University and a PhD from the London School of Economics. Mark Button is the corresponding author and can be contacted at: [email protected]

Jim Gee is Director of Counter Fraud Services at MacIntyre Hudson LLP and Chair of the Advisory Board of the Centre for Counter Fraud Studies. He has worked for KPMG and was also Chief Executive of the National Health Service Counter Fraud and Security Management Service.

Graham Brooks is a Senior Lecturer with research interests in gambling and counter fraud. He is also course leader for the BSc (Hons) in Counter Fraud and Criminal Justice Studies and the MSc in Counter Fraud and Counter Corruption Studies. He holds a degree from Leeds Metropolitan University and an MPhil from Cambridge University.

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