world corrupt report 2011

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REPORT TO THE NATIONSO N O C C U P A T I O N A L F R A U D A N D A B U S E

2010 Global Fraud Study


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2 | 2010 RepoRt to the NAtioNs ON OccuPATIONAl FRAUD ANd AbuSE

Lr rm prdn

When the ACFE published its rstReport to the Nation on Occupational Fraud and Abuse in 1996,

it broke new ground in anti-raud research by providing an analysis o the costs, the methodologies

and the perpetrators o raud within U.S. organizations. The collective body o knowledge con-

tained in the rst ve editions o the Report to the Nation published between 1996 and 2008

has become the most authoritative and widely quoted research publication on occupational

raud.

Now, or the rst time, the data contained in the Report have been drawn rom raud cases

throughout the world. As readers will see, it refects the truly universal nature o occupational raud. This expansion o

our research is denoted in the modied title or this study, which has now become the Report to the Nations on Occu-

pational Fraud and Abuse.

The inormation contained in this report is based on 1,843 cases o occupational raud that were reported by the Certied

Fraud Examiners (CFEs) who investigated them. These oenses occurred in more than 100 countries on six continents,

and more than 43% took place outside the United States. What is perhaps most striking about the data we gathered is

how consistent the patterns o raud are around the globe. While some regional dierences exist, or the most part oc-

cupational raud seems to operate similarly whether it occurs in Europe, Asia, South America or the United States.

The Report to the Nations is the brainchild o the ACFEs ounder and Chairman, Dr. Joseph T. Wells, CFE, CPA who

throughout his career has contributed more to the study o raud and the development o the anti-raud proession than

any other person. On behal o the ACFE, and in honor o its ounder, Dr. Wells, I am pleased to present the2010 Report to

the Nations on Occupational Fraud and Abuse to practitioners, business and government organizations, academics, the

media and the general public throughout the world. The inormation contained in this Report will be invaluable to those

who seek to deter, detect, prevent or simply understand the global economic impact o occupational raud.

James D. Ratley, CFE

President,

Association o Certied Fraud Examiners


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2010 RepoRt to the NatioNs on occupational FRaud and abuse |

Table of Contents

exv smmry .............................................................................................................................................................4

ir ..........................................................................................................................................................................6

th c f o Fr ..........................................................................................................................................8

DistributionofLosses

Hw o Fr i cmm ............................................................................................................................10

AssetMisappropriationSub-Schemes

DurationofFraudSchemes

d f Fr shm .............................................................................................................................................16

InitialDetectionofOccupationalFraudSchemes

SourceofTips

ImpactofHotlines

DetectionMethodsBasedonOrganizationType

DetectingFraudinSmallBusinesses

DetectionofOccupationalFraudBasedonRegion

Vm orgz ..........................................................................................................................................................24

GeographicalLocationofOrganizations

TypeofOrganizations

SizeofOrganizations

MethodsofFraudinSmallBusinesses

IndustryofOrganizations

Anti-FraudControlsatVictimOrganizations Anti-FraudControlsatSmallBusinesses

Anti-FraudControlsbyRegion

EffectivenessofControls

ImportanceofControlsinDetectingorLimitingFraud

ControlWeaknessesthatContributedtoFraud

ModicationofControls

prrr ........................................................................................................................................................................48

PerpetratorsPosition

PerpetratorsGender

PerpetratorsAge

PerpetratorsTenure

PerpetratorsEducationLevel PerpetratorsDepartment

PerpetratorsCriminalandEmploymentHistory

BehavioralRedFlagsDisplayedbyPerpetrators

Mhgy ......................................................................................................................................................................75

ax brkw f Ggrh Rg y cry ..........................................................................................78

Fr prv chk ................................................................................................................................................80

a h acFe ..................................................................................................................................................................82


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summary Fndng

Survey participants estimated that the typicalorganization loses 5% o its annual revenue toraud. Applied to the estimated 2009 Gross WorldProduct, this gure translates to a potential totalraud loss o more than $2.9 trillion.

The median loss caused by the occupationalraud cases in our study was $160,000. Nearlyone-quarter o the rauds involved losses o atleast $1 million.

The rauds lasted a median o 18 months beorebeing detected.

Asset misappropriation schemes were the mostcommon orm o raud in our study by a widemargin, representing 90% o cases though theywere also the least costly, causing a median losso $135,000. Financial statement raud schemeswere on the opposite end o the spectrum in bothregards: These cases made up less than 5% othe rauds in our study, but caused a median losso more than $4 million by ar the most costlycategory. Corruption schemes ell in the middle,

comprising just under one-third o cases andcausing a median loss o $250,000.

Occupational rauds are much more likely to bedetected by tip than by any other means. Thisnding has been consistent since 2002 when webegan tracking data on raud detection methods.

Small organizations are disproportionatelyvictimized by occupational raud. Theseorganizations are typically lacking in anti-raudcontrols compared to their larger counterparts,which makes them particularly vulnerable to raud.

The industries most commonly victimized in our

study were the banking/nancial services,manuacturing and government/publicadministration sectors.

Anti-raud controls appear to help reduce the costand duration o occupational raud schemes. Welooked at the eect o 15 common controls onthe median loss and duration o the rauds. Victimorganizations that had these controls in place hadsignicantly lower losses and time-to-detection thanorganizations without the controls.

High-level perpetrators cause the greatestdamage to their organizations. Frauds commit-ted by owners/executives were more than threetimes as costly as rauds committed by managers,and more than nine times as costly as employeerauds. Executive-level rauds also took muchlonger to detect.

excuv summary

This Report is based on data

compiled from a study of 1,843

cases of occupational fraud that

occurred worldwide between

January 2008 and December

2009. All information was pro-

vided by the Certied Fraud Ex-aminers (CFEs) who investigated

those cases. The fraud cases in

our study came from 106 nations

with more than 40% of cases

occurring in countries outside

the United States providing a

truly global view into the plague

of occupational fraud.

One-fourth of the frauds in this Reportcaused at least $1 million in losses.


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2010 RepoRt to the NAtioNs ON OccuPATIONAl FRAUD ANd AbuSE |

More than 80% o the rauds in our studywere committed by individuals in one o sixdepartments: accounting, operations, sales,executive/upper management, customer serviceor purchasing.

More than 85% o raudsters in our study hadnever been previously charged or convicted ora raud-related oense. This nding is consistentwith our prior studies.

Fraud perpetrators oten display warning signs

that they are engaging in illicit activity. The mostcommon behavioral red fags displayed by theperpetrators in our study were living beyond theirmeans (43% o cases) and experiencing nancialdiculties (36% o cases).

Cnclun and Rcmmndan

Occupational raud is a global problem. Thoughsome o our ndings dier slightly rom region toregion, most o the trends in raud schemes, per-petrator characteristics and anti-raud controls aresimilar regardless o where the raud occurred.

Fraud reporting mechanisms are a criticalcomponent o an eective raud prevention anddetection system. Organizations should implementhotlines to receive tips rom both internal andexternal sources. Such reporting mechanismsshould allow anonymity and condentiality, andemployees should be encouraged to reportsuspicious activity without ear o reprisal.

Organizations tend to over-rely on audits. Externalaudits were the control mechanism most widelyused by the victims in our survey, but they rankedcomparatively poorly in both detecting raud andlimiting losses due to raud. Audits are clearly

important and can have a strong preventativeeect on raudulent behavior, but they should notbe relied upon exclusively or raud detection.

Employee education is the oundation opreventing and detecting occupational raud.Sta members are an organizations top rauddetection method; employees must be trained inwhat constitutes raud, how it hurts everyone inthe company and how to report any questionableactivity. Our data show not only that most raudsare detected by tips, but also that organizationsthat have anti-raud training or employees andmanagers experience lower raud losses.

Surprise audits are an eective, yet underutilized,tool in the ght against raud. Less than 30% ovictim organizations in our study conductedsurprise audits; however, those organizationstended to have lower raud losses and to detectrauds more quickly. While surprise audits can beuseul in detecting raud, their most importantbenet is in preventing raud by creating a percep-tion o detection. Generally speaking, occupationalraud perpetrators only commit raud i theybelieve they will not be caught. The threat osurprise audits increases employees perception

that raud will be detected and thus has a strongdeterrent eect on potential raudsters.

Small businesses are particularly vulnerable toraud. In general, these organizations have ar ewercontrols in place to protect their resources romraud and abuse. Managers and owners o smallbusinesses should ocus their control investmentson the most cost-eective mechanisms, suchas hotlines and setting an ethical tone or theiremployees, as well as those most likely to helpprevent and detect the specic raud schemes thatpose the greatest risks to their businesses.

Internal controls alone are insucient to ully

prevent occupational raud. Though it is importantor organizations to have strategic and eectiveanti-raud controls in place, internal controls willnot prevent all raud rom occurring, nor will theydetect most raud once it begins.

Fraudsters exhibit behavioral warning signs o theirmisdeeds. These red fags such as living beyondones means or exhibiting control issues will notbe identied by traditional controls. Auditors andemployees alike should be trained to recognize thecommon behavioral signs that a raud is occurringand encouraged not to ignore such red fags, as

they might be the key to detecting or deterring araud.

Given the high costs o occupational raud,eective raud prevention measures are critical.Organizations should implement a raud preventionchecklist similar to that on page 80 in order to helpeliminate raud beore it occurs.


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A wide variety o crimes and swindles all under the um-

brella o raud. From Ponzi schemes and identity thet to

data breaches and alsied expense reports, the ways

perpetrators attempt to part victims rom their money are

extremely diverse and continually evolving. At their core,

however, all rauds involve a violation o trust.

For businesses, no trust violations have the potential to be

as harmul as those committed by the very individuals who

are relied upon to make the organization successul: its

employees. This report ocuses on the category o raud

occupational raud in which an employee abuses his

or her position within the organization or personal gain.

More ormally, occupational raud may be dened as:

The use of ones occupation for personal enrichment

through the deliberate misuse or misapplication of

the employing organizations resources or assets.

This denition is very broad, encompassing a wide rangeo misconduct by employees at every organizational level.

Occupational raud schemes can be as simple as pilerage

o company supplies or manipulation o timesheets, or as

complex as sophisticated nancial statement rauds.

One o the ACFEs primary missions is to educate anti-

raud proessionals and the general public about the seri-

ous threat occupational raud poses. To that end, we have

undertaken extensive research to provide an in-depth look

at the costs and trends in occupational raud. In 1996, theACFE released its Report to the Nation on Occupational

Fraud and Abuse, which was the largest known privately

unded study on the subject at the time.

The stated goals o the rst Report were to:

Summarize the opinions o experts on the percentage and amount o organizational revenue lost to allorms o occupational raud and abuse.

Examine the characteristics o the employees whocommit occupational raud and abuse.

Determine what kinds o organizations are victimso occupational raud and abuse.

Categorize the ways in which serious raud andabuse occur.

Since the inception o the Report to the Nation more than

a decade ago, we have released ve updated editions in

2002, 2004, 2006, 2008 and the current version in 2010. Like

the rst Report, each subsequent edition has been based

on detailed case inormation provided by Certied Fraud Ex-

aminers (CFEs). With each new edition o the Report, we

add to and modiy the questions we ask o our survey par-

ticipants in order to enhance the quality o the data we col-

lect. This evolution o theReport to the Nation has enabled

us to continue to draw more meaningul inormation rom

the experiences o CFEs and the rauds they encounter.

In our 2010 Report, we have, or the rst time ever, wid-

ened our study to include cases rom countries outside

the United States. This expansion allows us to more ully

explore the truly global nature o occupational raud and

provides an enhanced view into the severity and impact

o these crimes. Additionally, we are able to compare the

anti-raud measures taken by organizations worldwide inorder to give raud ghters everywhere the most appli-

cable and useul inormation to help them in their raud

prevention and detection eorts.

inrducn

A N Radr: Throughout this Report, we have included several comparisons o our current ndings with those rom our 2008 Report. However, it is important to note thatthe 2010 data include reported rauds rom CFEs in 106 countries, while the 2008 data pertain to rauds reported only by CFEs in the United States. Although the populations orespondents or the two studies are not entirely analogous, we have nonetheless included these prior-study comparisons, as we believe interesting and useul trends can be seenby comparing and contrasting the rauds reported in the two studies. To enhance data clarity, we have included comparisons o 2008 data with both all-case data and U.S.-only datarom our 2010 research when noteworthy discrepancies in our current ndings are present.


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Opationa Fra an Ase cassifation System

Corruption

Conflicts ofInterest

Cash

FraudulentDisbursements

PurchasingSchemes

SalesSchemes

Bid Rigging

OtherOther

Larceny Skimming Misuse Larceny

AssetRequisitionsand Transfers

False Salesand Shipping

Purchasingand Receiving

UnconcealedLarceny

Sales

Unrecorded Write-offSchemes

LappingSchemes

Unconcealed

Understated

ReceivablesRefunds

and Other

Other

Cash onHand

From theDeposit

Billing Schemes Payroll SchemesExpense

ReimbursementSchemes

Check TamperingRegister

Disbursements

Forged Maker False Voids

False RefundsForged

Endorsement

ConcealedChecks

AuthorizedMaker

Altered Payee

MischaracterizedExpenses

GhostEmployees

CommissionSchemes

OverstatedExpenses

FictitiousExpenses

MultipleReimbursements

WorkersCompensation

Falsified Wages

Shell Company

Non-AccompliceVendor

PersonalPurchases

InvoiceKickbacks

Asset/RevenueOverstatements

TimingDifferences

FicticiousRevenues

ImproperDisclosures

ConcealedLiabilities and

Expenses

ImproperAsset

Valuations

Asset/RevenueUnderstatements

EmploymentCredentials

InternalDocuments

ExternalDocuments

IllegalGratuities

EconomicExtortion

Non-Cash

Non-Financial

Bribery Financial

AssetMisappropriation

FraudulentStatements


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Measuring the cost o occupational raud is an important,

yet incredibly challenging, endeavor. Arguably, the true

cost is incalculable. The inherently clandestine nature

o raud means that many cases will never be revealed,

and, o those that are, the ull amount o losses might not

be uncovered, quantied or reported. Consequently, any

measurement o occupational raud costs will be, at best,

an estimate. Nonetheless, determining such an approxi-

mation is critical to illustrate the pandemic and destruc-

tive nature o white-collar crime.

We asked each CFE who participated in our survey to pro-

vide his or her best estimate o the percentage o annual

revenues that the typical organization loses to raud in a

given year. The median response was that the average

organization annually loses 5% o its revenues to raud.

Applying this percentage to the 2009 estimated Gross

World Product o $58.07 trillion1 would result in a pro-

jected total global raud loss o more than $2.9 trillion.

Readers should note that this estimate is based solely

on the opinions o 1,843 anti-raud experts, rather than

any specic data or actual observations; accordingly, it

should not be interpreted as a literal representation o the

worldwide cost o occupational raud. However, because

there is no way to precisely calculate the size o global

raud losses, the best estimate o anti-raud proession-

als with a rontline view o the problem may be as reli-

able a measure as we are able to make. In any event, it

is undeniable that the overall cost o occupational raud

is immense, certainly costing organizations hundreds o

billions or trillions o dollars each year.

t C occuanal Fraud

1United States Central Intelligence Agency, The World Factbook (https://www.cia.gov/library/publications/the-world-actbook/geos/xx.html)

Fraud, by its very nature, does

not lend itself to being scien-

tically observed or measured

in an accurate manner. One of

the primary characteristics of

fraud is that it is clandestine,

or hidden; almost all fraud in-volves the attempted conceal-

ment of the crime.

The typical organization loses 5% of itsannual revenues to occupational fraud.


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Drbun L

We received inormation about the total dollar loss or 1,822 o the 1,843 rauds reported to us in our study.2 The median

loss or these cases was $160,000. Nearly one-third o the raud schemes caused a loss to the victim organization o

more than $500,000, and almost one-quarter o all reported cases topped the $1 million threshold.

distrition o doar losses

2Although this Report includes raud cases rom more than 100 nations, all monetary amounts presented throughout this Report are in U.S. dollars.

0%

5%

10%

15%

20%

25%

30%

$1,000,000and up

$500,000 $999,999

$100,000 $499,999

$50,000 $99,999

$10,000 $49,999

$1,000 $9,999

Less than$1,000

Dollar Loss

PercentofCases

2.4%

7.2%

18.4%

10.6%

29.3%

8.4%

23.7%


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Previous ACFE research has identied three primary cat-

egories o occupational raud used by individuals to de-

raud their employers.Asset misappropriations are those

schemes in which the perpetrator steals or misuses an

organizations resources. These rauds include schemes

such as skimming cash receipts, alsiying expense re-

ports and orging company checks.

Corruption schemes involve the employees use o his orher infuence in business transactions in a way that vio-

lates his or her duty to the employer or the purpose o

obtaining a benet or him- or hersel or someone else.

Examples o corruption schemes include bribery, extor-

tion and a confict o interest.

Financial statement fraud schemes are those involving

the intentional misstatement or omission o material in-

ormation in the organizations nancial reports. Common

methods o raudulent nancial statement manipulation

include recording ctitious revenues, concealing liabili-

ties or expenses and articially infating reported assets.

As indicated in the ollowing charts, asset misappropriations

are by ar both the most requent and the least costly orm

o occupational raud. On the other end o the spectrum are

cases involving nancial statement raud. These schemes

were present in less than 5% o the cases reported to us,

but caused a median loss o more than $4 million. Corrup-

tion schemes ell in the middle category in both respects,

occurring in just under one-third o all cases involved in our

study and causing a median loss o $250,000.

hw occuanal Fraud i Cmmd

Based on previous ACFE

research we have broken down

the schemes reported to us

into three primary categories:

asset misappropriation,

corruption, and nancial

statement fraud.

Financial statement fraud is the mostcostly form of occupational fraud, causinga median loss of more than $4 million.


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Opationa Fras y category Freqeny3

Opationa Fras y category Meian loss

3The sum o percentages in this chart exceeds 100% because several cases involved schemes rom more than one category.

0% 20% 40% 60% 80% 100%

2010

2008

Financial

Statement Fraud

Corruption

Asset

Misappropriation88.7%

32.8%

10.3%

86.3%

26.9%

4.8%

Percent of Cases

Typ

e

ofFraud

$0 $1,000,000 $2,000,000 $3,000,000 $4,000,000 $5,000,000

2010

2008


Corruption

FinancialStatement Fraud

Median Loss

Type

ofFraud

$4,100,000

$2,000,000

$250,000

$135,000

$150,000

$375,000


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As previously mentioned, our 2010 data include raud cases rom countries throughout the world, while our 2008 data

contain only U.S.-based cases. In the ollowing charts, we isolated the U.S. cases rom our current study to make a more

direct comparison to our 2008 data. Interestingly, while nancial statement raud remained the least common and most

costly orm o raud among U.S. cases, there was a much lower percentage o nancial statement cases in this study

(our percent) as compared to 2008 (ten percent). Additionally, the median losses or all three categories o raud were

notably smaller in 2010 than they were in 2008.


Opationa Fras y category (u.S. ony) Freqeny4


0% 20% 40% 60% 80% 100%

2010

2008

Financial

Statement Fraud

Corruption

Asset

Misappropriation88.7%

21.9%

10.3%

89.8%

26.9%

4.3%

Percent of Cases

Type

ofFraud


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In addition to observing the requency and median losses

caused by the three categories o raud, we analyzed the

proportion o the total losses suered based on scheme

category. The cases in our study represented a combined

total loss o more than $18 billion. As indicated in the chart

to the right, o the total reported losses that were attribut-

able to a specic scheme type, 21% were caused by asset

misappropriation schemes, 11% by corruption and 68%

by raudulent nancial statements.

Opationa Fras y category (u.S. ony) Meian loss

Perent o Tota Reporte doar losses

$0 $500,000 $1,000,000 $1,500,000 $2,000,000

2010

2008


Corruption

FinancialStatement Fraud

Median Loss

Typ

e

ofFraud

$1,730,000

$2,000,000

$175,000

$100,000

$150,000

$375,000

Financial Statement Fraud

68.0%

Asset Misappropriation

20.8%

Corruption

11.3%


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A Marran sub-scm

With nearly 90% o occupational rauds involving some orm o asset misappropriation, it is instructional to urther de-

lineate the methods used by employees to embezzle organizational assets. We divided asset misappropriation schemes

into nine sub-categories, as illustrated in the table on page 15. The rst eight sub-categories represent schemes target-

ing cash; these rauds account or approximately 85% o all asset misappropriations.

Two o the sub-schemes skimming and cash larceny involve pilering incoming cash receipts, such as sales revenues

and accounts receivable collections. The next ve sub-categories billing, expense reimbursement, check tampering,

payroll and raudulent register disbursement schemes involve raudulent disbursements o cash. The eighth orm o

cash misappropriation targets cash the organization has on hand, such as petty cash unds or cash in a vault. The nal

sub-category o asset misappropriations covers the thet or misuse o non-cash assets, including inventory, supplies, xed

assets, investments, intellectual property and proprietary inormation. The table on page 15 provides the requency and

median loss associated with each asset misappropriation sub-category.

Duran Fraud scm

In addition to examining the monetary cost o the raud cases reported to us, we analyzed the length o time these schemes

lasted beore being detected. The median duration the time period rom when the raud rst occurred to when it was

discovered or all cases in our study was 18 months. Not surprisingly, cases involving nancial statement raud the

most costly orm o raud lasted the longest, with a median duration o 27 months. Fraudulent register disbursements,

on the other hand, were not only the least costly orm o raud in our study, but also tended to be detected the soonest.

Meian dration o Fra base on Sheme Type

0 5 10 15 20 25 30

Register Disbursement

Non-Cash

Larceny

Skimming

Cash on Hand

Corruption

Billing

Payroll

Expense Reimbursements

Check Tampering

Financial Statement Fraud 27

24

24

24

24

18

18

18

18

15

12

Median Months to Detection

SchemeType


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Asset Misappropriation S-categories

Cagry Dcrn examlCa

Rrd

prcn

all ca5Mdan

L

scm invlvng t Ca Rc

Skimming Any scheme in which cash is stolen roman organizationbefore it is recorded on theorganizations books and records

Employee accepts payment rom acustomer, but does not record the sale,and instead pockets the money

267 14.5% $60,000

Cash Larceny Any scheme in which cash is stolen roman organizationafterit has been recordedon the organizations books and records

Employee steals cash and checks romdaily receipts beore they can bedeposited in the bank

181 9.8% $100,000

scm invlvng Frauduln Dburmn Ca

Billing Any scheme in which a person causeshis employer to issue a payment bysubmitting invoices or ctitious goods orservices, infated invoices or invoices orpersonal purchases

Employee creates a shell company andbills employer or services not actuallyrendered

Employee purchases personal itemsand submits invoice to employer or

payment

479 26.0% $128,000

ExpenseReimbursements

Any scheme in which an employee makesa claim or reimbursement o ctitious orinfated business expenses

Employee les raudulent expensereport, claiming personal travel,nonexistent meals, etc.

278 15.1% $33,000

Check Tampering Any scheme in which a person steals hisemployers unds by intercepting, orgingor altering a check drawn on one o theorganizations bank accounts

Employee steals blank companychecks, makes them out to himsel oran accomplice

Employee steals outgoing check to avendor, deposits it into his own bankaccount

274 13.4% $131,000

Payroll Any scheme in which an employee causeshis employer to issue a payment bymaking alse claims or compensation

Employee claims overtime or hours notworked

Employee adds ghost employees to thepayroll

157 8.5% $72,000

Cash Register

Disbursements

Any scheme in which an employee makes

alse entries on a cash register to concealthe raudulent removal o cash

Employee raudulently voids a sale on

his cash register and steals the cash

55 3.0% $23,000

or A Marran scm

Cash on HandMisappropriations

Any scheme in which the perpetratormisappropriates cash kept on hand at thevictim organizations premises

Employee steals cash rom a companyvault

121 12.6% $23,000

Non-CashMisappropriations

Any scheme in which an employee stealsor misuses non-cash assets o the victimorganization

Employee steals inventory rom awarehouse or storeroom

Employee steals or misuses condentialcustomer nancial inormation

156 16.3% $90,000

5The sum o percentages in this table exceeds 100% because several cases involved asset misappropriation schemes rom more than one category.

N: Because asset misappropriation schemes are both so common and so diverse in their methods, or the remainder

o the Report, we will break down our analysis o the raud schemes into 11 categories corruption, nancial statement

raud and the nine sub-categories o asset misappropriation so as to provide a meaningul understanding o the ull

spectrum o ways in which employees deraud their employing organizations.


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One o the principal goals o our research is to identiy

how past rauds were detected so that organizations can

apply that knowledge to their uture anti-raud eorts.

Tips were by ar the most common detection method in

our study, catching nearly three times as many rauds as

any other orm o detection. This is consistent with the

ndings in our prior reports. Tips have been ar and away

the most common means o detection in every study

since 2002, when we began tracking the data.

Management review and internal audit were the second

and third most common orms o detection, uncovering

15% and 14% o rauds, respectively. It is also noteworthy

that 11% o rauds were detected through channels that

lie completely outside o the traditional anti-raud control

structure: accident, police notication and conession. In

other words, 11% o the time, the victim organization ei-

ther had to stumble onto the raud or be notied o it by a

third party in order to detect it.

Dcn Fraud scm

Initia detetion o Opationa Fras

Respondents to our survey

were asked to identify how the

frauds were rst discovered.

Three times as many frauds in

our study were uncovered by a

tip as by any other method.

Frauds are much more likely to bedetected by tips than by any other method.

0% 10% 20% 30% 40% 50%

IT Controls

Confession

Notified by PoliceSurveillance/Monitoring

External Audit

Document Examination

Account Reconciliation

By Accident

Internal Audit

Management Review

Tip 40.2%

15.4%

13.9%

8.3%

6.1%

5.2%

4.6%

2.6%

1.8%

1.0%

0.8%

Percent of Cases

Dete

ctionMethod


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surc t

Not surprisingly, employees were the most common

source o raud tips. However, customers, vendors, com-

petitors and acquaintances (i.e., non-company sources)

provided at least 34% o raud tips, which suggests that

raud reporting policies and programs should be publi-

cized not only to employees, but also to customers, ven-

dors and other external stakeholders.

imac Annymu Rrng

Mcanm (hln)

While tips have consistently been the most common way

to detect raud, the impact o tips is, i anything, understat-

ed by the act that so many organizations ail to implement

raud reporting systems. Such systems enable employees

to anonymously report raud or misconduct by phone or

through a web-based portal.6 The ability to report raud

anonymously is key because employees oten ear making

reports due to the threat o retaliation rom superiors ornegative reactions rom their peers. Also, most third-party

hotline systems oer programs to raise awareness about

how to report misconduct. Consequently, one would ex-

pect that the presence o a raud hotline would enhance

raud detection eorts and oster more tips.

This turns out to be true. As seen on page 18, the pres-

ence o raud hotlines correlated with an increase in the

number o cases detected by a tip. In organizations that

had hotlines, 47% o rauds were detected by tips, while

in organizations without hotlines, only 34% o cases were

detected by tips. This is important because tips have

repeatedly been shown to be the most eective way to

catch raud. The better an organization is at collecting andresponding to raud tips, the better it should be at detect-

ing raud and limiting losses.

In 67% o the cases where there was an anonymous

tip, that tip was reported through an organizations raud

hotline. This strongly suggests that hotlines are an eec-

tive way to encourage tips rom employees who might oth-

erwise not report misconduct. Perhaps most important, as

noted on page 43, organizations that had raud hotlines su-

ered much smaller raud losses than organizations without

hotlines. Those organizations also tended to detect rauds

seven months earlier than their counterparts.

6For simplicitys sake, we will reer to all reporting mechanisms as hotlines in this study.

0%

10%

20%

30%

40%

50%

Perp

etrator's

Acquaintan

ce

Compe

titor

Shar

eholde

r/

Owne

rVe

ndor

Anon

ymou

s

Custom

er

Employ

ee

49.2%

17.8%

13.4%12.1%

3.7%2.5% 1.8%

Source of Tips

P

ercentofTips

Sore o Tips


18/84


Dcn Md Bad n organzan ty

The chart on page 19 shows how rauds were detected based on the victims organization type. We see that privately

owned companies tended to have the ewest rauds detected by tip and the most rauds caught by accident, both o

which were also true in our 2008 study. Publicly held companies tended to detect more rauds by management review

and internal audit than their counterparts. Government agencies had the highest rate o detection by tips and had a pro-

portionately high rate o rauds caught through external audit.

Dcng Fraud n small BunSmall businesses historically tend to suer disproportionately high occupational raud losses, according to our previ-

ous reports. The trend was not as pronounced in this study as in past years, but we still saw that 31% o all occupa-

tional rauds were committed against small businesses (the highest rate o any category) and the median loss in those

schemes was $155,000 (see page 29). One reason that small businesses are particularly good targets or occupational

raud is that they tend to have ar ewer anti-raud controls than larger organizations (see page 39).

Dcn Fraud scm

Impat o Hotines

0% 10% 20% 30% 40% 50%

Organizations With Hotlines

Organizations Without Hotlines

Confession

Notified by Police

IT Controls

External Audit

Surveillance/Monitoring


By Accident

Account Reconcilliation

Management Review

Internal Audit

Tip

Percent of Cases

DetectionMethod

47.1%

33.8%

15.7%

15.7%

16.5%

11.2%

4.6%

4.7%

7.8%

3.7%

1.4%

3.0%

1.0%

0.9%

1.4%

2.2%

2.3%

1.1%

0.4%

6.5%

7.3%

11.9%


19/84


When we look at how small businesses detect rauds, it is apparent that they catch a much lower proportion o schemes

through tips or internal audits than larger organizations. According to the chart on page 20, only 33% o small business

rauds are detected by a tip, and only 8% are detected by an internal audit. Additionally, a relatively large percentageo rauds are caught by accident at small companies nearly twice as many as at larger organizations. Many o these

discrepancies are likely due to the low rates o control implementation at small businesses.

Initia detetion Metho y Organization Type

0% 10% 20% 30% 40% 50%

Government

Public Company

Private Company

Not-for-Profit

IT Controls

Confession

Notified by Police


External Audit


Account Reconcilliation

By Accident

Internal Audit

Management Review

Tip

Percent of Cases

DetectionMethod

43.2%

13.0%

10.7%

6.5%

8.9%

6.5%

6.5%

1.2%

1.8%

1.2%

0.6%

15.4%

11.6%

11.2%

8.2%

6.0%

5.2%

2.6%

2.5%

1.0%

0.5%

17.6%

16.7%

6.8%

3.9%

5.0%

2.3%

3.0%

1.2%

1.1%

1.2%

11.6%

15.1%

5.3%

4.6%

3.9%

7.4%

2.8%

1.4%

1.4%

0.4%

35.8%41.1%

46.3%


20/84


Dcn Fraud scm

Initia detetion o Fras in Sma bsinesses

Dcn occuanal Fraud Bad n Rgn

The ollowing charts show how rauds were detected based on the region in which they occurred.7 In every region, tips

were responsible or detecting the most occupational rauds by a wide margin. The percentage o cases detected by tips

ranged rom a high o 50% (in Arica) to a low o 38% (in the United States). In all but two regions, management review

and internal audit were the second and third most common means o detection, ollowing tips.

detetion in the unite States 1,001 cases

7See Appendix or a listing o countries included in each region.

0% 10% 20% 30% 40% 50%

100+ Employees


21/84


detetion in Asia 293 cases

detetion in Erope 155 cases

0% 10% 20% 30% 40% 50%

IT Controls

Notified by PoliceConfession




External Audit

By Accident

Management Review

Internal Audit

Tip 42.3%

11.3%

14.3%

8.9%

5.5%

4.4%

5.8%

2.7%

1.7%

2.4%

0.7%

Percent of Cases

D

etectionMethod

0% 10% 20% 30% 40% 50%

Confession

IT Controls

Notified by Police


External Audit



By Accident

Management Review

Internal Audit

Tip 40.0%

16.1%

17.4%

6.5%

5.8%

5.2%

3.9%

3.2%

1.3%

0.0%

0.6%

Percent of Cases

DetectionMethod


22/84


Dcn Fraud scm

detetion in Aria 111 cases

detetion in canaa 97 cases

0% 10% 20% 30% 40% 50%

IT Controls

ConfessionDocument Examination

External Audit

Notified by Police



By Accident

Internal Audit

Management Review

Tip 49.5%

11.7%

9.9%

9.0%

6.3%

0.9%

1.8%

5.4%

4.5%

0.9%

0.0%

Percent of Cases

D

etectionMethod

0% 10% 20% 30% 40% 50%

IT Controls

Confession

Notified by Police


External Audit


By Accident


Internal Audit

Management Review

Tip 46.4%

15.5%

12.4%

5.2%

6.2%

4.1%

4.1%

4.1%

1.0%

1.0%

0.0%

Percent of Cases

DetectionMethod


23/84


detetion in centra/Soth Ameria an the cariean 70 cases

detetion in Oeania 40 cases

0% 10% 20% 30% 40% 50%

IT Controls

By AccidentNotified by Police

Confession




Internal Audit

External Audit

Management Review

Tip 44.3%

14.3%

10.0%

0.0%

8.6%

4.3%

12.9%

4.3%

0.0%

1.4%

0.0%

Percent of Cases

D

etectionMethod

0% 10% 20% 30% 40% 50%

IT Controls

Confession

Notified by Police


External Audit



Internal Audit

By Accident

Management Review

Tip 45.0%

20.0%

10.0%

12.5%

2.5%

0.0%

2.5%

7.5%

0.0%

0.0%

0.0%

Percent of Cases

DetectionMethod


24/84


Ggracal Lcan organzan

As mentioned previously, or the rst time in the history

o our research on occupational raud, we opened up our

study to include raud cases investigated by CFEs out-

side the United States. As a result, the cases discussed in

this Report represent rauds perpetrated in 106 countries

around the world. We received inormation on the location

o 1,797 o the cases that were reported to us. O these,

43% occurred outside the United States, providing us with

a true insight into the global plague o occupational raud.

The chart below shows the number and median loss o

the cases reported to us, broken down by region. For vic-

tim organizations with locations in more than one coun-

try, we asked survey participants to choose the location

where the primary perpetrator was located. For example,

a raud perpetrated at a European arm o a Japanese com-

pany would be classied as occurring in Europe. Similarly,

a case involving raud perpetrated at the Canadian oce

o a South American company would be considered a

raud that occurred in Canada. The regional breakdowns

on case data throughout this Report should consequently

be read within this ramework. Additionally, due to the

large number o U.S. cases reported, we separated North

America into the United States and Canada, and grouped

the remaining countries by continent.

Vcm organzan

Geographia loation o Vitim Organizations8

Rgn Numbr Ca prcn Ca Mdan L (n U.s. dllar)

United States 1,021 56.8% $105,000

Asia 298 16.6% $274,000

Europe 157 8.7% $600,000

Arica 112 6.2% $205,000

Canada 99 5.5% $125,000

Central/South America and the Caribbean 70 3.9% $186,000

Oceania 40 2.2% $338,000

8See Appendix or a listing o countries included in each region.

As part of our survey, we asked

each respondent to provide

demographic information

about the organization that

was defrauded.

Small organizations are particularlyvulnerable to fraud.


25/84


The ollowing tables illustrate the requency o the 11 occupational raud schemes nancial statement raud, corrup-

tion and the nine asset misappropriation sub-schemes or each region.9

unite States 1,021 cases

scmNumbr

Ca

prcn

Ca

Billing 282 27.6%

Corruption 224 21.9%

Check Tampering 173 16.9%

Skimming 165 16.2%

Non-Cash 160 15.7%

Expense Reimbursements 154 15.1%

Cash on Hand 117 11.5%

Payroll 108 10.6%

Cash Larceny 98 9.6%

Financial Statement Fraud 44 4.3%

Register Disbursements 25 2.4%

Erope 157 cases

scm Numbr Ca prcn Ca

Corruption 79 50.3%

Billing 41 26.1%

Non-Cash 31 19.7%



Skimming 17 10.8%



Payroll 10 6.4%



Asia 298 cases

scmNumbr

Ca

prcn

Ca

Corruption 152 51.0%

Billing 56 18.8%

Non-Cash 55 18.5%


Skimming 38 12.8%





Payroll 12 4.0%


Aria 112 cases

scm Numbr Ca prcn Ca

Corruption 55 49.1%

Billing 38 33.9%

Non-Cash 24 21.4%




Skimming 13 11.6%


Payroll 6 5.4%



9The sum o percentages in these tables exceeds 100% because several casesinvolved schemes rom more than one category.


26/84


corrption cases y Region

Rgn Numbr Crrun Ca prcn all Ca n Rgn Mdan L

Asia 152 51.0% $330,000

Europe 79 50.3% $1,000,000

Arica 55 49.1% $208,000

Central/South America and the Caribbean 33 47.1% $250,000

Oceania 16 40.0% $800,000

United States 224 21.9% $175,000

Canada 21 21.2% $163,000

Vcm organzan

canaa 99 cases

scmNumbr

Ca

prcn

Ca

Billing 21 21.2%

Corruption 21 21.2%



Non-Cash 15 15.2%

Payroll 12 12.1%

Skimming 12 12.1%


Cash on Hand 9 9.1%



Oeania 40 cases

scmNumbr

Ca

prcn

Ca

Corruption 16 40.0%

Non-Cash 12 30.0%

Billing 11 27.5%


Skimming 5 12.5%



Cash Larceny 3 7.5%

Payroll 2 5.0%



centra/Soth Ameria an the cariean 70 cases

scmNumbr

Ca

prcn

Ca

Corruption 33 47.1%

Billing 20 28.6%

Non-Cash 13 18.6%


Skimming 9 12.9%





Payroll 3 4.3%


Crrun Ca by Rgn

We compared the proportion and cost o cases involving

corruption among the regional categories in our study. The

results are presented in the ollowing table.

Readers should keep in mind that this data does not neces-

sarily refect overall corruption levels within each region; it

only refects the specic raud cases that were investigated

and reported to us by the CFEs who took part in our study.


27/84


ty organzan

More than 40% o victim organizations in our study were privately owned businesses, and nearly one-third were publicly

traded companies, meaning that almost three-quarters o the victims represented in our study came rom or-prot enter-

prises. Sixteen percent o the rauds reported to us occurred at government agencies. Not-or-prot organizations were the

least represented category, with less than 10% o rauds taking place at these entities.

In addition to experiencing the most rauds, private and public companies were also victim to the costliest schemes in

our study; the median loss or the cases at these businesses was $231,000 and $200,000, respectively (see page 28).

In contrast, the losses experienced by government agencies and not-or-prot organizations were about hal as much.

Government agencies had a median loss o $100,000, while not-or-prots lost a median o $90,000.

Organization Type o Vitim Freqeny

0% 10% 20% 30% 40% 50%

2010

2008

Not-for-Profit

Government

Public Company

Private Company39.1%

28.4%

32.1%

14.3%

42.1%

16.3%

18.1%

9.6%

Percent of Cases

TypeofVictimO

rganization


28/84


Vcm organzan

Organization Type o Vitim Meian loss

Continuing the trend observed in our prior studies, small

organizations those with ewer than 100 employees

suered the greatest percentage o the rauds in our 2010

study, accounting or more than 30% o the victim orga-

nizations. However, the variation between size categories

is relatively small, with 23% o victims having between

100 and 999 employees, 26% having 1,000 to 9,999 em-

ployees and 21% having more than 10,000 employees.

This relatively small disparity contrasts with our previous

studies, in which small organizations were involved in a

much higher percent o rauds than any other category.

Additionally, our research has historically shown that

smaller organizations suer disproportionately large loss-

es due to occupational raud. Organizations with ewer

than 100 employees experienced the greatest median

loss o all categories o victim organizations in our 2008

study. The same was true in our 2006 study. However,

that was not the case when we looked at the ull body

o data rom our current survey. Consequently, we under-

took additional analyses to see what eect, i any, the in-

clusion o cases rom countries outside the United States

had on these ndings.

sz organzan

$0 $50,000 $100,000 $150,000 $200,000 $250,000 $300,000

2010

2008

Not-for-Profit

Government

Public Company

Private Company$231,000

$278,000

$200,000

$142,000

$100,000

$100,000

$109,000

$90,000

Median Loss

TypeofVic

timO

rganization


29/84


Size o Vitim Organization Freqeny

Size o Vitim Organization Meian loss

$0 $50,000 $100,000 $150,000 $200,000

2010

2008

10,000+

1,000 9,999

100 999


30/84


31/84


Size o Vitim Organizations Meian loss y Region

Md Fraud n small Bun

Because the challenges aced by small businesses in

combating occupational raud are numerous and unique,

it is helpul to know the types o rauds that are most

prevalent within these organizations. Such observations

may help small businesses target their limited resources

to those areas that pose the greatest risk.

O course, the specic risks aced by any organization are

largely dependent on its particular industry, operating envi-

ronment, processes, culture and many other actors. None-

theless, examining which raud schemes are most com-

monly perpetrated at small companies can aid us in better

understanding the raud issues aced by these businesses.

Sma bsinesses(


32/84


Vcm organzan

As the chart below illustrates, check tampering schemes were much more common at small organizations than at all

other entities. Skimming and payroll rauds were also more common in small organizations. These trends stand to rea-

son, as the unctions aected by such schemes the check writing, cash collection and payroll unctions, respectively

are more likely to be perormed by a single individual, such as a bookkeeper, and are oten subject to less oversight

within a small organization than in a large company where duties are more segregated and authorization o transactions

is more ormalized. In contrast, although corruption schemes were the third most common raud scheme aced by small

businesses, they were less requent within small companies than in bigger organizations.

Methos o Fra y Size o Vitim Organization

0% 5% 10% 15% 20% 25% 30% 35% 40%


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An-Fraud Cnrl a small Bun

We have long hypothesized that many small companies are particularly susceptible to raud at least partially due to the

limited resources they devote to anti-raud controls. To test this theory, we compared the presence o anti-raud controls at

those companies with ewer than 100 employees to the controls at companies with more than 100 employees. Our ndings

conrm what we suspected: The small companies in our study did indeed have ewer controls in place than the larger orga-

nizations, a actor that may contribute to the disproportionate impact o raud on these companies. While discrepancies in

levels o certain controls are somewhat expected given the associated costs or resources required to enact them, the gap

between controls in small businesses as opposed to larger organizations is striking. For example, it would be expected that

small businesses would have a lower rate o external audits and that ewer small companies would have a ormal internal

audit or raud examination unction. But even less expensive controls were oten absent in small businesses. While 64% o

large companies had some sort o management review o controls, processes, accounts or transactions, less than hal as

many small businesses had the same type o monitoring in place. Likewise, ormal codes o conduct and anti-raud policies

cost very little to implement, but serve as an eective way to make a clear and explicit statement against raudulent and

unethical conduct within an organization. Yet only 41% and 16% o small businesses had these policies (respectively) in

place when the raud occurred numbers dwared by the 83% and 50% rates o larger organizations.

Perhaps most concerning is that only 15% o small businesses had a hotline in place, compared to 64% o larger orga-

nizations. As previously discussed, our research shows that hotlines are consistently the most eective raud detection

method. Further, as discussed on page 43, the median loss or rauds at companies with hotlines was 59% smaller than

the median loss or rauds at organizations without such a mechanism. Arguably, enacting hotlines would go a long wayin helping small-business owners protect their assets rom dishonest employees.

Freqeny o Anti-Fra contros y Size o Vitim Organization

0% 20% 40% 60% 80% 100%

100+ Employees


40/84


41/84


Management certifationo Finania Statements

Rgn prcn Ca

Arica 68.8%

Canada 65.7%

Oceania 65.0%

Asia 62.8%

Europe 62.4%

United States 56.0%

Central/South America and Caribbean 51.4%

Inepenent Ait committee

Rgn prcn Ca

Arica 63.4%

Canada 59.6%

Oceania 57.5%

Asia 54.7%


Europe 54.1%

United States 50.8%

Empoyee Spport Programs

Rgn prcn Ca

Canada 57.6%

United States 54.8%

Oceania 45.0%

Arica 38.4%


Europe 28.0%

Asia 22.5%

Fra Training or Empoyees

Rgn prcn Ca

United States 42.7%

Arica 39.3%

Europe 37.6%

Asia 37.2%


Canada 29.3%

Oceania 22.5%

Management Review

Rgn prcn Ca

Asia 59.4%

Europe 54.8%

Canada 53.5%

Arica 52.7%

Oceania 52.5%

United States 51.6%


Hotine

Rgn prcn Ca


United States 52.0%

Arica 47.3%

Europe 45.9%

Asia 43.3%

Canada 41.4%

Oceania 25.0%

Fra Training orManagers/Exetives

Rgn prcn Ca

United States 44.5%

Arica 41.1%

Asia 40.9%

Europe 37.6%


Canada 30.3%

Oceania 25.0%

Anti-Fra Poiy

Rgn prcn Ca

Arica 49.1%

United States 38.7%


Canada 38.4%

Asia 36.6%

Europe 36.3%

Oceania 32.5%


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43/84


Meian loss base on Presene o Anti-Fra controsCnrl17 prcn Ca imlmnd Cnrl n plac Cnrl N n plac prcn Rducn

Hotline 48.6% $100,000 $245,000 59.2%

Employee Support Programs 44.8% $100,000 $244,000 59.0%

Surprise Audits 28.9% $97,000 $200,000 51.5%

Fraud Training or Employees 39.6% $100,000 $200,000 50.0%

Fraud Training or Managers/Execs 41.5% $100,000 $200,000 50.0%

Job Rotation/Mandatory Vacation 14.6% $100,000 $188,000 46.8%

Code o Conduct 69.9% $140,000 $262,000 46.6%

Anti-Fraud Policy 39.0% $120,000 $200,000 40.0%

Management Review 53.3% $120,000 $200,000 40.0%

External Audit o ICOFR 59.3% $140,000 $215,000 34.9%

Internal Audit/FE Department 66.4% $145,000 $209,000 30.6%

Independent Audit Committee 53.2% $140,000 $200,000 30.0%

Management Certication o F/S 58.9% $150,000 $200,000 25.0%

External Audit o F/S 76.1% $150,000 $200,000 25.0%

Rewards or Whistleblowers 7.4% $119,000 $155,000 23.2%

Similarly, we compared the duration o raud schemes at organizations with and without anti-raud controls. As refected

in the table below, the presence o each control correlated with a reduction in the duration o raud. We ound it interest-

ing that the controls associated with the greatest reduction in scheme lengths are not the same as the ones that had the

most impact on median loss.

dration base on Presene o Anti-Fra controsCnrl17 prcn Ca imlmnd Cnrl n plac Cnrl N n plac prcn Rducn

Management Review 53.3% 12 months 24 months 50.0%

Internal Audit/FE Department 66.4% 14 months 24 months 41.7%

External Audit o ICOFR 59.3% 15 months 24 months 37.5%

Code o Conduct 69.9% 15 months 24 months 37.5%

Surprise Audits 28.9% 12 months 19 months 36.8%

Hotline 48.6% 13 months 20 months 35.0%

Management Certication o F/S 58.9% 15 months 23 months 34.8%

Rewards or Whistleblowers 7.4% 12 months 18 months 33.3%Job Rotation/Mandatory Vacation 14.6% 12 months 18 months 33.3%

External Audit o F/S 76.1% 16 months 24 months 33.3%

Anti-Fraud Policy 39.0% 13 months 18 months 27.8%

Fraud Training or Employees 39.6% 13 months 18 months 27.8%

Fraud Training or Managers/Execs 41.5% 13 months 18 months 27.8%

Independent Audit Committee 53.2% 15 months 20 months 25.0%

Employee Support Programs 44.8% 15 months 18 months 16.7%

17KeY:

External Audit o F/S = Independent external audits o the organizations nancial statements

Internal Audit / FE Department = Internal audit department or raud examination department

External Audit o ICOFR = Independent audits o the organizations internal controls over nancial reporting

Management Certication o F/S = Management certication o the organizations nancial statements


44/84


imranc Cnrl n Dcng r Lmng Fraud

Not all controls are eective against all rauds. Most control mechanisms are more likely to detect or deter some raud

schemes than others. Likewise, some perpetrators are more adept than others at circumventing particular controls, and

some controls are more susceptible to being overridden than others.

We thought it useul to examine which controls had the greatest eect on the rauds reported in our study. We asked the

CFEs who took part in our survey to rank the importance o several anti-raud controls in detecting or limiting the raud.

The ollowing chart shows the respondents opinions regarding each controls useulness.

Vcm organzan

Importane o contro in deteting or limiting Fra

18

KeY:External Audit o F/S = Independent external audits o the organizations nancial statements

Internal Audit / FE Department = Internal audit department or raud examination department

External Audit o ICOFR = Independent audits o the organizations internal controls over nancial reporting

Management Certication o F/S = Management certication o the organizations nancial statements

0% 10% 20% 30% 40% 50% 60% 70% 80%

Not at all Important

Somewhat Important

Very Important

External Audit of F/S

External Auditof ICOFR

Rewards forWhistleblowers

Hotline

Job Rotation/Mandatory Vacation

Surprise Audits

Management Review

Internal Audit/FE Department

Percent of Respondents

Control18

60.8%

50.3%

49.0%

42.0%

41.3%

38.3%

36.0%32.4%

29.4%

31.5%

40.7%

45.4%

27.9%23.0%

24.5%

17.9%

25.3%21.4%

25.7%

25.3%31.2%

19.3%

23.5%

19.2%


45/84


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Vcm organzan

Primary Interna contro Weakness y Size o Vitim Organization

Primary Interna contro Weakness in largest cases

0% 10% 20% 30% 40% 50%

100+ Employees


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prrar

prrar Ag

The distribution o perpetrators based on their age was similar to our 2008 study, but the 2010 perpetrators tended to be

slightly younger. Our past reports have generally shown the highest levels o raud to occur in the 3650 age range, but this

year we ound more than hal o all cases were committed by individuals between the ages o 31 and 45. Generally speak-

ing, median losses tended to rise with the age o the perpetrator, which is consistent with our prior research. The most

notable dierence between 2008 and 2010 is the losses caused by perpetrators older than 60. In each study, however,

we were dealing with ewer than 40 cases in that category. Given the small sample size, we believe this is more likely to

be an anomaly than an indication o any particular trend.

Age o Perpetrator Freqeny

0%

5%

10%

15%

20%

2010

2008

>6056 6051 5546 5041 4536 4031 3526 30


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prrar Darmn Bad n Rgn

The ollowing tables show the distribution o perpetrators based on their department or each region. In every region but

Asia, accounting departments were associated with the greatest number o rauds. Overall, the distribution o cases was

very similar regardless o region. The six highest-requency departments (accounting, operations, sales, executive/upper

management, customer service and purchasing) accounted or between 70% and 85% o the cases in every region.

unite States 913 cases

DarmnNumbr

Ca

prcn

CaAccounting 222 24.3%

Operations 189 20.7%

Executive/Upper Management 127 13.9%

Sales 120 13.1%

Customer Service 77 8.4%

Purchasing 39 4.3%

Warehousing/Inventory 36 3.9%

Finance 28 3.1%

Inormation Technology 26 2.8%

Manuacturing and Production 11 1.2%

Marketing/Public Relations 11 1.2%

Legal 7 0.8%Board o Directors 6 0.7%

Human Resources 6 0.7%

Research and Development 6 0.7%

Internal Audit 2 0.2%

Erope 146 cases

DarmnNumbr

Ca

prcn

Ca

Accounting 26 17.8%


Operations 21 14.4%

Purchasing 13 8.9%

Sales 13 8.9%

Finance 11 7.5%



Board o Directors 6 4.1%






Asia 272 cases

DarmnNumbr

Ca

prcn

CaSales 57 21.0%

Operations 42 15.4%

Accounting 41 15.1%


Purchasing 29 10.7%

Finance 11 4.0%






Manuacturing and Production 6 2.2%Inormation Technology 4 1.5%

Internal Audit 1 0.4%


Aria 105 cases

DarmnNumbr

Ca

prcn

Ca

Accounting 31 29.5%

Operations 13 12.4%

Finance 11 10.5%



Purchasing 7 6.7%



Sales 5 4.8%




Legal 1 1.0%



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sal Darmn

The most common rauds in the sales department were corruption (34% o cases) and thet o non-cash assets (24%).

Fraudsters in the sales department were somewhat more likely than others to steal non-cash assets. Conversely, they

were much less likely to engage in billing schemes, check tampering or payroll raud.

Shemes committe y Perpetrators in the Saes department 225 cases25


0% 5% 10% 15% 20% 25% 30% 35%

All Cases

Sales

Payroll


Check Tampering

Register Disbursements

Cash Larceny

Cash on Hand

Billing

Expense Reimbursement

Skimming

Non-Cash

Corruption

Percent of Cases

SchemeType

33.8%

23.6%

17.5%

32.8%

16.4%

14.5%

15.6%

15.1%

26.0%

13.8%

12.0%

12.0%

9.3%

8.0%

13.4%

4.0%

3.6%

4.8%

1.8%

8.5%

9.8%

3.0%


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Cumr srvc Darmn

Corruption was the most common orm o raud among customer service employees (22% o cases), but compared

to the distribution or all cases, we see that corruption was actually much less likely to occur in customer service than

elsewhere. Conversely, skimming, thet o cash on hand and raudulent register disbursements were more likely to occur

in customer service than in other areas o the organization.

Shemes committe y Perpetrators in the cstomer Servie department 120 cases27


0% 5% 10% 15% 20% 25% 30% 35%

All Cases

Customer Service

Payroll


Expense Reimbursement

Register Disbursements

Check Tampering

Billing

Cash Larceny

Non-Cash

Cash on Hand

Skimming

Corruption

Percent of Cases

S

chemeType

21.7%

19.2%

14.5%

32.8%

18.3%

12.0%

17.5%

17.5%

9.8%

9.2%

8.3%

26.0%

8.3%

8.3%

15.1%

3.3%

1.7%

4.8%

0.8%

8.5%

13.4%

3.0%


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prrar Crmnal and emlymn

hry

prrar Crmnal Backgrund

Only 7% o the raud perpetrators in our study had been

previously convicted o a raud-related oense, which

was virtually identical to our nding in 2008. Eighty-six

percent had never been charged with or convicted o a

prior oense. The low rate o prior convictions suggests

that criminal background checks may have some eect in

preventing raud, but the eect is probably limited.

prrar emlymn Backgrund

In addition to criminal history, past employment issues

may indicate that an employee is more likely to engage

in raudulent conduct in the uture. O the respondents in

our survey, 791 were able to provide inormation about

the perpetrators prior employment history. Among those

cases, about 8% o perpetrators had been previously

punished and 10% had been previously terminated or

raud-related conduct.

Bavral Rd Flag Dlayd by

prrar

While a raud is ongoing, the perpetrator oten displays

certain behaviors or characteristics that might indicate he

or she has a heightened risk o committing raud. On their

own, these behavioral red fags do not prove an individual

is engaged in a raud, but they should raise warning sig-

nals to the individuals co-workers and managers, as well

as the organizations anti-raud sta. When these red fags

exist alongside other indicators o misconduct, this can be

a strong clue that something is wrong. As discussed earlier

in this report, occupational rauds oten last or months or

years beore they are caught, so the ability to detect rauds

as early as possible can have a big eect in limiting losses.

0%

20%

40%

60%

80%

100%2010

2008

Charged But

Not Convicted

Prior

Convictions

Never Charged

or Convicted

85.7%87.4%

6.7% 6.8% 7.7%5.7%

Criminal Background

PercentofCases

0%

20%

40%

60%

80%

100% 2010

2008

PreviouslyPunished

PreviouslyTerminated

Never Punishedor Terminated

82.4% 82.6%

9.5%12.3%

8.1%5.1%

Employment Background

PercentofCases

Perpetrators crimina bakgron

Perpetrators Empoyment bakgron


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prrar

We presented survey respondents with a list o common behavioral red fags and asked them to identiy which o these

warning signs had been displayed by the perpetrator prior to detection o the raud. As shown in the chart below, the most

common red fags displayed by perpetrators were living beyond nancial means (43% o cases), experiencing nancial

diculties (36%), excessive control issues with regard to their jobs (23%) and an unusually close association with vendors

or customers (22%). This distribution is very similar to what we ound in our 2008 study. As we continue to track this

data in uture studies, we hope to be able to identiy consistent relationships between behavioral warning signs and

the occurrence o occupational raud. Ideally, this data will help organizations build better raud-detection programs that

incorporate behavioral data in addition to more standard anti-raud controls.

behaviora Re Fags o Perpetrators29

29The sum o percentages in this chart exceeds 100% because in many cases perpetrators displayed more than one behavioral red fag.

0% 10% 20% 30% 40% 50%

2010

2008

Complained about lack of authority

Excessive family/peer pressure for success

Instability in life circumstances

Past legal problems

Excessive pressure from within organization

Complained about inadequate pay

Past employment-related problems

Refusal to take vacations

Addiction problems

Irritability, suspiciousness or defensiveness

Divorce/family problems

Wheeler-dealer attitude

Unusually close association with vendor/customer

Control issues, unwillingness to share duties

Financial difficulties

Living beyond means 43.0%38.6%

36.4%

34.1%

22.6%

18.7%

22.1%

15.2%

19.2%

20.3%

17.6%

17.1%

14.1%

13.6%

11.9%

13.3%

10.2%

6.8%

9.3%

7.9%

7.9%

7.3%

7.5%

6.5%

6.3%

8.7%

5.6%

4.9%

5.1%

4.2%

4.6%

3.6%

Percent of Cases

BehavioralRed

Flag


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Red Flags Based on peretrators poston

The behavioral indicators that a raud perpetrator displays can vary depending on a number o actors. The ollowing

chart shows the distribution o red fags based on the perpetrators level o authority. Among employee-level raudsters,

the most common behavioral red fag was nancial diculties, which was present in nearly hal o all employee raud

cases. Because employee-level raudsters generally have lower incomes than managers or owners/executives, we would

expect their motivation or committing raud to more oten be based on an immediate, pressing nancial need, which

explains why this red fag shows up so oten. While nancial diculty was still requently cited in cases involving manag-

ers and owners/executives, it occurred much less oten. Conversely, owners/executives and managers were much more

likely than employees to display control issues, to have unusually close associations with vendors or customers or to

exhibit a wheeler-dealer attitude. Each o these red fags tends to refect the authority level o owners/executives and

managers, who are in a better position than employees to infuence organizational decision-making, arrange deals with

outside parties and exert their control over the direction or tone o the organization.

behaviora Re Fags o Perpetrators base on Position30

30The sum o percentages in this chart exceeds 100% because in many cases perpetrators displayed more than one behavioral red fag.

0% 10% 20% 30% 40% 50%

Owner/Executive

Manager

Employee

Complained about lack of authority

Excessive family/peer pressure for success

Instability in life circumstances

Past legal problems

Excessive pressure from within organization

Complained about inadequate pay

Past employment-related problems

Refusal to take vacations

Addiction problems

Irritability, suspiciousness or defensiveness

Divorce/family problems

Wheeler-dealer attitude

Unusually close association with vendor/customer

Control issues, unwillingness to share duties

Financial difficulties

Living beyond means40.7%

43.8%

30.7%26.1%

25.8%33.0%

29.8%

35.2%

24.9%

21.0%

19.3%16.4%16.5%

9.8%16.9%16.5%

12.1%12.7%

11.6%10.0%

7.7%

11.1%7.6%8.4%

9.8%6.8%7.3%

4.8%9.9%

8.4%

6.3%5.9%

7.7%

6.6%4.3%5.7%

5.8%4.3%5.7%

6.7%2.7%

2.6%

10.7%

15.2%

12.1%

10.7%

48.3%

47.6%

Percent of Cases

BehavioralRed

Flag


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Mdlgy

The2010 Report to the Nations on Occupational Fraud and

Abuse is based on the results o an online survey distrib-

uted to 22,927 Certied Fraud Examiners (CFEs) in Octo-

ber 2009. As part o the survey, respondents were asked

to provide a detailed narrative o the single largest raud

case they had investigated that met our explicit criteria:

The case must have involved occupational raud1.(dened as internal raud, or raud committed bya person against the organization or which he or

she works).

The investigation must have occurred between2.January 2008 and the time o survey participation.

The investigation must have been completed.3.

The CFE must have been reasonably sure the4.perpetrator(s) was/were identied.

Respondents were also presented with 87 questions to

answer. These questions covered particular details o the

scheme, including inormation about the perpetrator, the

victim organization and the methods o raud employed, as

well as raud trends in general. Overall, we received 1,939

responses to the survey, 1,843 o which were usable or

purposes o this Report. The data contained herein is based

solely on the inormation provided in these 1,843 cases.

W prvdd Daa?

We sent the survey to all CFEs in good standing at the

time o the survey launch. We asked respondents to pro-

vide certain inormation about their proessional experi-

ence and qualications so that we could gather a uller

understanding o who was involved in investigating the

rauds reported to us as part o our research.

prmary occuan

More than hal o the CFEs who participated in our study

identied themselves as either raud examiners or internal

auditors. Another 12% stated that they are accountants,

and just over 7% indicated they work as law enorcement

ocers.

The 2010 Report to the Nations

on Occupational Fraud and

Abuse is based on the results of

an online survey distributed

to 22,927 Certied Fraud

Examiners (CFEs) in late 2009.

The data in this study is based on 1,843cases of occupational fraud that werereported by CFEs.


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Andx

Brakdwn Ggrac Rgn by Cunry

Aria 112 cases

CunryNumbr

Ca

Cameroon 1

Democratic Republic o the Congo 1

Egypt 5

Ethiopia 1

Ghana 4Guinea 1

Kenya 7

Liberia 1

Malawi 1

Mauritius 2

Mozambique 2

Nigeria 21

Republic o the Congo 1

Senegal 1

South Arica 47

Sudan 1

Tanzania 4

Tunisia 1

Uganda 5

Zambia 2

Zimbabwe 3

Asia 298 cases

CunryNumbr

Ca

Aghanistan 1

Bahrain 1

Cambodia 2

China 62

Cyprus 3India 37

Indonesia 27

Iran 1

Iraq 1

Japan 16

Jordan 4

Kuwait 3

Kyrgyzstan 1

Lebanon 4

Malaysia 22

Oman 4

Pakistan 8

Philippines 16

Qatar 5

Saudi Arabia 9

Singapore 7

South Korea 5

Sri Lanka 2

Taiwan 4

Tajikistan 1

Thailand 2

Turkey 20

Turkmenistan 2

United Arab Emirates 27

Vietnam 1


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centra/Soth Ameria anthe cariean 70 cases

CunryNumbr

Ca

Argentina 7

Bahamas 1

Barbados 1

Belize 1

Bolivia 1

Brazil 12

Chile 1

Colombia 3

Costa Rica 1

Dominican Republic 2

Grenada 1

Honduras 1

Jamaica 4

Mexico 20

Nicaragua 2

Panama 1

Peru 3

Saint Lucia 1

Saint Vincent and the Grenadines 2

Trinidad and Tobago 4

Venezuela 1

Oeania 40 cases

CunryNumbr

Ca

Australia 29

Fiji 2

Micronesia 1

New Zealand 8

Erope 157 cases

CunryNumbr

Ca

Austria 3

Belgium 9

Bulgaria 3

Czech Republic 5

Estonia 1

Finland 3

France 1

Germany 19

Greece 6

Hungary 3

Ireland 1

Italy 7

Kosovo 1

Liechtenstein 1

Luxembourg 1

Montenegro 1

Netherlands 14

Poland 9

Portugal 2

Romania 5

Russia 18

Serbia 1

Slovakia 1

Slovenia 1

Spain 8

Switzerland 4

Ukraine 1

United Kingdom 28


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2010 RepoRt to the NatioNs on occupational FRaud and abuse |

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