Consumer Fraud in the United States: 

An FTC Survey

Staff Report of the 

Bureaus of Economics and Consumer Protection

Federal Trade Commission

Keith B. Anderson

August 2004
ii 

Federal Trade Commission

Timothy J. Muris Chairman

Mozelle W. Thompson Commissioner

Orson Swindle* Commissioner

Thomas B. Leary Commissioner

Pamela Jones Harbour Commissioner

Luke M. Froeb Director, Bureau of Economics

J. Howard Beales, III Director, Bureau of Consumer Protection

The author is an economist in the Bureau of Economics of the Federal Trade Commission. The 

views expressed in this report are those of the author and do not necessarily reflect the views of 

the Federal Trade Commission or any individual Commissioner.

* Commissioner Swindle did not participate in this matter.
iii

Acknowledgments

John Yun and Hajime Hadeishi made major contributions to the econometric analyses in 

Chapters 4 and 5 respectively. Without their hard work and expert advice, the study would 

not be what it is. James Lacko, Jesse Leary, Alan Mathios, and David Newhouse provided 

extremely useful advice on methodological issues. The survey was conducted by Public Opinion 

Strategies, and Bill McInturff, Elizabeth Frontczak and Tom Dewhurst of that firm made 

significant contributions to the survey design, as did various staff in the Bureau of Consumer 

Protection of the FTC. Christopher Kelley and David Yans provided valuable assistance in 

coding open-ended responses. Dawne Holz in the Office of Consumer and Business Education 

in the Bureau of Consumer Protection was responsible for the formatting of the report. Drafts 

were reviewed and valuable editorial suggestions provided by Howard Beales, Pauline Ippolito, 

Lydia Parnes, Paul Pautler, Nat Wood, and Kial Young. Assistance was also provided by Carolyn 

Samuels, Stefano Sciolli, Marie Tansioco, and Lance Toler.
iv
Table of Contents

v

Table of Contents

List of Tables.................................................................................................................................vii

List of Figures............................................................................................................................... ix

Executive Summary................................................................................................................ ES-1

Chapter 1: Introduction ...............................................................................................................1

Other Studies ............................................................................................................................2

Chapter 2: Description of the Survey..........................................................................................7

Types of Fraud Investigated......................................................................................................7

Specific Types of Fraud .....................................................................................................8

More General Problems That May Be Associated With Fraud .......................................17

Switching of Long Distance Telephone Service Providers.............................................18

Victims of Fraud or Targets of Fraud?....................................................................................19

Consumer Purchasing Behavior .............................................................................................20

Chapter 3: Which Types of Frauds Are the Most Common? .................................................25

The Number of Victims ..........................................................................................................25

The Number of Incidents........................................................................................................30

Media Employed.....................................................................................................................37

The Cost of an Incident of Fraud............................................................................................38

Open-Ended Descriptions of Fraudulent Experiences............................................................41

Methodological Appendix to Chapter 3 .....................................................................................45

Chapter 4: Who is a Victim of Fraud?......................................................................................49

Characteristics Analyzed ........................................................................................................49

Methodology...........................................................................................................................52

Analysis of Aggregate Measures of Risk................................................................................54

Race and Ethnicity...........................................................................................................55

Current Income................................................................................................................62

Future Income..................................................................................................................63

The Burden of Debt.........................................................................................................65

Age ..................................................................................................................................68

Marital Status...................................................................................................................69

Other Characteristics.......................................................................................................69

The Likelihood of Being a Victim of Specific Frauds............................................................70

Slamming vs. Frauds.......................................................................................................71

Different Types of Frauds................................................................................................74

The Role of Language ............................................................................................................75

Conclusion ..............................................................................................................................76
Consumer Fraud in the United States: An FTC Survey

vi

Chapter 5: Who Complains? .....................................................................................................79

Complaint Data Collected ......................................................................................................79

To Whom Do Consumers Complain?.....................................................................................80

Characteristics of Those Who Complain ................................................................................82

Internet Usage..................................................................................................................84

Education Level...............................................................................................................96

Age ..................................................................................................................................97

Income .............................................................................................................................98

Gender and Marital Status...............................................................................................99

Race and Ethnicity.........................................................................................................100

Method of Payment .......................................................................................................101

How Satisfied Are Those Who Complain? ...........................................................................102

Entity To Whom Complaint Was Made.........................................................................103

Amount Lost..................................................................................................................108

Internet Usage, Education, Marital Status, Gender, and Age ........................................108

Income ...........................................................................................................................109

Race and Ethnicity.........................................................................................................109

Payment Mechanism .....................................................................................................110

Conclusion ............................................................................................................................111

Chapter 6: Conclusion..............................................................................................................115

Issues for Future Studies.......................................................................................................117

Appendix A: The Survey Instrument..................................................................................... A-1
List of Tables

vii

Table ES-1: The Most Common Types of Consumer Fraud ....................................................ES-3

Table ES-2: Percent of Survey Participants Who Are Victims of Frauds, 

by Single Characteristic .......................................................................................ES-8

Table 2-1: Consumer Responses to Solicitations ......................................................................21

Table 3-1: Estimated Number of Adults Who Were Victims of Fraud or Had Their Long 

Distance Telephone Service Changed Without Permission, 

One Year Period Prior to the Survey ........................................................................26

Table 3-2: Estimated Number of Incidents of Fraud or of Unauthorized Changes in Long 

Distance Telephone Service, One Year Period Prior to the Survey..........................32

Table 3-3: Number of Incidents Experienced by Victims .........................................................35

Table 3-4: Fraud Incidents by Type of Product Involved ..........................................................36

Table 3-5: How Victims First Learned About the Product or Service Involved in Frauds........38

Table 3-6: Distribution of Estimated Losses Per Incident for Different Types of Frauds.........40

Table 3-7: Responses to Open-Ended Question About The Type of Fraud Experienced..........41

Table 3-8: Closed-End Responses of Survey Participants Who Described Frauds That 

Occurred in the Last Year in Answer to Open-Ended Question...............................43

Table 4-1: Distribution of Values for Explanatory Variables.....................................................50

Table 4-2: Percent of Survey Participants Who Are Victims, By Single Characteristic ...........56

Table 4-3: Likelihood of Being a Victim, Probit Estimation, Marginal Effects, 

Aggregate Measures.................................................................................................59

Table 4-4: Likelihood of Being a Victim, Probit Estimation, Marginal Effects, 

Individual Problems .................................................................................................72

Table 5-1: To Whom Did Consumers Complain? .....................................................................80

Table 5-2: Percent of Consumers Who Complained, By Type of Problem...............................82

Table 5-3: Percent of Consumers Who Complain, By Single Characteristic ............................86

Table 5-4: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, 

Complaints Filed with Anyone.................................................................................88

Table 5-5: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, 

Complaints Filed with Official Sources...................................................................90

Table 5-6: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, 

Complaints Filed with Seller or Manufacturer.........................................................92

Table 5-7: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, 

Complaints Filed with Bank or Credit Card Company ............................................94

Table 5-8: Degree of Satisfaction with Results of Complaints ...............................................103

List of Tables
Consumer Fraud in the United States: An FTC Survey

viii

Table 5-9: Satisfaction with the Results of a Complaint, By Single Characteristic ................104

Table 5-10: Satisfaction with Results of Complaints, Probit Estimation, Marginal Effects .....106

Table 5-11: Marginal Effects by Fraud Type, Conditional-Mean-Imputation Probit 

Equations................................................................................................................112
List of Figures

ix

Figure ES-1: Most Common Types of Consumer Fraud ...........................................................ES-2

Figure ES-2: Victims of Fraud, By Race and Ethnicity.............................................................ES-4

Figure ES-3: Victims of Fraud, By Expected Income - Three Years Future .............................ES-5

Figure ES-4: Victims of Fraud, By Comfort with Current Level of Debt.................................ES-6

Figure ES-5: Victims of Fraud, By Age.....................................................................................ES-6

Figure 3-1: Specific Types of Fraud, By Number of Victims .....................................................29

Figure 3-2: Specific Types of Fraud, By Number of Incidents...................................................31

Figure 3-3: Media Used to Promote Frauds................................................................................37

Figure 3-4: Median Dollars Lost, By Specific Type of Fraud.....................................................40

Figure 4-1: Likelihood of Being a Victim, By Race and Ethnicity.............................................55

Figure 4-2: Likelihood of Being a Victim, By Expected Change in Future Income...................64

Figure 4-3: Likelihood of Being a Victim, By Comfort with Current Level of Debt .................66

Figure 4-4: Likelihood of Being a Victim, By Age.....................................................................67

Figure 4-5: Likelihood of Being a Victim, Fraud Compared to Slamming ................................74

Figure 5-1: Likelihood of Complaining, By Internet Usage .......................................................84

Figure 5-2: Likelihood of Complaining, By Education ..............................................................96

Figure 5-3: Likelihood of Complaining, By Age ........................................................................97

Figure 5-4: Likelihood of Complaining, By Gender...................................................................99

Figure 5-5: Likelihood of Complaining, By Race and Ethnicity ..............................................100

Figure 5-6: Complaint Satisfaction, By Party Complained To .................................................103

Figure 5-7: Complaint Satisfaction, By Payment Mechanism..................................................110

List of Figures
Consumer Fraud in the United States: An FTC Survey

x 
ES-1

Executive Summary

Executive Summary

Consumer frauds pose a threat to consumers and the economy. Even the 

most wary and sophisticated consumers may fall victim to fraudulent offers – in 

the mail, in the media, and on the Internet. To learn more about the extent of 

consumer fraud and to enhance our understanding of its victims, the Federal Trade 

Commission (“FTC”) last year commissioned a survey of 2,500 randomly-chosen 

adults about their consumer experiences during the previous year. 

This survey will help the FTC better serve fraud victims through law 

enforcement and education. The survey was designed, in part, to assist the 

agency in determining whether information in the FTC’s Consumer Sentinel 

database of fraud complaints is representative of consumers’ actual experiences 

with fraud in the marketplace. The survey provides the agency with a broader 

snapshot of fraud in America which, in addition to helping target law enforcement 

actions, will allow the FTC to target education campaigns more precisely towards 

particular consumer groups who are at risk of falling victim to fraud but who may 

not complain to the FTC about their experiences.

Rather than asking generally whether survey participants had fallen victim 

to “fraud” in the past year, the survey targeted ten specific types of fraud and two 

additional situations that frequently indicate that a fraud may have occurred.1 

The ten specific frauds were selected because they cover the most prevalent 

types of complaints reported in the FTC’s complaint database and are frauds that 

have frequently led to FTC enforcement actions. The survey also asked about 

“slamming” – a situation in which a consumer’s long distance telephone service 

is switched from one carrier to another without the consumer’s permission. 

Although the FTC’s complaint database includes many consumer complaints 

concerning slamming, slamming is somewhat different than the other consumer 

problems covered by the survey. (Unlike many of the other problems, victims 

of slamming do receive something of value, in that they are still able to make 

long distance telephone calls, though not via the carrier they have chosen; 

and therefore it is difficult to determine the extent of the injury.) In addition, 

telephone service is regulated by the Federal Communications Commission, 

rather than the FTC. Slamming is therefore considered separately.

1. The ten specific types of fraud were (1) paying an advance fee to obtain a loan or credit card that a 

consumer was promised or guaranteed to receive, (2) being billed for a buyers’ club membership a consumer 

did not agree to purchase, (3) purchasing credit card insurance, (4) purchasing credit repair services, (5) 

paying money or making a purchase to receive a promised prize and then not receiving the prize or receiving 

a prize that was not as promised, (6) being billed for Internet services a consumer did not agree to purchase, 

(7) purchasing a membership in a pyramid scheme, (8) being billed for information services provided either 

over the Internet or by pay-per-call telephone service that a consumer had not agreed to purchase, (9) making 

a payment to someone who represented that as a result of making the payment a consumer would receive a 

government job, and (10) purchasing a business opportunity where the seller made earnings claims that were 

not realized or promised assistance that was not provided. The two more general situations were (1) paying 

for a product or service that a consumer does not receive and (2) being billed for a product, other than the 

specific products identified above, that a consumer had not agreed to purchase. 
ES-2

Consumer Fraud in the United States: An FTC Survey

What are the Top Problems Identified by the Survey?

The survey suggests that nearly 25 million adults in the U.S. – 11.2 percent 

of the adult population – were victims of one or more of the consumer frauds 

covered by the survey during the previous year. More than 35 million incidents of 

these various frauds occurred during the year.2

Advance Fee Loan Scams

The most 

frequently reported 

type of consumer 

fraud was advance 

fee loan scams, 

which involve a 

consumer paying 

money to a seller 

prior to receiving 

a promised or 

guaranteed loan or 

credit card. FTC 

rules prohibit 

charging such 

an advance fee 

in the context of 

telemarketing.

Some 4.5 million consumers – 2.1 percent of U.S. adults – made such 

payments, but did not receive the promised loan or credit card in the year 

covered by the survey. Some survey participants reported that they had paid for 

a promised loan or credit card more than once during the last year. As a result, 

an estimated 6.5 million incidents of this fraud occurred during the year, or three 

incidents per 100 adults.

Buyers’ Club Memberships

The second most commonly reported fraud covered by the survey was being 

billed for a membership in a buyers’ club or for a buyers’ guide publication 

without having agreed to join the club or purchase the publication. Some four 

million U.S. adults – 1.9 percent of the adult population – were unwittingly billed 

for memberships in these clubs or for such buyers’ guides in the year prior to the 

survey. An estimated 4.8 million incidents of this type of fraud took place during 

that time.

2. As discussed in the report, these estimates are based on somewhat conservative assumptions 

regarding who is considered to be a victim. (See page 11.) Figures on the number of victims and their 

characteristics are based on data that has been appropriately weighted, using weights supplied by the 

contractor who conducted the survey, to adjust for sampling and response rate issues.

Figure ES-1

Most Common Types of Consumer Fraud

1.55 1.75 1.80 2.00

3.35

4.05

4.55

0.0

1.0

2.0

3.0

4.0

5.0

Advance Fee

Loans

Buyers' Clubs Credit Card

Insurance

Credit Repair Prize

Promotions

Internet

Services

Pyramid

Schemes

Millions of Victims
ES-3

Executive Summary

Credit Card Insurance and Credit Repair

The third and fourth most common frauds were also related to credit: 

An estimated 3.3 million adults bought insurance as protection against the 

unauthorized use of credit cards, and some 2.0 million adults paid for credit 

“repair” services. Fraudulent operators sell credit card insurance by claiming 

that card holders face considerable financial risk if their credit cards are misused. 

This costly insurance, however, is generally unnecessary because federal law 

limits consumer liability to $50, and credit card companies often do not require 

consumers who report a lost, stolen, or misused credit card to pay anything. 

Credit repair frauds may involve paying money to someone who falsely promises 

to have truthful, negative information removed from a consumer’s existing credit 

record. Credit repair frauds also may involve paying for information about how 

to establish a new credit record by using a number other than a Social Security 

number to apply for credit. Both of these types of credit repair are illegal.

Table ES-1: The Most Common Types of Consumer Fraud

Type of Problem

Number of 

Victimsa

(millions of adults)

Number of 

Incidentsb 

(millions)

Paid an advance fee to obtain a loan or credit card that you were 

promised or guaranteed you would receive 4.55 6.55

Billed for buyers’ club memberships you did not agree to purchase 4.05 4.80

Purchased credit card insurance 3.35 4.60

Purchased credit repair 2.00 2.45

Paid money or made a purchase to receive a promised prize and 

did not receive the prize or prize was not as promised 1.80 2.40

Billed for Internet services you did not agree to purchase 1.75 1.90

Purchased a membership in a pyramid scheme 1.55 2.55

Total, Specific Types of Fraud Included in the Survey 18.35 27.40

Total, Any Type of Fraud, Specific or General, Included in the 

Survey 24.45 35.45

Unauthorized Changes in Long Distance Telephone Service 

(“Slamming”) 13.90 17.60

Total, Any Fraud Covered by Survey or Unauthorized Changes in 

Long Distance Service 35.60 53.00

Notes. 

a Individuals are included only once in these counts, even if they experienced multiple incidents of the relevant 

fraud. Numbers are rounded to the nearest 0.05 million. Numbers will not add to totals, because some individuals 

experienced several types of fraud.

b Each incident of fraud is included in these counts, including multiple incidents for an individual. Numbers are 

rounded to the nearest 0.05 million. Numbers may not add to totals, because of rounding.

Source: Tables 3-1 and 3-2.
ES-4

Consumer Fraud in the United States: An FTC Survey

Telephone Slamming

The survey also found that an estimated 13.9 million consumers experienced 

unauthorized changes in long distance telephone service – 6.5 percent of the U.S. 

adult population. Indeed, some consumers reported that they were slammed more 

than once: An estimated 17.6 million incidents of slamming occurred during the 

year preceding the survey. 

Frauds Are Mass Marketed

The survey revealed that 33.0 percent of fraud victims first learned about an 

offer or product that turned out to be fraudulent from a printed source, including 

newspaper or magazine ads, direct mail solicitations, catalogs, and posters. 

Telemarketing was the first source of contact in 16.8 percent of the frauds reported 

by survey participants; the Internet – including email and web sites – was the first 

contact in 14 percent of cases.

Who Is Most Likely to be a Victim? 

Some consumers are more likely to become victims of fraud than others. The 

study found that race or ethnicity, expectations about future income, and comfort 

with one’s level of debt were all associated with the likelihood of being a victim 

of fraud.

Racial and Ethnic Minorities

The survey 

found that members 

of several racial and 

ethnic minorities 

were much more 

likely to be victims 

of fraud than nonHispanic whites. 

Of non-Hispanic 

whites, 6.4 percent 

had been victims of 

one or more of the 

frauds covered by 

the survey during 

the previous year.3

3. Although the numbers in the text are the results of simple cross-tab comparisons of members of 

different racial and ethnic groups, the results are qualitatively the same after controlling for demographic 

differences such as income and education.

Figure ES-2 

Victims of Fraud

By Race and Ethnicity

14.3%

17.1%

33.8%

6.4% 7.3%

0%

10%

20%

30%

40%

Hispanics African Americans American Indians /

Alaska Natives

Non-Hispanic Whites Others
ES-5

Executive Summary

4. While the number of survey participants who described themselves as American Indians or Alaska 

Natives was small, the difference in the rate of fraud between this group and non-Hispanic whites is 

statistically significant, as are all of the differences highlighted in the Executive Summary.

Figure ES-3

Victims of Fraud

By Expected Income – Three Years Future

14.2%

9.6%

5.0%

7.2%

11.0%

0%

10%

20%

30%

40%

Much Lower Slightly Lower About the Same Slightly Higher Much Higher

Those who are American Indians or Alaska Natives were at greatest risk: 

Almost 34 percent of survey participants in this group had been victims of one or 

more of the frauds covered by the survey in the preceding year – more than five 

times the percentage of victims among non-Hispanic whites.4

Both Hispanics and African Americans were more than twice as likely to 

be victims of consumer fraud as non-Hispanic whites. Some 14.3 percent of 

Hispanics and 17.1 percent of African Americans interviewed had been victims of 

one or more of the frauds in the survey during the prior year. On the other hand, 

only 7.3 percent of participants who were assigned to the “Other” racial category 

– which includes those who identified themselves as Asian, as Hawaiian or Other 

Pacific Islander, or as belonging to more than one racial group – were victims.

Consumers Who Expect Large Changes in Their Future Income

The survey 

also indicated that 

consumers who 

anticipate a large 

change in their 

incomes in the next 

three years were 

more than twice as 

likely to be victims 

of fraud as those 

who expect their 

incomes to remain 

stable. Only five 

percent of survey 

participants who 

expected their 

incomes to remain largely unchanged over the next three years reported being 

victims of one or more of the frauds examined. By contrast, 11.0 percent of 

survey participants who expected their incomes to be much lower and 14.2 

percent of those who expected their incomes to be much higher in the next three 

years were victims.
ES-6

Consumer Fraud in the United States: An FTC Survey

Figure ES-4

Victims of Fraud

By Comfort with Current Level of Debt

2.7%

8.1% 9.1%

19.2%

0%

10%

20%

30%

40%

More Debt Than Can

Comfortably Handle

About As Much Debt As

Can Comfortably Handle

Could Handle More Debt

Than Currently Have

Do Not Have Any Personal

Debt

Figure ES-5

Victims of Fraud

By Age

4.7% 6.1%

8.7%

11.1% 11.1%

8.3%

0%

10%

20%

30%

40%

18 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 and over

Consumers Who Are Uncomfortable with Their Current Debt

Consumers 

who had more debt 

than they could 

comfortably handle 

also were more 

likely to be fraud 

victims. Only 

2.7 percent of 

consumers without 

debt reported being 

victims of fraud. 

On the other hand, 

19.2 percent of the 

survey participants 

who felt that they 

had too much debt 

indicated they had 

been victims of 

fraud – more than 

seven times the 

risk faced by those 

without any current 

debt.

The Elderly Do Not 

Experience More 

Fraud

The FTC 

survey found that 

consumers 65 years 

old or older did not 

experience more 

fraud than those 

who were younger.

Who Complains About Consumer Fraud? 

In 29.3 percent of cases of fraud or slamming, consumers did not complain 

to anyone about their experience. When consumers did complain, they most 

frequently complained to the seller or manufacturer of the product or service 

involved. Based on the survey results, an estimated 53.7 percent of consumers 

who experienced an incident complained to the seller or manufacturer, and 18.6 

percent directed their complaints to a bank or credit card company. An estimated 

8.4 percent of consumers complained to an “official source” – a local, state, 
ES-7

Executive Summary

or federal government agency or a Better Business Bureau. Knowing which 

types of consumers complain and to whom will help the FTC determine the 

representativeness of the Consumer Sentinel database of fraud complaints.

Women and Younger Consumers More Likely to Complain

Women and younger consumers were more likely to complain when they 

believed they had been defrauded. An estimated 74.5 percent of women who 

were victims complained to someone about their experience. For men, the 

complaint rate was 10 percentage points lower. Similarly, almost 75 percent 

of consumers under the age of 35 complained, compared to 55.4 percent of 

consumers between 55 and 64.

The survey found that those consumers who used a credit card were no more 

or less likely to complain than those who used another payment mechanism. 

However, consumers who used a credit card were more likely to complain to a 

bank or credit card company, and less likely to complain to an official source. At 

the same time, consumers who used an online payment service were more likely 

to complain to an official source – twice as likely as those who paid with cash, 

and about ten times as likely as those who paid with a credit card.

Credit Card Users More Likely to be Satisfied with Results of Complaints

Overall, almost 60 percent of survey participants who complained said 

they were either “very” satisfied or “somewhat” satisfied with the result of their 

complaint; 40 percent indicated that they were either “not too satisfied” or “not at 

all satisfied.”

Consumers who complained were more likely to be satisfied with the results 

when they had used a credit card in the transaction (62.6 percent were satisfied) 

than when they had paid with cash (28.0 percent were satisfied). Those who did 

not lose money were more likely to be satisfied (77.0 percent were satisfied) than 

those who did. Still, 28.2 percent of those who lost $100 or more said that they 

were satisfied with the result of their complaint.

Public Opinion Strategies conducted the telephone survey for the FTC, 

and developed the survey instrument together with staff in the FTC’s Bureau 

of Economics and Bureau of Consumer Protection. This report is based on the 

survey and subsequent analysis of the data by staff of the Bureau of Economics. 

In analyzing the results of the survey, particular assumptions and methodologies 

were employed. In each instance, the assumptions are set forth in the report, with 

an explanation of the reasons a particular route was chosen. Although alternative 

approaches would yield differences in specific estimates, the staff does not believe 

they would noticeably alter the report’s central conclusions.
ES-8

Consumer Fraud in the United States: An FTC Survey 

Table ES-2: Percent of Survey Participants Who Are Victims of Frauds, by Single Characteristic

A. By Race and Ethnicity

Fraud Only

Fraud and Unauthorized 

Changes in Long 

Distance Service

Hispanics 14.3% 26.7%

African Americans 17.1% 24.1%

American Indians or Alaska Natives 33.8% 38.0%

Non-Hispanic Whites 6.4% 12.5%

Others 7.3% 11.7%

B. By Expected Income Three Years in the Future

Fraud Only

Fraud and 

Unauthorized Changes 

in Long Distance 

Service

Will be much lower 11.0% 21.3%

Will be slightly lower 7.2% 12.7%

Will be about the same 5.0% 11.4%

Will be slightly higher 9.6% 15.3%

Will be much higher 14.2% 23.5%

C. By Comfort with Current Level of Debt

Fraud Only

Fraud and 

Unauthorized Changes 

in Long Distance 

Service

More debt than can comfortably handle 19.2% 27.3%

About as much debt as can comfortably handle 9.1% 15.4%

Could handle more debt than currently have 8.1% 15.1%

Do not have any personal debt 2.7% 8.6%

 D. By Age

Fraud Only

Fraud and 

Unauthorized Changes 

in Long Distance 

Service

18 - 24 8.3% 11.4%

25 - 34 11.1% 18.4%

35 - 44 11.1% 18.2%

45 - 54 8.7% 17.4%

55 - 64 6.1% 10.7%

65 and over 4.7% 10.9%
Chapter 1: Introduction

1

Chapter 1: Introduction

One of the key functions of the Federal Trade Commission (“FTC” or 

“the Commission”) is to protect consumers from fraudulent, deceptive, and 

unfair practices. The Commission has brought many law enforcement actions 

against individuals and businesses who injure consumers by making fraudulent 

representations. In addition, the Commission seeks to educate consumers about 

how they can protect themselves from fraud.

From fiscal year 1995 through fiscal year 2003, the Commission and its 

law enforcement partners brought 2,215 law enforcement actions directed at 

fraudulent operators, including those who promote Internet frauds, fund-raising 

fraud, fraudulent offers promising consumers a credit card in return for the 

payment of an advance fee, and Internet auction fraud. Of these actions, the 

Commission brought 522 cases itself.1 The Commission estimates that its antifraud law enforcement actions in fiscal years 2002 and 2003 saved consumers 

more than $1.15 billion.2 Moreover, in fiscal year 2003 alone, the Commission 

estimates that it distributed 28 million copies of its various consumer education 

publications, either in paper form or electronically, to raise awareness of the latest 

frauds.3

The Commission’s law enforcement experience shows that the problem 

of consumer fraud is large. However, law enforcement may not provide a 

comprehensive picture of the types and extent of frauds in the marketplace – it 

shows only the extent of the harms caused by the firms the Commission sues. Nor 

is comprehensive information on the extent of consumer fraud readily available 

from other sources.

To develop more systematic information on the extent of consumer fraud, the 

Federal Trade Commission commissioned a survey of consumer experiences with 

fraud. The survey was conducted in late May and early June of 2003. This study 

reports on the FTC staff’s analysis of the results of that survey.

Chapter 2 describes the various kinds of consumer fraud covered by the 

survey. Chapter 3 presents basic survey results, including estimates of the number 

of U.S. consumers who were victims of these various frauds, as well as the 

number of incidents of these frauds. How much money consumers typically lost 

if they were victims and how the fraudulent offers were promoted to consumers 

are also examined. Chapter 4 examines whether the likelihood of being a victim 

varies with consumers’ demographic characteristics, such as age or level of 

1. For the fiscal year 2003 figures, see Federal Trade Commission, Budget Summary, Fiscal Year 2005 

Congressional Justification, p. 4. (Found at http://www.ftc.gov/ftc/oed/fmo/budgetsummary05.pdf, visited 

March 2, 2004.) For the 1995 to 2002 figures see Federal Trade Commission Performance Report for Fiscal 

Year 2002, p. 17. (Found at http://www.ftc.gov/opp/gpra/prfy2002.pdf, visited March 2, 2004.)

2. Id., p. 17.

3. Budget Summary, p. 17.
Consumer Fraud in the United States: An FTC Survey

2

education. Finally, Chapter 5 discusses which consumers are more or less likely 

to complain about being a victim of a fraud and which consumers are more likely 

to be satisfied with the results of any complaints they make. The remainder of 

Chapter 1 is devoted to a brief review of other studies that provide empirical data 

on consumer fraud.

Other Studies

Only a limited amount of empirical work has been done on consumer fraud 

and its victims. The National Institute of Justice in the U.S. Department of 

Justice (“DOJ”) sponsored a November 1991 survey of a random sample of 1,246 

consumers aged 18 and over.4 This survey, which asked participants about their 

experiences with specific types of problems, found that 15 percent of participants 

had been the victim of a successful personal fraud in the 12 months prior to the 

interview.5 However, in 10 percent of these cases, the consumer lost no money. 

Therefore, 13 percent of survey participants reported suffering direct monetary 

injury as a result of a successful fraud.6

The DOJ researchers also found that the likelihood of being a victim of a 

successful fraud and of losing money varied with a consumer’s age and level of 

education. They found that older consumers were less likely to be victims. Also, 

those who had not graduated from high school were less likely to be a victim than 

were those who had more education.7

A second source of information on consumer experiences with fraud is a 

series of surveys conducted for AARP. One of these surveys, from December 

4. The results of this survey have been published in a number of places including Richard M. Titus, Fred 

Heinzelmann, and John M. Boyle, “Victimization of Persons by Fraud,” Crime and Delinquency, 41 (January 

1995), pp. 54-72.

5. Titus et al., report that their survey was designed to measure both attempts to defraud and successful 

efforts. However, in several of the areas included in the survey, it is not clear that consumers would be able 

successfully to identify an attempt to defraud them, unless they actually fell for the scam. For example, the 

survey asked whether “anyone [had] ever sold or tried to sell you what they claimed was a lottery ticket, or 

a ticket of admission, which turned out to be fake” and whether “anyone [had] promised you a prize, a free 

vacation, or a free sample, which later turned out not to be free or ended up costing you more than the prize, 

vacation or sample was worth.” (Survey questions 9 and 17. The survey questions are reprinted at pages 68 

- 71 of Titus et al.) Because it seems unlikely that consumers would, in many cases, know whether someone 

had attempted to defraud them, the FTC survey was designed to inquire only about cases where the attempt to 

defraud was successful.

6. The results of this survey are not directly comparable to those of the FTC survey because they deal 

with different types of fraud. In particular, the DOJ survey asked about several “local” fraud problems, such 

as problems with automobile or appliance repairs and with home repairs and improvements that were not 

included in our survey. In addition, several of the frauds examined in the current study were not included in 

the DOJ survey.

7. Titus et al., p. 60. These authors claim that individuals with a masters degree or beyond are also less 

likely to be a victim of fraud than those with intermediate levels of education. However, this result appears to 

be based on attempted frauds, not successes. When FTC staff examined only the successful frauds reported 

in the DOJ survey, we found no significant differences in the DOJ data among groups with a high school 

education or beyond.
Chapter 1: Introduction

3

1998, involved interviews with 1,504 adults over the age of 18.8 The sampling 

procedure was designed to allow the survey results to be projected to the 

population at large. Based on this survey, AARP reported that “Three quarters 

of those in the study (74%) report that they had at least one bad experience when 

buying a product or service in the year preceding the interview.”9 This figure 

was derived from responses to a series of questions about specific things that 

may have happened to consumers when making a purchase. These included 

whether consumers had purchased “a product that was defective, or did not work 

properly,” whether “a product or service you bought was not received in the time 

it was promised,” and whether “you were given a written estimate for repair work, 

but the final bill turned out to be much higher than the estimate.”10 Although 

each of these problems may result in consumer injury, it is not clear that all such 

occurrences would constitute a fraudulent offer.

A better measure of the extent of consumer fraud comes from the question 

from the AARP survey that asked “Thinking about all the bad experiences 

you have EVER had as a consumer, was there ever a time you felt you were 

the subject of a MAJOR consumer swindle or fraud?” Seventeen percent of 

survey participants answered this question affirmatively.11 One weakness of this 

question, however, is that it failed to define what was meant by a major swindle or 

fraud. Each consumer was left to define the term for him or herself. Thus, there 

is likely to be inconsistency in the answers given by different consumers.

In addition to estimating the share of adults who had been a victim of a bad 

buying experience or a major fraud or swindle, AARP analyzed how these figures 

varied with the consumer’s age. They found that older consumers – those who 

were 65 or over – were less likely to report that they felt that they were deceived 

or taken advantage of during a purchase transaction within the last year. Although 

80 percent of consumers between 18 and 49 reported feeling deceived or taken 

advantage of in the last year, only 72 percent of those between 50 and 64 years 

of age and only 60 percent of those who were at least 65 did so.12 Similarly, 

although 19 percent of consumers under the age of 65 said that they had been the 

8. See, American Association of Retired Persons, Consumer Behavior, Experiences and Attitudes: A 

Comparison by Age Group, 1999. AARP conducted another consumer experience survey in December 2002 

and January 2003. (See, AARP, 2003 Consumer Experience Survey: Insights on Consumer Credit Behavior, 

Fraud and Financial Planning, 2003.) Because the 2002-03 survey was limited to consumers who were at 

least 45 years old, however, the results of that survey are not directly comparable to the findings of the FTC 

survey.

9. Id., p. 19.

10. Id.

11. Id., p. 21. Although the FTC survey relies primarily on specific questions about particular types of 

consumer experiences, it did include a question similar to the one in the 1998 AARP survey: “Now, thinking 

about your experiences as a consumer, was there ever a time when you felt you were a victim of a consumer 

fraud?” (Survey question 10) Twenty-eight percent of participants in the FTC survey answered this question 

in the affirmative.

12. Id., p. 19.
Consumer Fraud in the United States: An FTC Survey

4

victim of a major consumer fraud or swindle sometime during their lifetime, only 

8 percent of senior citizens indicated that they had been a victim.13

In addition to its consumer experience surveys, AARP has conducted 

two other empirical studies of telemarketing fraud – one in 1996 and one in 

2003.14 The samples used in these studies, however, are not random samples of 

consumers, but samples of known fraud victims.15 As such, the studies cannot 

be used to estimate the incidence of consumer fraud. Rather, their purpose is to 

understand the characteristics of those who are victims of frauds. In addition, the 

samples consisted solely of older consumers – those age 50 and over in the 1996 

study and those 45 and above in the 2003 study.

The 1996 study found that 

Victims in this survey ... are more affluent and more educated than other 

people age 50 and older.... Almost all victims own their own homes, and 

close to a third have college degrees. Just under half (43%) have annual 

household incomes of $30,000 or more compared with just over a third 

(38%) of all adults 50 and older.... Forty-three percent have assets, not 

including home equity, of at least $50,000 and 28 percent report assets of 

$100,000 or more.16

The study also found that victims are not socially isolated, contrary to what 

has often been suggested.17 In addition, the study found that victims say that 

they do not like telemarketing calls, they try to avoid them, and they are skeptical 

of the sales presentations. Furthermore, 90 percent of victims believe that it is 

acceptable to hang up on a persistent telemarketer, though the study suggests that 

some of the victims have trouble actually hanging up.18

13. Id., at 21. Interestingly, AARP found that the percentage of consumers who felt that they had been a 

victim of a major fraud or swindle was highest for those between 50 and 64 years of age. Of this group, 23 

percent said that they had been a victim at some point in their lives. This compares with 18 percent of those 

under age 50 and 8 percent of those 65 and over.

14. American Association of Retired Persons, Telemarketing Fraud Victimization of Older Americans: 

An AARP Survey, 1996, and AARP Foundation, Off the Hook: Reducing Participation in Telemarketing 

Fraud, 2003.

15. In the 2003 study of fraud victims, AARP did include a randomly-drawn sample of consumers so 

that they could compare the characteristics of victims to those of the population at large. In the 1996 study, 

the findings for victims were compared with the results of a random survey of all consumers that had been 

conducted by the contractor for another client in the previous year.

16. AARP (1996), p. 7.

17. Id., p. 4.

18. Id., p. 10. The authors of the study acknowledge that it is difficult to know whether the opinions 

expressed in the survey represent the views of victims at the time they were victimized or whether their views 

changed as a result of their fraudulent experiences.

In addition, it is not clear that the sample of victims included in this survey is demographically 

representative of victims in general. The sample used in the 1996 study was drawn from lists of victims of 

nine frauds. The lists were provided by the District Attorney for Denver, Colorado, and the Florida State 

(continued...)
Chapter 1: Introduction

5

In the 2003 study of fraud victims, AARP examined the characteristics of 

victims of two different types of frauds – a lottery scam and an investment scam. 

The study found that the characteristics of victims of the two types of fraud differ 

from each other and from the general population of those age 45 and over.

19 

Further, it found that many victims tend to deny that they have been the victim of 

a fraud and to understate the amount of money they have lost as a result.20

In conclusion, only a few recent studies examine consumer fraud and its 

victims. This FTC study is designed to add to our knowledge by providing more 

current information on consumer fraud generally and more detailed information 

on the specific types of fraud most frequently reported in the Commission’s 

Consumer Sentinel fraud complaint system. The results of this survey will permit 

the Commission to target education campaigns and law enforcement initiatives 

more precisely towards particular consumer groups who are most at risk of 

falling victim to fraud but who may not have complained to the FTC about their 

experiences.

18. (...continued)

Attorney General. At least six of the nine victim lists included only victims who had either complained to 

authorities or who had filed affidavits as part of the legal proceedings. The demographic characteristics of 

those who have filed complaints, or have been willing to provide affidavits, may not be representative of all 

victims across a wide range of frauds. Chapter 5 of this study investigates how the likelihood of complaining 

varies across groups with different demographic characteristics and finds that women, consumers who make 

relatively greater use of the Internet, those with more education, and younger victims are more likely to 

complain.

19. Off the Hook, p. A-10.

20. Id., p. A-15. The study’s authors point out, however, that at least some of the under-reporting 

may have been the result of the way the survey questions were structured. The questions that were used 

to decide whether a person admitted to being a victim of a fraud asked about sending money to “callers 

from organizations you are not personally familiar with.” If, as is sometimes believed to happen, fraudsters 

attempted to gain the victims’ confidence by making multiple calls to a victim before asking for money, then 

the victims may have felt that they knew the organization before they sent any money.

In addition, because the AARP study was designed to learn about actual victims of a fraud, the survey 

caller asked to speak with the particular victim. (See, Off the Hook, Appendix C-3.) This may have made 

participants less willing to admit to being a victim of a fraud than in a more anonymous survey, such as the 

present one, where the name of the individual being interviewed is never collected.
Consumer Fraud in the United States: An FTC Survey

6
Chapter 2: Description of the Survey

7

Chapter 2: Description of the Survey

To learn more about the types and extent of fraud perpetrated on U.S. 

consumers, the Federal Trade Commission commissioned a telephone survey of 

2,500 randomly-chosen adults.21 The survey was conducted between May 20 and 

June 3, 2003, and asked participants about their experiences during the year prior 

to the interview.

Types of Fraud Investigated

Although most consumers have some notion of what fraud is, those notions 

may differ. In designing the survey, we were therefore concerned about simply 

asking whether participants had experienced fraud.22 If some participants 

included certain types of experiences as fraud, while others did not, the resulting 

measures of the incidence of fraud would be subject to considerable measurement 

error, and the study would be less useful.

To avoid this problem, we constructed the survey to focus on specific 

experiences that consumers might have had and which might have been 

fraudulent, rather than solely asking generally whether the consumer had 

experienced fraud.23 Participants were first told:

Now we would like to ask you about some types of frauds that happen 

to consumers. Since there are a lot of ways in which a consumer might 

be cheated or be a victim of fraud, I am going to read you descriptions 

of some ways in which consumers are sometimes cheated or become 

victims of fraud. Please tell me which of these things, if any, have 

happened to you in the past year.

21. The survey was conducted for the Commission by Public Opinion Strategies. The survey instrument 

was developed collaboratively by the contractor and staff in the Commission’s Bureau of Economics and 

Bureau of Consumer Protection. The sample was drawn proportional to the number of adults in each state 

and also to obtain the correct ratio of female to male interviewees. It was conducted using a random digit 

dialing sampling methodology. The contractor provided weights to adjust for sampling and response rate 

issues. Unless otherwise noted, the results reported here are based on the weighted survey results.

22. The word “we” as used in this report refers to the author of the study and/or the staff of the Bureaus 

of Economics and Consumer Protection. It does not refer to the Federal Trade Commission or any of the 

Commissioners.

23. Before asking about the specific types of fraud, one question asked participants if they ever felt they 

“were the subject of a consumer fraud.” (Survey question 9) Approximately one half of those who indicated 

that they had such an experience were then asked to describe the event that led to this feeling. The responses 

to this question are discussed below.
Consumer Fraud in the United States: An FTC Survey

8

We asked about ten specific types of experiences designed to cover many of 

the frauds that have led to FTC enforcement actions. In addition, we asked about 

two more general types of experiences that may indicate fraud. Finally, we asked 

participants whether their long distance service had been changed without their 

authorization.24

Specific Types of Fraud

In deciding which frauds to include in the survey, we focused on those that 

have generated the greatest number of complaints in the FTC’s Consumer Sentinel 

database of fraud complaints.

Advance Fee Loans and Credit Cards

The FTC frequently receives complaints about offers for a loan or credit 

card in return for the payment of a fee.25 These offers, which are often directed 

to consumers with tarnished credit records, require that the consumer pay the fee 

before the promised loan or credit card is received. In most instances, however, 

consumers who pay the required fee do not receive the promised loan or credit 

card. Indeed, it is a violation of the Telemarketing Sales Rule to ask for a 

payment before delivering a promised credit card or loan, if the offer is made by 

telephone.26

To assess the frequency with which this problem occurs, the survey asked “In 

the past YEAR, have you paid money to anyone who promised or guaranteed to 

provide you with a credit card or loan, other than a mortgage loan, but required 

you to pay a fee before receiving the credit card or loan?”27 As with all of the 

24. Questions about the various types of frauds were asked in a randomized fashion, though questions 

about similar types of frauds – e.g., those related to unauthorized billing or those related to employment or 

business opportunities – were asked together. The randomization routine involved first randomizing the 

areas of inquiry and then randomizing the order of the questions within the area. When participants indicated 

that they had had a particular experience about which they were being asked, all of the follow-up questions 

were then asked before the questions related to different types of frauds were resumed. The complete survey 

instrument is included in the Appendix.

In addition to the specific areas discussed in the text, the survey also asked participants whether in the 

last year they had “purchased something where the item ... received turned out to be of substantially lower 

quality than what was originally represented....” (Survey question 50) We have not included responses to 

this question in this report. When participants who indicated that they had such an experience were asked to 

describe how the item they received differed from what they expected (Survey question 55), the descriptions 

very often seemed to involve something that was more of a bad purchase experience than an experience with 

fraud.

25. See, e.g., FTC v. Assail, Inc., et al., Civ. No. W03CA007 (W.D. Tex. (filed Jan. 9, 2003)) (FTC 

Matter Number X030021); FTC v. 9094-5114 Quebec, Inc., Civ. No. 03 C 7486 (N.D. Ill. (filed Oct. 23, 

2003)) (FTC Matter No. X040003); FTC v. ClickForMail.com, Inc., Civ. No. 03 C 3033 (N.D. Ill. (filed May 

7, 2003)) (FTC Matter No. X030054); FTC v. Bay Area Bus. Council, Inc., Civ. No. 02 C 5762 (N.D. Ill. 

(filed Aug. 13, 2002)) (FTC Matter No. X020103).

26. See Telemarketing Sales Rule, 16 C.F.R. 310.4(a)(4).

27. Survey question 16. Mortgage loans were excluded from the question because it is common business 

practice for those applying for a mortgage loan to pay for items such as credit reports and property appraisals 

before the loan is approved.
Chapter 2: Description of the Survey

9

types of fraud in the survey, participants who answered in the affirmative were 

then asked “How many times has this happened to you in the past year?”28 These 

participants also were asked whether they had actually received the promised loan 

or credit card.29 Only those who had not received the promised loan or credit card 

were considered to be victims of a fraud.30

Credit Repair

Consumers who have trouble obtaining credit because of negative 

information in their credit records are sometimes targets of offers claiming that 

the seller, in exchange for a fee, will help the consumer improve his or her credit 

record and thus enable the consumer to obtain credit. The survey asked specific 

questions about two types of so-called “credit repair” schemes, both of which are 

illegal under the Credit Repair Organizations Act.31

The first type of scheme involves a false claim that the seller can remove 

derogatory information from a credit report – even though it is accurate and even 

though the credit reporting agency is legally permitted to include the information 

in the credit report – and thereby improve the consumer’s ability to obtain credit. 

Consumers are generally required to make an up-front payment to obtain these 

services. Not surprisingly, little, if any, of the negative information is actually 

removed after consumers pay the required fee.32 To assess the extent of this 

fraud, survey participants were asked: “In the past YEAR, have you paid money 

to anyone who promised or guaranteed to remove negative, but true, information 

from your credit record, but failed to get the information removed?”33

In the second type of scheme, the seller promises – in exchange for a payment 

– to tell consumers how to create a new identity to use in applying for credit. 

Typically, the seller directs the consumer to obtain a new personal identification 

number, often an employer identification number (“EIN”), and then to use this 

number in applying for credit, rather than his or her Social Security number. The 

seller claims that by using the new identity on credit applications, the consumer 

28. Responses concerning the number of times the event occurred are coded in the same question as the 

original question. Thus, the responses to question 16 show both whether the person indicated that they paid 

money for a loan or credit card and, if so, how many times this happened in the last year.

29. Survey question 17. As with all follow-up questions, those participants who indicated that they had 

paid an advance fee for a loan or credit card more than one time in the past year were asked to focus on the 

most recent time they had done so in answering this question.

30. About 27 percent of those who said that they had paid money to obtain a promised credit card or loan 

said that they had actually received the credit card or loan.

31. Pub. L. No. 104-208, 110 Stat. 3009 (September 30, 1996).

32. See, e.g., FTC v. ICR Services, Inc., Civ. No. 03 C 5532 (N.D. Ill. (filed Aug. 8, 2003)) (FTC Matter 

No. X030077); FTC v. Jordan Maxwell, Civ. No. 03-0128 (C.D. Cal. (filed Jan. 7, 2003)) (FTC Matter No. 

X030030).

33. Survey question 13. Although the survey question only asked about instances where the participant 

paid money for credit repair services that were not, in fact, provided, the Credit Repair Organizations Act 

makes it illegal for a credit repair organization to charge or pay for any credit repair services in advance of 

providing those services in full. (15 U.S.C. 1679c(b)).
Consumer Fraud in the United States: An FTC Survey

10

can hide derogatory credit report information from potential lenders. The survey 

question related to this scheme was: “In the past YEAR, have you paid money to 

anyone who promised or guaranteed to provide information to help you create a 

new credit identity or new credit record?”34

Credit Card Insurance

The final credit-related fraud we examined involves the sale of insurance that 

purportedly protects consumers from unauthorized charges to their credit card 

accounts. Federal law limits consumers’ liability for the misuse of their credit 

cards to $50,35 and credit card companies often do not require that consumers pay 

even this amount. Nevertheless, some fraudulent operators attempt to defraud 

consumers by misrepresenting that card holders face considerable financial risk 

if their credit cards are misused. These operators then offer to sell consumers 

insurance to protect against this purported risk.36

To examine this type of offer, participants were asked: “In the past YEAR, 

have you paid money to anyone who promised or guaranteed to provide insurance 

to protect you against the unauthorized use of your credit cards?”37

Unauthorized Billing for Buyers’ Club Memberships

The survey also examined the practice of billing consumers without their 

consent for memberships in a buyers’ club or for publications that promise to 

show the consumer how to save money. A buyers’ club is designed to permit 

consumers to purchase products at a lower price than is generally available, and 

buyers’ clubs are not inherently problematic. 

The Commission has taken action against the deceptive marketing of buyers’

clubs, however.38 In recent years, for example, sellers have offered a membership 

in a buyers’ club as an add-on or “upsale item” at the end of a telemarketing 

sale. Having completed the sale that ostensibly was the reason for the call, the 

telemarketer then offers the consumer a free trial membership in a buyers’ club as 

a “thank you.” 

34. Survey question 14.

35. 15 U.S.C. 1643 (2004). See also, Federal Trade Commission, Bureau of Consumer Protection, 

Office of Consumer and Business Education, FTC Consumer Alert: Credit Card Loss Protection Offers: 

They’re the Real Steal, October 2000, at http://www.ftc.gov/bcp/conline/pubs/alerts/lossalrt.htm.

36. See, e.g., FTC v. Pac. First Benefit LLC., Civ. No. 02 C 8678 (N.D. Ill. (filed Dec. 2, 2002)) (FTC 

Matter No. X030010); FTC v. 1492828 Ontario, Inc., Civ. No. 02 C 7456 (N.D. Ill. (filed Oct. 17, 2002)) 

(FTC Matter No. X030001); FTC v. Efficient Telesales Services, Inc., Civ. No. 02 C 3776 (N.D. Ill. (filed 

May 28, 2002)) (FTC Matter No. X020069); FTC v. Consumer Alliance, Inc., Civ. No. 02 C 2429 (N.D. Ill. 

(filed Apr. 4, 2002)) (FTC Matter No. X020076).

37. Survey question 15.

38. See, e.g., FTC v. Wellquest Int’l, Civil Action No. 03-5002 (C.D. Cal. (filed Jul. 10, 2003)) (FTC 

Matter No. X030074); FTC v. Preferred Alliance, Inc., Civil Action No. 1:03-CV0405 (N.D. Ga. (filed Feb. 

12, 2003)) (FTC Matter No. X030022); US v. Richard L. Prochnow, Civil Action No. 02-CV-917 (N.D. Ga. 

(filed Apr. 9, 2002)) (FTC Matter No. X020054).
Chapter 2: Description of the Survey

11

Sometimes the membership is offered as a negative option, whereby the 

credit card that the consumer used to make the initial purchase is automatically 

charged for the price of the membership unless the consumer cancels the 

membership by the end of the free trial period. If the seller does not make the 

negative option clear, however, consumers may agree to accept the free trial 

offer believing that the membership will not continue beyond the free trial period 

unless the consumer affirmatively takes steps to continue the membership.39 

Consequently, consumers are charged for the membership without their 

authorization.40

Buyers’ clubs were just one of several problems involving unauthorized 

billing that were covered by the survey. This section of the survey began with a 

general question about whether, in the last year, participants had “been billed for a 

product or service which [they] did not agree to purchase or were ... billed for an 

amount that was substantially more than [they] expected to pay.”41 Participants 

who answered in the affirmative were then asked a series of questions designed 

to learn more about the products or services involved. In the case of buyers’

club memberships, the survey asked whether participants had been billed for “a 

publication or membership in a club that the seller told [them] would allow [them] 

to purchase something for a lower price than is generally available” but that they 

had not agreed to purchase.42

With regard to unauthorized billing, FTC staff recognizes that sometimes 

consumers may be billed for a product they did not order as a result of an honest 

mistake by a legitimate business. We do not want to count such mistakes as 

frauds. The survey, therefore, asked participants who indicated that they had 

experienced a billing-related problem whether they had sought a refund from the 

seller. When a refund had been sought, the survey then asked whether the seller 

provided a refund or other adjustment that the purchaser found acceptable.43 

Survey participants who answered in the affirmative are not considered to be 

39. Indeed, consumers may only be informed about the negative option in introductory membership 

information that is mailed to them after they have agreed to accept the free trial membership. This 

information is often sent by third-class bulk mail and many consumers do not open the mail because it 

appears to be unsolicited promotional materials.

40. The Commission addressed this problem in the amendments to its Telemarketing Sales Rule 

(“TSR”) that became effective March 31, 2003. Under the revised TSR, sellers are prohibited from using 

a consumer’s credit card account that the seller had previously obtained to charge for a membership that 

automatically converts from a free trial unless the consumer repeats at least part of the account number to the 

seller and gives his or her express agreement to be billed for the membership. (See 16 CFR 310.4(a)(6)(i).)

41. Survey question 18.

42. Survey question 21. It should be noted that, as worded, this question would not capture all problems 

that may arise with buyers’ clubs. For example, consumers who bought a membership in a buyers’ club 

and later found that the membership did not provide the promised amount of savings would not answer this 

question affirmatively.

43. Survey questions 26 and 27, which were asked following all affirmative responses to questions 19 

through 22.
Consumer Fraud in the United States: An FTC Survey

12

victims of a fraud in most instances, because they did not suffer any monetary 

harm as a result of the billing error.44

Participants who did not ask for a refund are somewhat harder to categorize. 

Some who failed to seek a refund probably did fall victim to fraud and would not 

have obtained a refund if they had asked for one. Others were likely dealing with 

legitimate firms and would have received one – and thus should not be considered 

victims of fraud. To address this issue, we have assumed that, had they asked, the 

same fraction would have received a refund as is observed for those who did ask. 

We make this assumption separately for each type of problem where the survey 

asked about refunds. For example, about half of those who asked for a refund 

after experiencing unauthorized billing for a buyers’ club membership actually 

received one. We therefore assumed that half of those who reported problems 

with buyers’ club memberships but did not ask for a refund would have received 

one had they asked. We therefore considered only half of those who did not ask 

for a refund to be victims of fraud.45

44. We have not applied this principle to consumers who suffered from unauthorized changes in their 

long distance telephone service (“slamming”), however. Because of the nature of the problem, all consumers 

who report having experienced slamming are counted as victims, even though they may not have suffered any 

monetary harm.

With respect to consumers who obtained refunds, we recognize that some of them may, in fact, have 

been defrauded. In some cases, for example, fraudulent operators may provide refunds to consumers who 

complain – particularly if the consumer complains to a Better Business Bureau or a legal authority. In this 

way, the fraudulent operator can appear responsive to consumer complaints and therefore avoid attracting the 

attention of law enforcement, while continuing to profit from consumers who are less aggressive. Moreover, 

consumers who obtain refunds nonetheless experience some injury because they must spend time and effort 

to obtain the refund or other adjustment. 

The survey did not ask specific questions about whether consumers sought and obtained refunds for 

some of the other types of fraud – e.g., the credit frauds discussed above. Victims of all frauds were asked 

how much money they had paid, however, and how much they had lost, as part of the fraudulent transaction. 

As with consumers who explicitly indicated that they had obtained a refund, consumers who indicated that 

they had not paid anything or that they had not lost anything as a result of a transaction are generally not 

considered to be victims of a fraud for purposes of this study. (See discussion at page 19, below.)

45. Our decision to treat as non-victims of fraud both those consumers who received refunds and those 

consumers who we project through imputation might have obtained refunds had they made such a request 

is a conservative one. It not only reduces the numbers for victims of fraud but it may initially seem to be at 

odds with some of the cases brought by the Commission. However, we do not believe that analysis used in 

a study such as this can be applied to the FTC’s fraud cases or vice versa. For example, the FTC has sued a 

number of companies that operate high-volume, low-dollar fraudulent credit card billing schemes to charge 

consumers’ credit card accounts without their authorization. See, e.g., FTC v. J.K. Publications, Inc., 99 F. 

Supp. 2d 1176 at 1201 (C.D. Cal. 2000). In such cases, the FTC frequently argues that most or even all of 

the transactions are fraudulent. After a trial, the court in J.K. Publications found that more than 90 percent 

of the transactions were demonstrably fraudulent. Even so, only about 15 percent of the more than $40 

million billed to consumers was credited or refunded to victims before the FTC brought its case. Applying 

the standard used in this study to the facts in that case would have yielded a result whereby consumers who 

received refunds – and even some who did not – would have been excluded from the pool of victims, when 

in reality virtually all of the transactions associated with the defendants were fraudulent. Applying the 

analysis from such cases to this study, however, would lead to an equally erroneous result. In the context 

of a randomized telephone study, we have very limited information about the nature of the businesses with 

whom the consumers were interacting. Therefore, to presume that either all or none of these transactions 

are fraudulent would be unsupportable. Consequently, we have adopted the more conservative approach 

explained above for the purposes of this study, but would not endorse its application to fraud cases brought 

by the FTC. 
Chapter 2: Description of the Survey

13

Unauthorized Billing for Internet-Related Services

The survey also examined unauthorized billing involving the provision of 

Internet-related services. In particular, we inquired whether consumers had been 

billed for either Internet access services or a web site that they had not agreed 

to purchase.46 This problem is illustrated by the Commission’s action against 

certain promoters of web-based “yellow-page” services that promised to list 

a small business in a yellow-page style directory. These sellers promised to 

provide consumers with a copy of the proposed web page and a free trial period 

for the service.47 Consumers agreed to receive the trial page believing that they 

could examine the page and then decide whether to pay for the service after the 

trial period. The promised copy of the page often did not appear, however, and 

the seller began billing the consumer before the expiration of the supposed trial 

period. Often these charges appeared on the consumer’s telephone bill, where 

they were frequently overlooked and just paid.

Unauthorized Billing for Information Services

The Commission’s cases have also involved unauthorized billing for 

information services, such as adult entertainment, gambling, or psychic services. 

These services can be provided either over the Internet or over a pay-per-call 

telephone line, such as a 900-number. In some cases, consumers have had their 

Internet service rerouted without their knowledge, resulting in very high charges 

for access to the information services provided.48 In other cases, the marketer of 

the information service persuaded consumers to provide credit card information 

supposedly for purposes unrelated to billing – such as to verify that the individual 

was of legal age – and then used the card number to bill consumers.49 

To investigate this type of problem, survey participants were asked if they 

had experienced a billing problem “while purchasing 900 number pay-per-call or 

Internet information services, such as adult entertainment, gambling, or psychic 

services.”50

46. Survey question 19 asked whether survey participants had the experience of being billed for a service 

that they had not agreed to purchase or of being billed for an amount that was substantially more than they 

anticipated paying “while purchasing Internet-related services, such as Internet access or a web-site.” As 

with other unauthorized billing problems, consumers who requested and received a refund were not counted 

as victims.

47. See, e.g., FTC v. Epixtar Corp., et al., Civ. No. 03-CV-8511 (DAB) (S.D. N.Y. (filed Oct. 28, 2003)) 

(FTC Matter No. X040008).

48. See, e.g., FTC v. Alyon Technologies, Inc., et al., Civ. No. 1:03-CV-1297(RWS) (N.D. Ga. (filed May 

13, 2003) (FTC Matter No. X030053); FTC v. BTV Industries, Inc., Civ. No. CVS-02-0437-LRH-PAL (D. 

Nev. (filed Mar. 27, 2002)) (FTC Matter No. X020029); FTC v. Verity International, Ltd., Civ. No. 00 Civ 

7422 (LAK) (S.D. N. Y. (filed Oct. 2, 2000) (FTC Matter No. X010001).

49. See, e.g., FTC v. The Crescent Publishing Group, Inc., et al., Civ. No. 00 Civ. 6315 (LAK) (S.D. 

N.Y. (filed Aug. 23, 2000)) (FTC Matter No. X000114); FTC v. J.K. Publications, Civ. No. CV-99-0444 ABC 

(AJWx) (C.D. Cal. (filed Jan. 19, 1999) (FTC Matter No. X990014).

50. Survey question 20. Again, those who asked for and received a refund were not considered to be 

victims.
Consumer Fraud in the United States: An FTC Survey

14

Pyramid Schemes

The survey also addressed the sale of pyramid marketing schemes.51 Pyramid 

schemes often claim that purchasers will operate their own businesses selling a 

particular product or service and that they will make money both from their own 

sales and from those of others they recruit to join the program. Although such 

a business may look like a legitimate multi-level marketing program, it differs 

because the income earned by participants comes ultimately from recruiting, 

rather than the sale of products or services to consumers. Most participants in 

pyramid schemes lose money because the program really just transfers money 

from those who have joined most recently to those who have been involved for 

a longer period of time. At any point in time, the vast majority of those who 

have joined the program – often 90 percent or more – will not have recouped the 

money they paid to join.52

To learn about the extent of problems with pyramid offerings, survey 

participants were first asked whether, in the past year, they had “paid anyone for 

an opportunity to operate [their] own business, such as a work-at-home plan, 

a business opportunity or a franchise.”53 To learn whether the business was a 

pyramid, participants were then asked whether they were “led to believe that most 

of the money [they] earned from this business would be from recruiting others to 

join the business, rather than from the sale of products.”54

Business Opportunity Offerings With False Earnings Claims or False Offers of 

Assistance

Business opportunity offerings also sometimes involve false promises that 

purchasers will make a large amount of money. Similarly, sellers sometimes 

make false promises that they will provide purchasers with assistance in finding 

customers or locations. For example, sellers of fraudulent vending machine 

business opportunities may promise to provide high-volume locations where 

purchasers can place their machines.55

51. Commission cases against promoters of pyramid schemes have included FTC v. NexGen300.com, 

Inc., Civ. No. CIV’03 120 TUC WDB (D. Az. (filed Feb. 18, 2003)) (FTC Matter No. X030035); FTC v. 

Trek Alliance, Inc., Civ. No. CV-02-9270 JSL (AJWx) (C.D. Cal, (filed Dec. 6, 2002)) (FTC Matter No. 

X030011); FTC v. Skybiz.com, Inc., Civ. No. 01CV0396K (E) (N.D. Okla. (filed May 30, 2001)) (FTC Matter 

No. X010046).

52. See, e.g., Vander Nat, Peter J., and William W. Keep, “Marketing Fraud: An Approach for 

Differentiating Multilevel Marketing from Pyramid Schemes,” Journal of Public Policy & Marketing, 21 

(Spring 2002), pp. 139-151.

53. Survey question 31. As in the other areas of the survey, participants who indicated that they had 

made such a purchase were then asked how many times they had made such a purchase in the last year. 

Those who indicated that they had made more than one such purchase were then asked to focus on the most 

recent such purchase in answering the remaining questions in this area.

54. Survey question 33.

55. Commission cases against promoters of fraudulent business opportunities have included FTC v. 

Ameritel Payphone Distributors, Inc., Civ. No. 00-514-CIV Gold/Simonton (S.D. Fla. (contempt entered Apr. 

9, 2004)) (FTC Matter No. X000012); FTC v. Greeting Cards of Am., Civ. No. 03-60746-CIV Gold (S.D. Fla.

(continued...)
Chapter 2: Description of the Survey

15

55. (...continued)

(filed Apr. 21, 2003)) (FTC Matter No. X030044); FTC v. Medical-Billing.com, Inc., Civ. No. 3-02CV0702P 

(N.D. Tex. (filed Apr. 5, 2002)) (FTC Matter No. X020046); FTC v. Accent Marketing, Inc., No. 02-0405-CBM (S.D. Ala. (filed Jun. 4, 2002)) (FTC Matter No. X020066).

56. As discussed above, the question about whether a participant had purchased a business opportunity 

was question 31 in the survey. Question 36 asked about unrealized earnings claims, while question 37 asked 

about promises of assistance that was not received.

When writing the questions to include in the survey, staff intended that survey participants would 

include information about various types of work-at-home schemes that have generated complaints to the 

Commission’s Consumer Sentinel system. It is possible, however, that some participants would not have 

interpreted the survey question in that way. This is particularly likely where consumers have been involved 

with something like an envelope stuffing or product assembly work-at-home scheme, which consumers may 

consider as a job offering rather than a business opportunity.

57. Given that the survey was limited to purchases that had been made in the last year, it is possible that 

some business-opportunity purchasers who indicated that they had not realized the promised level of earnings 

will do so in the future. It is not uncommon for a business to have lower earnings when it is just getting 

started than after the business has been in operation for some period of time.

Of 19 participants who said that they had purchased a business opportunity other than a pyramid, seven 

said that they had been led to believe that they would earn a certain amount of money from the business. Of 

these, five said that they had earned as much as they had been promised. Seven of the 19 also said that they 

had been promised assistance in locating customers and, of those, six said that the promised assistance had 

been provided.

Business opportunity offerings generally include some package of 

information, equipment, and services that purportedly will enable the consumer 

to establish and operate a successful business. Such offerings often appeal to 

consumers who have little or no business experience because they supposedly 

provide everything needed to own and operate the business. By promising 

that the business is certain to make at least a specific income, a seller can lead 

potential purchasers – particularly those without experience operating their 

own businesses – to believe that there is little risk in purchasing the business. 

Similarly, claims that the seller will provide consumers who purchase their 

business opportunity offerings with customers or selling locations can convince 

potential purchasers that they do not need to do much work to operate this 

business and that they are highly likely to succeed.

To measure the extent of problems with false earnings claims, survey 

participants who indicated that they had purchased a business opportunity were 

asked whether they had been “led to believe that [they] would earn a certain 

amount of income or profit from this business.” Those who answered in the 

affirmative were then asked “Did you earn at least roughly as much money as 

you had been led to expect?” Similarly, participants were asked whether they 

had been promised “help in locating customers who would use [their] services or 

allow [them] to sell [their] products from their premises,” and, if so, whether they 

had obtained the promised assistance.56 Victims of this type of fraud are limited 

to those who said that they had not made as much as had been promised or that 

they had not received the assistance that had been promised.57
Consumer Fraud in the United States: An FTC Survey

16

Government Job Promises

The survey also asked about a type of employment fraud in which the seller 

guarantees or represents that it is highly likely that consumers will obtain a 

government job. Often, these offers promise jobs with the Postal Service. The 

ads often look like “Help Wanted” ads, but in fact they are not placed by the 

government or anyone who can provide the promised jobs. Rather, they typically 

are offers to sell a course or study guide that supposedly will improve the 

consumer’s score on a test that is allegedly required to obtain the promised job. 

It is not clear that the materials offered can actually improve consumers’ scores, 

and in any event the ads frequently are run in areas where the test will not even be 

offered because there are no job vacancies to be filled.58

To identify consumers who had fallen victim to this type of 

misrepresentation, survey participants were asked “In the past year, have you 

paid anyone who promised that you would obtain a job at the U.S. Postal Service 

or another branch of state or federal government?” Those who answered in the 

affirmative were then asked “Did you get the job that was promised?”59 Anyone 

who had not received the promised job was considered a victim of this type of 

fraud.60

Prize Promotions

The final specific type of fraud investigated in the survey involves offers of 

free prizes. Prize promotions have been another frequent source of fraudulent 

representations and consumer complaints to the FTC. In these schemes, sellers 

tell consumers that they have won a prize – or that they have won one of four 

or five possible prizes – but that they must buy a product or make some other 

payment before they can receive their prize. Even when the seller does not 

directly tell consumers that they must make a purchase, consumers may be misled 

into believing that they are more likely to win the prize if they make a purchase. 

Alternatively, consumers may be told that they have to attend a sales presentation 

to receive the promised prize.61

58. The FTC sued a promoter of a government job promotion fraud in FTC v. American Career Services, 

Inc., Civ. No. 02-0593-CB-M (S.D. Ala. (filed Aug. 5, 2002)) (FTC Matter No. X020094).

59. Survey questions 32 and 38.

60. In fact, of the ten survey participants who indicated that they had paid for such an offer, nine said 

that they had not obtained the promised job, while the tenth person either indicated that he or she did not 

know or refused to answer the question.

61. Commission cases against promoters of fraudulent prize offerings, including lottery scams, have 

included FTC v. Dillon Sherif, et al., Civ. No. CV02-0294C (W.D. Wa. (filed Feb. 7, 2002)) (FTC Matter No. 

X020018); FTC v. World Media Brokers, Inc., et al., Civ. No. 02-C-6985 (N.D. Ill. (filed Sept. 30, 2002)) 

(FTC Matter No. X020110); FTC v. Global Network Enterprises, Inc., et al., Civ. No. SAC V 00-625GLT 

(ANX) (C.D. Ca. (filed Jun. 26, 2000)) (FTC Matter No. X000083).
Chapter 2: Description of the Survey

17

Sometimes, even though consumers make the payment or attend the 

presentation, they do not receive the promised prize or find that the prize they 

receive is not what had been promised.62 The survey sought to investigate this 

problem through a series of questions. First, it asked whether, in the last year, 

anyone had told survey participants that they had won a prize or been selected 

to receive an award, such as money, a free vacation, or some other product or 

service. Those who answered affirmatively were then asked whether they had 

been told that they had to pay something, purchase a good or service, or attend 

a sales presentation to receive the prize or award, and if so, whether they had 

made “the required payment or purchase or [had attended] the required sales 

presentation.” Finally, those who indicated that they had fulfilled the applicable 

requirements were asked whether they had received the promised gift or award 

and, if so, whether the award had been “essentially what had been described to 

[them].”63

More General Problems That May Be Associated With Fraud

In addition to the ten specific types of frauds described above, the survey also 

asked consumers whether they had experienced two more general problems that 

may indicate fraud.

Billing Problems, Other Products

In addition to asking participants if they had been billed for the particular 

products or services described above without their consent, the survey also asked 

more generally whether the participant had been billed for “some other product or 

service” that they had not agreed to purchase.64

Paid But Not Received

The survey also sought information about consumers who paid for a product 

or service but never received it. The Federal Trade Commission often receives 

complaints from consumers who report that they purchased an item and paid for 

it, but the seller never provided it. To gauge the extent of this problem, the survey 

asked participants: “Other than the things we have already discussed, in the past 

year have you purchased something which you paid for but NEVER received?”65

62. Prize promotions are regulated by a variety state and federal laws. See e.g., Telemarketing Sales 

Rule, 16 C.F.R. 310.3(a)(2)(iv)-(v). A prize promotion could be unlawful even if the promised prize is 

awarded. For the limited purposes of this survey, however, we elected not to include any instance where 

a consumer received the prize that was promised. This is again an effort to ensure that our estimates are 

conservative given the limitations of the survey data. As we explained in footnote 45, supra, the assumptions 

used for the purposes of this survey may not be applicable to calculations of injury in the FTC’s fraud cases 

where many more facts about the transactions may be available.

63. Survey questions 39 through 44.

64. Survey question 22. The specific types of unauthorized billing covered by the survey are discussed 

above.

65. Survey question 45.
Consumer Fraud in the United States: An FTC Survey

18

As with problems of unauthorized billing, if consumers fail to receive a 

product for which they paid, this failure may indicate that the seller was engaged 

in fraud. Alternatively, it may simply indicate a mistake made by an honest seller. 

As with the questions about billing, we attempted to differentiate between the 

legitimate and illegitimate by asking about the seller’s willingness to provide a 

refund or to make some other adjustment that was satisfactory to the purchaser.

66 

A willingness to make such an adjustment may indicate that the seller is more 

likely to be legitimate and just made a mistake, whereas a seller who refuses to 

make an adjustment or who makes it overly difficult for the consumer to obtain 

one is more likely to have fraudulent intentions.67

Switching of Long Distance Telephone Service Providers

The final problem investigated by the survey was the extent to which 

consumers had their long distance telephone service switched from one provider 

to another without their permission. To inquire about this practice – commonly 

referred to as “slamming” – the survey asked: “And in the past year, has your 

long distance telephone service been switched to another company without your 

knowledge or consent?”

Although we included unauthorized telephone service switching in the 

survey, this problem differs in some key respects from the others included in the 

survey. In the other areas we investigated, victims often obtain nothing of value 

in return for the money they pay. In these cases, the minimum amount of injury to 

the consumer can be approximated by the amount of money paid.

The same cannot be said about the switching of consumers’ long distance 

service. Although consumers (and businesses that provide long distance service) 

are harmed by slamming, consumers who are slammed can make long-distance 

calls and therefore receive something for the money they pay. Thus, the consumer 

injury from this practice is often primarily annoyance, loss of consumer choice, 

time spent undoing the switch, and any costs – such as fees to switch service 

– that are incurred in doing so.68

In addition, although consumers often complain to the FTC about slamming, 

telephone service is regulated by the Federal Communications Commission. 

Because of all these differences, this report discusses slamming separately from 

the other problems examined.

66. See survey questions 47 and 48. 

67. As with the cases of unauthorized billing, when the seller provided a refund or other acceptable 

adjustment, we do not consider the incident to be fraud. In addition, we assume that only a portion of those 

who did not seek a refund were victims of fraud. (See page 12, above.) As with unauthorized billing, 

excluding instances in which the consumer obtained a refund or other adjustment for an undelivered product 

may understate the extent of fraud, because some fraudulent sellers may make refunds to complaining 

consumers in order to appear legitimate and increase the likelihood that they can escape the attention of law 

enforcement.

68. The survey did not ask about any fees that consumers had to pay to return to their preferred carrier.
Chapter 2: Description of the Survey

19

Victims of Fraud or Targets of Fraud?

The survey questions were designed to identify consumers who were actual 

victims of frauds and not those who may have been the target of an unsuccessful 

attempt to defraud them. For example, participants were asked whether they had 

paid anyone for services designed to improve their credit records or create a new 

record. They were not asked whether anyone had attempted to sell them services 

that would improve or replace their credit records.

Nonetheless, in some cases the survey responses suggest that participants 

may have reported on attempted fraud. For example, participants who indicated 

that they had experienced a particular problem, such as paying someone to 

improve their credit record, were asked how much they paid for the service and 

how much they lost.69 In answering these questions, participants sometimes 

indicated that they had not paid anything or that they had not lost anything.

These responses may indicate that the participant was not an actual victim 

of a fraud but was reporting on an attempted fraud. In other cases, participants 

may have initially fallen for an offer, but obtained a refund or otherwise stopped 

payment.70 In deciding how to treat these consumer responses, we adopted 

a relatively conservative approach. First, we included consumers as fraud 

victims only if they appeared to have lost money.71 Similarly, we did not include 

consumers who indicated that they obtained a refund or other adjustment that the 

consumer found to be satisfactory.72 Finally, we included only some consumers 

69. See survey question 64, which was a follow-up question asked each time participants indicated that 

they had experienced one of the types of problems included in the survey. Where participants indicated that 

they had experienced the problem more than once in the last year, these questions were asked of the most 

recent event.

70. For example, if consumers used a credit card to pay for an item but realized before paying the bill 

that the offer was not as represented, they may have disputed the charge and refused to pay. (See, e.g., Federal 

Trade Commission, Bureau of Consumer Protection, Office of Consumer and Business Education, FTC Facts 

for Consumers: Fair Credit Billing, March 2002, at http://www.ftc.gov/bcp/conline/pubs/credit/fcb.htm.)

71. The one exception to this principle involves unauthorized switching of long distance telephone 

service. As discussed above, the primary loss in such cases is the annoyance, time, loss of consumer choice, 

and any fees incurred in switching back to the consumer’s preferred carrier.

72. The percentage of survey participants who indicated that they had experienced a particular type of 

problem but that they had not lost any money or had obtained a refund ranged from 0 percent (for those who 

had purchased a business opportunity and did not realize the promised level of earnings or did not receive the 

promised assistance) to 74 percent (for those who were billed for an Internet service that they had not agreed 

to purchase). Across the ten specific frauds examined, 46 percent of those who had experienced a problem 

indicated that they had not lost any money or had received a refund, and are therefore not counted as victims 

of frauds. Including the two more general types of frauds, the percentage of those who obtained a refund or 

otherwise lost no money rises to 53 percent.

By excluding instances in which participants initially fell for a fraudulent offer but were able to avoid 

losing money, we are understating the number of consumers who suffered some form of injury as a result 

of the fraudulent offer. In particular, consumers who succeeded in stopping payment or obtaining a refund 

may have had to expend significant time and effort to do so. This time and effort is a form of injury from the 

fraudulent offer, because the consumers could have done something else with that time if they had not been 

victimized.
Consumer Fraud in the United States: An FTC Survey

20

who did not seek a refund.73 By these exclusions, we have attempted to avoid 

treating legitimate business errors as fraud.

Consumer Purchasing Behavior

Before turning to an examination of the incidence of the various types of 

fraud in the next chapter, it is worthwhile to consider briefly what participants 

said in response to several questions about purchases made in response to 

telemarketing, television, or direct mail solicitations.74 Table 2-1 provides the 

responses to these questions both in aggregate and by the age of the participant.

First, of the 2,500 consumers who participated in our survey, 85.8 percent 

indicated that they had received at least one telemarketing call in the last year.

75 

The percentage varies significantly, however, depending on the consumer’s age. 

Of those between 25 and 64 years of age, 88.6 percent said that they had received 

a telemarketing call in the last year. However, only 74.8 percent of those between 

18 and 24 and 79.6 percent of those 65 and over said that they had received 

telemarketing calls.76

The survey then asked whether the participant had made a purchase or a 

charitable contribution in response to a telemarketing call. Considering purchases 

first, 3.7 percent of participants indicated that they had made at least one purchase 

in response to a telemarketing call from a company with whom they had not 

previously done business. More than half of those who reported such purchases 

– 56.9 percent – said that they had made only one such purchase, while another 

21.3 percent said that they made two purchases.77

Individuals between 25 and 34 were the most likely to make a purchase from 

a company with whom they had not previously done business in response to a 

telemarketing call, with 6.4 percent saying that they had made at least one such 

purchase in the last year. The percentage declined in older groups – only 1.4 

percent of participants aged 65 or over said that they had made such purchases in 

the last year. Younger consumers also were less likely than the 25 to 34 year old 

73. For a more complete discussion of the treatment of cases in which refunds were not sought, see page 

12.

74. See survey questions 1 through 6. In future research, we intend to examine whether making 

purchases in response to solicitations in these media has any relationship to the likelihood of being a victim 

of fraud.

75. We note that the survey was conducted prior to the implementation of the Commission’s National Do 

Not Call Registry.

76. The differences among age groups are jointly significant at the 1 percent level. Individually, the 

percentage of consumers between 18 and 24 years of age and of those aged 65 or older who had received a 

telemarketing call in the last year are each significantly lower than for those between 25 and 64 years of age 

at the 1 percent level. 

77. We do not report the average number of such purchases because the average value would be highly 

affected by the one individual who indicated that he or she had made 25 such purchases. The next highest 

number reported was 7.
Chapter 2: Description of the Survey

21

Table 2-1: Consumer Responses to Solicitations

Percent of consumers who,

in the past year, have Overall

By Age

Sig.a

18-24 25 - 34 35 - 44 45 - 54 55 - 64 65 and 

over

Received a telemarketing call 85.8% 74.8% 87.3% 89.9% 89.5% 87.5% 79.6% ***

Purchased something in response 

to a telemarketing call from a 

company with whom you have not 

previously done business

3.7% 1.8% 6.4% 4.9% 3.8% 3.2% 1.4% ***

Contributed to a charity to which 

you have not previously donated 

in response to a telemarketing call

7.9% 7.5% 12.3% 10.2% 5.7% 7.9% 4.7% ***

Placed an order for a product by 

telephone, Internet, or mail after 

receiving an unsolicited piece of 

mail from a company with whom 

you have not previously done 

business

9.1% 7.5% 13.4% 9.3% 9.4% 8.3% 6.5% **

Placed an order for a product by 

telephone, Internet, or mail after 

seeing a television advertisement 

or infomercial

22.3% 21.4% 25.3% 24.7% 24.4% 19.7% 17.7% * 

Purchased something from an 

Internet web site

37.9% 38.4% 52.0% 50.5% 43.5% 28.3% 14.5% ***

Note. 

a Indicates joint statistical significance of differences across age groups.

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level
Consumer Fraud in the United States: An FTC Survey

22

group to make such purchases: only 1.8 percent of participants between 18 and 24 

reported making at least one such purchase in the last year.78

Turning to charitable contributions made in response to a telemarketing call, 

more than twice as many participants – 7.8 percent – reported that they made a 

contribution to a new charity in response to a telemarketing solicitation within the 

last year. Forty-four percent of those who reported such contributions contributed 

to only one new charity, while another 26 percent say that they contributed to 

two.79

The variation in the likelihood of making contributions in response to a 

telemarketing call across different age groups is quite similar to the pattern of 

making purchases. As with telemarketing purchases, those between the ages of 

25 and 34 had the highest probability of making contributions to a new charity in 

response to a telemarketing call, with 12.3 percent of this group saying that they 

had done so in the last year. Consumers aged 65 and over were the least likely to 

have made a contribution to a new charity, with only 4.7 percent indicating that 

they had done so.80 However, the difference among age groups is less pronounced 

in the case of contributions: Whereas consumers between 25 and 34 years of 

age were 4.5 times as likely as those 65 and over to have made a purchase in 

response to a telemarketing call, they were only 2.6 times as likely to have made a 

charitable contribution.

The survey also asked about purchases made after seeing a television 

advertisement or infomercial, and about purchases made in response to an 

unsolicited direct mail solicitation. In both cases, the survey asked participants 

only about orders made by telephone, mail, or Internet. If consumers receive 

an ad in the mail or see an ad on television but then visit a store before making 

a purchase, they presumably have an opportunity to see the merchandise before 

buying.

78. The differences among age groups are jointly significant at the 1 percent level. Individually, the 

differences in the percentage of consumers making telemarketing purchases is significant at the 1 percent 

level in comparing the rate for those aged 65 and over to that for those who are between 25 and 34. The 

differences are significant at the 5 percent level in comparing the rate for those aged 18 to 24 or for those 

aged 55 to 64 to that for those aged 25 to 34. The difference between the 45 to 54 year old group and the 25 

to 34 group was significant at the 10 percent level.

79. Again, the presence of an extreme response from one individual – in this case a person who said that 

he or she made 200 such contributions – makes an average value unreliable.

80. Unlike telemarketing purchases, the youngest group of consumers – those between 18 and 24 – do 

not have the second lowest likelihood. Those between 45 and 54 were less likely to make contributions than 

those between 18 and 24.

Again, the differences among age groups are jointly significant at the 1 percent level. Individually, the 

difference in the percentage of consumers making telemarketing contributions is significant at the 1 percent 

level in comparing those aged 65 and over to those who are between 25 and 34. The difference is significant 

at the 5 percent level in comparing the rate for consumers aged 45 to 54 to the rate for those aged 25 to 34, 

while the difference between the 18 to 24 year old group and the 25 to 34 year old group is significant at the 

10 percent level.
Chapter 2: Description of the Survey

23

The third line of Table 2-1 presents data on purchases made in response to 

a direct mail solicitation. Without visiting a store, 9.1 percent of participants 

reported making a purchase from someone with whom they had not previously 

done business in response to such a solicitation. Just under 40 percent of those 

who made such purchases said that they made only one purchase. Another 27 

percent said that they made two purchases, while an additional 21 percent made 

three or four purchases.

Purchases made in response to a television advertisement or infomercial 

were clearly the most popular of the purchasing behaviors in Table 2-1. Almost 

one-quarter of participants – 22.2 percent – said that they had ordered a product 

in response to a television advertisement or infomercial without visiting a store.81 

As with purchases made in response to direct mail, just under 40 percent of those 

who made purchases in this way said that they had done so only once in the last 

year. Almost 30 percent said that they had made two such purchases, while about 

15 percent said that they had done so three or four times in the last year.

For purchases in response to both direct mail and television advertisements 

or infomercials, differences across age groups follow the same pattern as for 

telemarketing purchases and contributions. Consumers between 25 and 34 are the 

most likely to respond and those over 65 are the least likely. Indeed, the pattern 

for direct mail purchases is very similar to that for telemarketing contributions.82 

The differences across age groups, however, are less pronounced in the case of 

purchases made in response to a television advertisement or infomercial without 

visiting a store.83 Although those aged 25 to 34 were still the most likely to make 

such purchases and those 65 or over the least likely, they were only 1.4 times as 

likely as those over 65 to have made them.

81. To some extent the higher rate of response here may be caused by the fact that, unlike the questions 

discussed previously, the survey did not specify that purchases in response to a television ad or infomercial 

had to involve a company with which the consumer had not previously done business.

82. Across age groups, the differences in the likelihood of making purchases in response to direct mail 

solicitations are jointly significant at the 5 percent level. Individually, the rate for those aged 65 and over 

differed significantly from that for those aged 25 to 34 at the 1 percent level, while the rate for consumers 

aged 45 to 54 differed from the rate for the 25-to-34 group at the 5 percent level of significance. The rate for 

35 to 44 year olds differed from the 25-to-34 rate at the 10 percent level of significance.

83. For consumers who had made a purchase in response to a television advertisement or infomercial, 

the age variables are jointly significant at only the 10 percent level. The difference in the percentage making 

such purchases in the 65 and over group and those between 25 and 34 was significant at the 1 percent level, 

while the difference between the 55 to 64 year old group and the 25 to 34 year old group was significant at 

the 10 percent level.
Consumer Fraud in the United States: An FTC Survey

24

Finally, the survey asked consumers if they had made any purchases from an 

Internet web site in the last year.84 Thirty-eight percent of participants indicated 

that they had. Among those who made Internet purchases, 25 percent indicated 

that they had made at least ten Internet purchases in the last year, and the median 

number of purchases was four.85

Purchases from Internet sites vary strongly with age. More than half of 

consumers between 25 and 44 years of age said that they had made at least one 

purchase from an Internet web site in the past year. The rate of purchase for those 

who were older was considerably lower. For those in the 55 to 64 year old group, 

28.3 percent said that they had made an Internet purchase in the last year, and 

only 14.5 percent of those aged 65 or over had done so.86

84. As with purchases in response to a television ad or infomercial, the question about purchases from 

an Internet web site did not specify that purchases involve a company with which the consumer had not 

previously done business. The survey did not include a specific question asking whether purchases had been 

made in response to email, whether or not the email was unsolicited commercial email.

85. An average number of purchases is not reported because it is heavily influenced by five participants 

who said that they made 200 or more purchases during the year.

86. Across age groups, the differences in the likelihood of having made an Internet purchase are jointly 

significant at the 1 percent level. Individually, the rates for those in the 18 to 24, 55 to 64, and 65 and over 

groups are significantly different from the rate for the 25 to 34 year old group at the 1 percent level. The 

difference between the 45 to 54 year old group and the 25 to 34 year old group is significant at the 5 percent 

level.
Chapter 3: Which Types of Frauds Are the Most Common?

25

Chapter 3: Which Types of Frauds Are the Most Common?

In Chapter 2, we detailed the various problems explored in our survey. This 

chapter examines which of these problems is most common and their overall 

frequency. Our goal is to answer two important questions: First, how many 

consumers are victims of these frauds and/or slamming? Second, how many 

incidents of these problems occur?87 We also discuss the types of media used 

by fraudulent operators to convey their offers to consumers. Finally, we present 

evidence on the costs to consumers resulting from the frauds and slamming 

examined in the survey.

The Number of Victims

As shown in Table 3-1, the survey results suggest that 16.3 percent of adult 

Americans were victims of one or more of the frauds covered by the survey and/

or of slamming during the year before the survey.88 Extrapolating this result to the 

87. In considering the estimates of the extent of fraud – both the estimates of the number of victims 

and the number of incidents – it is important to keep in mind that some participants may not be aware that 

they were victims. This is particularly likely with frauds that involve being billed for a product or service 

that the consumer had not agreed to purchase. In many enforcement actions, the Commission has found that 

consumers have failed to notice charges placed on their credit card or telephone bills by fraudulent operators 

and have simply paid them. In the case of monthly recurring charges, this frequently happens for some 

months before the consumer notices the charge. Because such consumers would not be aware that they had 

been victimized, they could not describe the fraud in the survey.

There is also a possibility that some participants in the survey who were victims of one or more 

of the problems addressed may not have admitted that they were victims. In its most recent research on 

telemarketing fraud, AARP interviewed consumers who were known to have been victims of a foreign lottery 

scam or of an investment scam. Among other questions, the AARP survey asked participants whether they 

had been a victim of a major scam or swindle in the last three years in connection with “telephone callers 

from organizations you are not personally familiar with.” Only one-half of the known lottery victims and 27 

percent of known investment victims answered this question in the affirmative. (AARP Foundation, Off the 

Hook: Reducing Participation in Telemarketing Fraud, 2003, p. C-28.) That is, at least half of the known 

victims apparently denied that they had been a victim.

We have no way of knowing whether we have a similar problem with our results. Nevertheless, 

several differences between our survey and the one done by AARP may reduce the likelihood and extent of 

any denial of victimization. First, as AARP notes in its study, the fact that the question in that study focused 

on telephone calls from organizations with which the consumer was not personally familiar may have 

led some victims to answer the question in the negative because they felt that they were familiar with the 

organization that scammed them. (Id., p. A-15) The questions related to experiences with fraud in our survey 

did not focus on telemarketing calls from an unfamiliar source. Second, our survey did not ask consumers 

to indicate whether or not they were a victim. Rather, it asked about specific events that consumers might 

have experienced. Finally, because AARP wanted to interview known victims, they had to ask for specific 

individuals by name. In contrast, consumers participating in our survey were never asked to give their 

names and interviewers did not ask to speak with specific individuals. This procedure increased the degree 

of anonymity afforded participants and may have reduced the likelihood that they would deny having a 

particular experience.

88. The survey was conducted between May 20 and June 3, 2003, and therefore the results measure the 

extent of the various types of fraud during the last seven months of 2002 and the first five months of 2003.

(continued...)
Consumer Fraud in the United States: An FTC Survey

26

Table 3-1: Estimated Number of Adults Who Were Victims of Fraud or Had Their Long Distance 

Telephone Service Changed Without Permission, One Year Period Prior to the Surveya

Type of Problem

Number of

Adults

(millions)b

Percent of 

Populationb

Victims of Any Fraud Covered by the Survey or Unauthorized 

Changes in Long Distance Service

35.60

(32.45 - 38.75)

16.3%

(14.9% - 17.8%)

Victims of Unauthorized Changes in Long Distance Telephone 

Service (“Slamming”)

(1) 13.90

(11.75 - 16.10)

6.5%

(5.5% - 7.5%)

Victims of Any Type of Fraud, Specific or General, Included in the 

Survey

24.45

(21.85 - 27.10)

11.2%

(10.0% - 12.5%)

Victims of Specific Types of Fraud Included in the Survey 18.35

(15.95 - 20.70)

8.4%

(7.3% - 9.5%)

Paid an advance fee to obtain a loan or credit card that you were 

promised or guaranteed you would receivec

(2) 4.55 

(3.30 - 5.80)

2.1%

(1.5% - 2.7%)

Billed for buyers’ club memberships you did not agree to purchase (3) 4.05

(2.95 - 5.20)

1.9%

(1.4% - 2.4%)

Purchased credit card insurance (4) 3.35

(2.35 - 4.40)

1.6%

(1.1% - 2.0%)

Purchased credit repair (5) 2.00

(1.15 - 2.85)

0.9%

(0.5% - 1.3%)

Paid money or made a purchase to receive a promised prize and 

did not receive the prize or prize was not as promised

(6) 1.80

(1.10 - 2.55)

0.8%

(0.5% - 1.2%)

Billed for Internet services you did not agree to purchase (7) 1.75

(1.05 - 2.45)

0.8%

(0.5% - 1.1%)

Purchased a membership in a pyramid schemed (8) 1.55

(0.80 - 2.30)

0.7%

(0.4% - 1.1%)

Billed for information services provided either over the Internet or 

by pay-per-call that you had not agreed to purchase

(9) 0.80

(0.25 - 1.35)

0.4%

(0.1% - 0.6%)

Made a payment to someone who represented that you would 

receive a government job

(10) 0.65

(0.10 - 1.20)

0.3%

((x)e - 0.6%)

Purchased a business opportunity where promised earnings were 

not realized or promised assistance was not provided

(11) 0.45

(0.05 - 0.90)

0.2%

((x) - 0.4%)

Victims of More General Types of Fraud Included in the Survey 7.35

(6.00 - 8.75)

3.4%

(2.8% - 4.0%)

Billed for a product or service you did not agree to purchase or 

billed an amount significantly more than you expected, products 

other than those identified above

(12) 4.60

(3.50 - 5.70)

2.1%

(1.6% - 2.6%)

Paid for a product but did not receive it (13) 2.90

(2.05 - 3.80)

1.4%

(1.0% - 1.8%)

(Notes on next page)
Chapter 3: Which Types of Frauds Are the Most Common?

27

Table 3-1 (cont.)

Notes. 

a Projections are based on U.S. population of 217.76 million adults aged 18 and over as of July 1, 2003. (See U.S. 

Census Bureau, Population Division, Table ST-EST2003-01res: Annual Estimates of the Resident Population by 

Selected Age Groups of the United States and States: July 1, 2003 and April 1, 2000.) Numbers are rounded to the 

nearest 0.05 million and percentages to the nearest 0.1 percent. Amounts for individual categories will not sum to 

totals because some individuals are victims of more than one of the listed categories.

b Because we surveyed a sample of 2,500 individuals and not the entire adult population, there is uncertainty in 

these estimates. The numbers in parentheses in the table indicate the bounds of the 95 percent confidence intervals 

for the various estimates. For example, there is a 95 percent probability that the true number of victims of one or 

more of these problems lies between 32.45 million and 38.75 million consumers or between 14.9 percent and 17.8 

percent of adults in the United States. 

 Estimates in row (1) are significantly greater than those in all other rows, those in rows (2) and (12) are greater 

than those in rows (5) - (11) and (13), those in row (3) and (4) are significantly greater than those in rows (5) - (11), 

those in row (13) are significantly greater than those in rows (6) through (11), those in rows (5) - (7) are significantly 

greater than those in rows (9) - (11), and those in row (8) are greater than those in row (11). (All reported significant 

differences are significant at the 5 percent level or above.)

c These estimates assume that participants who said that they were required to pay an advance fee, but also said 

that they had received the promised loan, were not victims. If these participants are also considered to be victims, 

there were an estimated 6.20 million victims of advance fee loan or credit card scams.

d Participants who purchased membership in a pyramid scheme and who said that they had earned as much money 

as had been promised are not counted as victims. If these participants are considered to be victims, the estimated 

number of victims rises to 1.80 million.

e (x) denotes a value of less than 0.05 percent.
Consumer Fraud in the United States: An FTC Survey

28

U.S. adult population suggests that 35.60 million individuals were victims during 

that year.89

Notably, more than any single type of fraud, the problem that survey 

participants reported most frequently was having their long distance telephone 

service switched from one carrier to another without their permission. Of 

participants in the survey, 6.5 percent reported that they had been slammed during 

the last year. Projecting to the entire U.S. adult population, we find that 13.90 

million individuals experienced this problem.

Considering the different types of frauds investigated by the survey, we find 

that an estimated 24.45 million adults – 11.2 percent of the adult population in the 

United States – were victims of one or more of the frauds examined in the survey, 

including both the ten specific and the two general types of frauds.90 We further 

estimate that 18.35 million adults – 8.4 percent of the U.S. adult population 

– experienced one or more of the ten specific frauds studied, while approximately 

7.35 million individuals – 3.4 percent of the population – experienced one or 

both of the two more general fraud problems included in the survey. Based on the 

survey results, we estimate that most victims who experienced the specific frauds 

– more than 87 percent – experienced only one of the ten types.91

88. (...continued)

As discussed in the Methodological Appendix to this chapter, in some cases it was only possible to 

estimate a probability that a participant in the survey had been the victim of one or more types of fraud. In 

estimating the number of victims, both in total and for the specific types of frauds, these individuals were 

included, weighted by the appropriate probabilities. We make similar assumptions in estimating the total 

number of incidents.

89. The figures for the total number of victims or of the total number of incidents are simply 

extrapolations of the results of the survey findings to the entire U.S. adult population. Such an extrapolation 

is appropriate because the survey was a random survey of adults in the United States.

Because we surveyed a sample of 2,500 individuals and not the entire adult population, there is 

uncertainty in these estimates. The figures in the table in parentheses indicate the bounds of the 95 percent 

confidence intervals for the various figures. For example, there is a 95 percent probability that the true 

number of victims of one or more of these problems lies between 32.45 million and 38.75 million adult 

Americans or between 14.9 percent and 17.8 percent of adults in the United States.

As discussed in the previous chapter, one of the issues we had to resolve in estimating the number of 

victims of fraud was how to treat participants who had a particular experience that might have been a fraud 

but who had not attempted to obtain a refund. In arriving at the estimates presented in the text, we have 

assumed that some percentage of those who did not seek a refund would have received one if they had asked. 

We therefore do not treat everyone who did not seek a refund as a victim – rather, we count only the number 

of consumers who we estimate would not have received a refund even if they had asked. (See page 12, 

above.) 

90. To avoid double counting, each participant who experienced multiple incidents of any single type 

of fraud is counted as one victim when arriving at the estimates of the number of victims of fraud in total 

and of each of the types of fraud he or she experienced. On the other hand, when we estimate the number of 

incidents of fraud, the experiences of such persons account for multiple incidents. Because of the way victims 

are counted, the estimates of the number of victims of individual frauds do not add up to the total number of 

victims of any fraud, since one overall victim could be a victim of more than one of the fraud types.

91. The maximum number of specific frauds experienced by one victim was three. Approximately 0.6 

percent of survey participants experienced both one or more specific frauds and one or more of the general 

frauds. Including both specific and general frauds, 89 percent of victims experienced only one type of fraud 

and, again, the maximum number of types of fraud experienced by any one individual was three.
Chapter 3: Which Types of Frauds Are the Most Common?

29

Figure 3-1

Specific Types of Fraud

By Number of Victims

0.45 0.65 0.80

1.55 1.80 1.75

2.00

3.35

4.05

4.55

0.0

1.0

2.0

3.0

4.0

5.0

Advance Fee

Loans

Buyers' Clubs Credit Card

Insurance

Credit Repair Prizes Internet

Services

Pyramid

Schemes

Information

Services

Government

Job Offers

Business

Opportunities

In Millions

Source: Table 3-1

Table 3-1 

and Figure 3-1 

provide estimates 

of the number of 

consumers who 

experienced each 

of the ten specific 

types of frauds 

covered in the 

survey.92 The fraud 

that affected the 

largest number of 

participants was 

the payment of an 

advance fee for 

a “guaranteed” 

loan or credit card that the consumer never received. An estimated 4.55 million 

individuals – 2.1 percent of all adults in the United States – were victims of this 

fraud.93 

The second most frequently reported specific fraud was being billed for a 

membership in a buying club or for a publication that claims to tell the consumer 

how to save money while purchasing some type of product where the consumer 

had not agreed to purchase the membership or publication. This fraud was 

reported by 1.9 percent of survey participants, implying that 4.05 million U.S. 

adults were victims in the year before the survey was conducted. Ranking third, 

the purchase of credit card insurance was also reported by more than one percent 

92. In estimating the number of victims for each type of fraud, we had to account for those consumers 

who said that they did not know whether they had been a victim of a particular type of fraud. In addition, 

we had to deal with cases in which data on the amount of money lost was not available, either because the 

participant did not answer the relevant question or because the participant had multiple experiences, since 

the questionnaire only asked about the amount of money lost in the most recent incident in such cases. The 

Methodological Appendix to this chapter discusses our treatment of these issues.

93. While 2.1 percent of survey participants indicated that they had paid a fee to receive a promised, but 

undelivered, credit card or loan, an additional 0.8 percent indicated that they had made such a payment and 

had actually received the promised credit card or loan.

We have some reason to question whether the survey results may include more than just advance 

fee loan frauds. Survey participants who indicated that they had paid an advance fee to someone who had 

promised them a loan or credit card were asked how they first learned about the offer and how they made the 

purchase. In about half of these cases, participants indicated that they had first learned about the offer from 

a direct mail solicitation. Of these, half also said that they also purchased the credit card or loan through the 

mail. In the FTC staff’s enforcement experience, most advance fee loans are not marketed or sold through 

the mail. We therefore wonder whether some survey participants have confused the offer of a credit card that 

has an annual fee which will be paid after the credit card is obtained with an advance fee offer where the fee 

must be paid before the credit card or loan is received. In any future research, care should be taken to make 

sure that it is possible to differentiate between these two types of fees. 
Consumer Fraud in the United States: An FTC Survey

30

of survey participants (3.35 million victims, 1.6 percent of participants).94 By 

contrast, less than 0.5 percent of the adult population appears to have experienced 

(i) being billed for information services provided either over the Internet or by 

pay-per-call telephone service that they had not agreed to purchase (800,000 

victims, 0.4 percent of the adult population), (ii) a phony offer of assistance in 

obtaining a government job (650,000 victims, 0.3 percent of the adult population), 

or (iii) purchasing a business opportunity involving false earnings claims or false 

promises of assistance (450,000 victims, 0.2 percent of the population).95

A general follow-up question at the end of the specific fraud questions did not 

produce evidence of any major frauds missed by the specific questions.96

The Number of Incidents

While Table 3-1 and Figure 3-1 report our estimates of the number of 

individuals who experienced the various types of frauds and slamming during 

the year prior to the survey, Table 3-2 and Figure 3-2 provide estimates of the 

number of incidents of each type of fraud and of slamming that occurred during 

that year and the number of incidents per one hundred adults. Because Table 3-1 

is reporting on the number of victims, a consumer who had multiple experiences 

with the same type of fraud is only counted once in Table 3-1. In Table 3-2 

94. There may be some over-reporting of the instances of credit card insurance fraud. Almost one-third 

of survey participants who said that they had purchased credit card insurance said that they first learned about 

the offer from their credit card company or credit card statement. We are not aware of credit card issuers 

selling the kind of fraudulent credit card insurance we sought to measure in this survey. We therefore wonder 

whether consumers are reporting on some other kind of offer – perhaps insurance to continue payments in the 

event that the card holder becomes unemployed or disabled. Again, future surveys should attempt to more 

clearly identify the fraudulent offers.

95. Although Table 3-1 ranks the various types of fraud from most to least frequent on the basis of 

the estimated number of victims of each type of fraud, it is important to note that some of the apparent 

differences between the number of victims of different types of fraud are not statistically significant. 

Significant differences are indicated in note b of the table. 

96. After asking about the 10 specific and the two more general forms of fraud explicitly examined 

in the survey, participants were asked if “there were any other occasions in the past year that [they] felt 

a person or company had cheated [them] out of money or property.” (Survey question 59) Again, those 

who indicated that they had such an experience were asked to describe what had happened. Of the 2,500 

survey participants, 104 answered in the affirmative when asked about other events. Of these, 88 provided 

a description of the event. In only a few cases did these descriptions provide a usable description of a 

fraudulent encounter. Of those few observations, six described problems in receiving rebates or discounts 

that they had been promised when buying a product or service. Three participants complained about 

problems with charges on a telephone bill – either being charged on the basis of a cell phone plan other 

than the one the consumer had selected or problems with the billing of long distance services. Finally, one 

person described a problem with a magazine seller who automatically renewed a subscription at the end of 

the subscription term and placed the charge on the consumer’s credit card, and another person described a 

problem with an online reservation service that failed to pay for a lodging reservation after the consumer paid 

the online service for the lodging.

Of course, we cannot rule out the possibility that other significant frauds exist but were not reported 

in answer to this question. Another survey question that preceded the specific fraud questions did reveal 

evidence of other types of fraud, including fraudulent charitable solicitations, that were not covered in the 

survey. We discuss this evidence at the end of the chapter.
Chapter 3: Which Types of Frauds Are the Most Common?

31

Figure 3-2

Specific Types of Fraud

By Number of Incidents

0.65 0.55

0.85

1.90

2.45 2.40 2.55

4.60 4.80

6.55

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

Advance Fee

Loans

Buyers' Clubs Credit Card

Insurance

Credit Repair Prizes Internet

Services

Pyramid

Schemes

Information

Services

Government

Job Offers

Business

Opportunities

In Millions

Source: Table 3-2

and Figure 3-2, 

however, consumers 

who paid someone 

to improve their 

credit record several 

different times 

during the year 

would be counted 

multiple times 

because they had 

experienced credit 

repair fraud multiple 

times.97

Projecting the 

results of the FTC 

survey to the U.S. adult population, Table 3-2 shows that an estimated 53.00 

million incidents of the frauds covered by the survey and slamming occurred 

during the preceding year.98 This amounts to 24.3 incidents per one hundred 

adults. As with the number of victims, slamming accounted for the largest 

number of incidents. This category alone accounted for one-third of all incidents 

reported – a projected 17.60 million occurrences during the year preceding the 

survey, or 8.1 incidents per one hundred U.S. adults.

97. Similarly, participants who experienced more than one type of fraud only count once in the total 

figures in Table 3-1. In Table 3-2, each incident of each type of fraud is counted separately in calculating the 

total number of incidents.

98. When survey participants were asked how many times they had a particular experience, the 

responses were coded one, two, three, four or more, or don’t know. In estimating the number of incidents, we 

have conservatively assumed that responses coded as “four or more” were in fact equal to four. Although this 

procedure may lead to a slight downward bias in the estimated number of incidents, we do not believe that 

the bias is significant. First, we expect that most of those who said “four or more” in fact had the experience 

four times. The number of participants reporting that they had an experience a particular number of times 

declines strongly as the number of events increases. In 73 percent of cases, those who were victims of a 

particular type of fraud indicated that it had only happened once in the past year. Those reporting two events 

of the same type of fraud accounted for 16 percent of cases, and those reporting three incidents accounted 

for only 4 percent. In only 6 percent of cases did participants say that they had experienced four or more 

incidents of a single type of fraud. Thus, even if the average value for those who answered “four or more” 

was five rather than four, the average number of incidents would only increase by 4 percent.

When participants indicated that they had a particular kind of experience but did not know how 

many times it had happened to them, we set the number of incidents equal to the average of the number 

of incidents for that type of fraud reported by other participants who reported having the experience and 

who indicated the number of times it happened. Similarly, as discussed in the Methodological Appendix, if 

participants said that they did not know whether they had experienced a particular type of event, we assigned 

them a probability of having had the experience equal to the percentage of affirmative responses given by 

those who knew whether they had the experience. We also assumed that the number of incidents these 

participants experienced was equal to the average number of incidents for participants who said that they 

had the experience and knew how many times it had happened, multiplied by the probability that they had 

the experience. Finally, when participants reported multiple experiences of a particular type of event, the 

probability that they suffered monetary loss on incidents other than the first one was assumed to be equal to 

the percentage of incidents in which such monetary loss was reported.
Consumer Fraud in the United States: An FTC Survey

32

Table 3-2: Estimated Number of Incidents of Fraud or of Unauthorized Changes in Long Distance 

Telephone Service, One Year Period Prior to the Surveya

Type of Problem

Number of

Incidents

(millions)b

Incidents per

Hundred Adult

Americansb

Incidents 

Per 

Victim

Total, Any Fraud Covered by the Survey or Unauthorized 

Changes in Long Distance Service

53.00

(47.35 - 58.65)

24.3

(21.7 - 26.9)

1.50

Unauthorized Changes in Long Distance Telephone 

Service (“Slamming”)

(1) 17.60

(14.65 - 20.50)

8.1

(6.7 - 9.4)

1.25

Total, Any Type of Fraud, Specific or General, Included 

in the Survey

35.45

(30.90 - 39.95)

16.3

(14.2 - 18.3)

1.45

Total, Specific Types of Fraud Included in the Survey 27.40

(23.25 - 31.50)

12.6

(10.7 - 14.5)

1.50

Paid an advance fee to obtain a loan or credit card that 

you were promised or guaranteed you would receivec

(2) 6.55

(4.55 - 8.55)

3.0

(2.1 - 3.9)

1.45

Billed for buyers’ club memberships you did not agree to 

purchase

(3) 4.80

(3.40 - 6.20)

2.2

(1.6 - 2.9)

1.15

Purchased credit card insurance (4) 4.60

(3.10 - 6.15)

2.1

(1.4 - 2.8)

1.35

Purchased a membership in a pyramid schemed (5) 2.55

(1.20 - 3.85)

1.2

(0.6 - 1.8)

1.60

Purchased credit repair (6) 2.45

(1.35 - 3.55)

1.1

(0.6 - 1.6)

1.20

Paid money or made a purchase to receive a promised 

prize and did not receive the prize or prize was not as 

promised

(7) 2.40

(1.35 - 3.45)

1.1

(0.6 - 1.6)

1.30

Billed for Internet services you did not agree to purchase (8) 1.90

(1.10 - 2.70)

0.9

(0.5 - 1.2)

1.10

Billed for information services provided either over the 

Internet or by pay-per-call that you had not agreed to 

purchase

(9) 0.85

(0.25 - 1.45)

0.4

(0.1 - 0.7)

1.10

Made a payment to someone who represented that you 

would receive a government job

(10) 0.65

(0.10 - 1.20)

0.3

((x)e - 0.6)

1.00

Purchased a business opportunity where promised 

earnings were not realized or promised assistance was 

not provided

(11) 0.55

(0.05 - 1.25)

0.3

((x) - 0.6)

1.20

Total, More General Types of Fraud Included in the Survey 8.05

(6.50 - 9.60)

3.7

(3.0 - 4.4)

1.10

Billed for a product or service you did not agree to 

purchase or billed an amount significantly more than you 

expected, products other than those identified above

(12) 4.85

(3.65 - 6.05)

2.2

(1.7 - 2.8)

1.05

Paid for a product or service but did not receive it (13) 3.20

(2.20 - 4.20)

1.5

(1.0 - 1.9)

1.10

(Notes on next page)
Chapter 3: Which Types of Frauds Are the Most Common?

33

Table 3-2 (cont.)

Notes.

a Projections are based on U.S. population of 217.76 million adults aged 18 and over as of July 1, 2003. (See U.S. 

Census Bureau, Population Division, Table ST-EST2003-01res: Annual Estimates of the Resident Population by 

Selected Age Groups of the United States and States: July 1, 2003 and April 1, 2000.) Numbers are rounded to the 

nearest 0.05 million and percentages to the nearest 0.1 percent. Totals may not equal the sum of individual figures 

due to rounding.

b The numbers in parentheses are 95 percent confidence intervals. Estimates in row (1) are significantly greater 

than those in all other rows, those in rows (2) and (12) are significantly greater than those in rows (5) - (11) and (13), 

those in rows (3) and (4) are significantly greater than those in rows (5) - (11), those in row (5) - (8) are significantly 

greater than those in rows (9) - (11), and those in row (13) are greater than those in rows (8) - (11). (All reported 

significant differences are significant at the 5 percent level or above.)

c These estimates assume that participants who said that they were required to pay an advance fee, but also said 

that they had received the promised loan, were not victims. If these participants are also considered to be victims, 

there were an estimated 9.75 million incidents of an advance fee loan or credit card scams.

d Participants who purchased membership in a pyramid scheme and who said that they had earned as much money 

as had been promised are not counted as victims. If these participants are considered to be victims, the estimated 

number of incidents rises to 3.15 million.

e (x) denotes a value of less than 0.05.
Consumer Fraud in the United States: An FTC Survey

34

Considering both the specific and the general types of frauds covered by the 

survey – but excluding slamming – an estimated total of 35.45 million incidents 

of fraud occurred during the year prior to the survey. That is, there were 16.3 

incidents per hundred adults in the United States. Considering just the ten specific 

frauds, we estimate that there were a total of 27.40 million incidents during the 

year. In general, the numbers in Table 3-2 and Figure 3-2 show that the types of 

fraud that had the most victims also had the most incidents.99 Where the rankings 

vary between Tables 3-1 and 3-2, the differences in the number of incidents of the 

relevant types of fraud are not statistically significant.100

Table 3-2 also includes the number of incidents per victim for each type of 

fraud. On average, survey participants who suffered at least one incident of fraud 

or of slamming had a total of 1.50 incidents.101 For the ten specific frauds covered 

by the survey, the average number of incidents per victim is also 1.50. For the 

ten specific frauds individually, the average number of incidents per victim ranges 

from 1.60 (for those who purchased a membership in a pyramid scheme) to 1.00 

(for those who made a payment to someone who represented that they would 

receive a government job).

Table 3-3 shows the number of different incidents encountered by those who 

were victims of fraud or of fraud and slamming.102 Whether we examine the ten 

specific frauds covered by the survey, all frauds covered by the survey, or include 

unauthorized changing of long distance telephone service in addition to fraud, we 

find that 71 percent to 74 percent of victims experienced only a single incident 

during the year before the survey was taken. Between 17 percent and 19 percent 

of victims experienced two separate incidents, and 6 to 8 percent experienced 

99. The wording of the question about the number of incidents of a particular type of fraud may have 

biased the number of reported incidents upward for the questions about being billed for an item that the 

participant had not agreed to purchase. Participants who indicate, for example, that they were billed for a 

buyers’ club membership that they did not agree to purchase were then asked “How many times has this 

happened to you in the last year?” (Survey question 21) It is possible that participants who received multiple 

bills for the same item responded to this question by indicating the number of bills they had received, while 

we would have preferred to consider this a single incident involving a single item. Although we cannot rule 

out the possibility that some participants responded this way, a comparison of the average number of times 

participants reported an incident occurring for the four types of false billing problems (Survey questions 

19 through 22) with the average number of times reported for other problems suggests that this response 

problem is not widespread. Indeed, on average, participants who reported experiencing a false billing 

problem reported that the problem happened less frequently than those who were victims of other types of 

fraud – an average value of 1.36 for false billing problems compared to 1.62 for other types.

100. The significance of differences in the number of incidents among the categories is indicated in 

footnote b of Table 3-2.

101. This number includes both multiple incidents of the same type of problem and incidents of more 

than one type of problem. As shown in the table, the average victim of slamming suffered 1.25 incidents of 

slamming, while the average victim of all frauds suffered 1.45 incidents. This result is consistent with the 

conclusion that the average victim of fraud and/or slamming suffered 1.50 incidents, because some victims of 

fraud were also victims of slamming.

102. See the Methodological Appendix for a description of how we handled instances in which there was 

uncertainty as to whether or not an event constituted a fraud.
Chapter 3: Which Types of Frauds Are the Most Common?

35

Table 3-3: Number of Incidents Experienced by Victims

Total Number of 

Incidents Specific Frauds Only All Fraud All Fraud & Slamming

1 71.2% 74.1% 72.0%

2 19.1% 16.7% 17.7%

3 8.2% 6.5% 6.5%

4 1.1% 2.3% 3.0%

5 0.5% 0.4% 0.7%

6 0.0% 0.0% 0.0%

7 0.0% 0.0% 0.2%

Note. Figures may not sum to 100 percent due to rounding.

three separate incidents. Analyzing frauds only, the highest number of incidents 

reported by an individual was five; the highest number was seven if we include 

slamming.

In general, we believe that Table 3-2 provides the most accurate estimates 

that can be derived from the survey results, because these estimates represent 

types of frauds specifically addressed in the survey. Nevertheless, it is also useful 

to consider the number of incidents classified by the product involved, as set forth 

in Table 3-4.103 In general, the products with the greatest number of incidents 

track the most frequent frauds shown in Table 3-2. In particular, the seven top 

103. To develop these numbers we had to estimate the share of the two more general types of frauds that 

involved different products. The information from which these estimates are derived came from questions 

23 and 49, which asked participants what the product was when they (a) indicated that they had received an 

unauthorized bill related to a purchase of a product other than one of those covered by the ten specific frauds 

or (b) indicated that they had paid for a product but never received it.

One reason the product-specific estimates are somewhat less reliable than the previous estimates is 

that, in a significant number of cases, we did not receive usable information about the product involved 

in the problematic transaction. For example, in the responses to survey question 23, we did not get 

product information for 11 of the 38 participants who had lost money. That is, in 11 of the 38 cases where 

participants were asked what the product was, the response is either coded as “other” or as “don’t know 

/ refused.” Similarly, in 5 of 24 cases where participants were asked about the product involved where 

participants said that they had paid for a product but not received it, the answer was either “other” or “don’t 

know / refused.” 

The fact that many of the estimates in Table 3-3 are parts of the various types of fraud that the survey 

asked about and that they may be sums of various pieces of different categories creates a problem for the 

estimation of confidence intervals. This problem occurs because the portion to be allocated to a specific 

category is a random variable based on survey responses as is the overall estimate of the number of incidents 

involved. In general, the properties of the product of two random variables are not well known. To deal with 

this problem, we used simulation to estimate confidence intervals when the estimates involved more than 

the sum of random variables. We simulated 1,000 values of the function that provided the required estimate. 

After ranking the estimates from largest to smallest, we then deleted the largest and smallest 2.5 percent of 

the simulated values. This procedure gave us our estimate of the 95 percent confidence interval.
Consumer Fraud in the United States: An FTC Survey

36

Table 3-4: Fraud Incidents by Type of Product Involveda

Product Number of Incidents (millions)b

Advance fee loans or credit cards 6.50

(4.55 - 8.55)

Buyers’ clubs 4.95

(3.60 - 6.30)

Credit card insurance 4.60

(3.10 - 6.15)

Telephone and Internet services (not including information services provided 

over the Internet or pay-per-call telephone)

3.15

(2.05 - 4.20)

Pyramid scheme 2.55

(1.20 - 3.85)

Credit repair 2.45

(1.35 - 3.55)

Prizes 2.40

(1.35 - 3.45)

Household and kitchen items 1.20

(0.40 - 2.00)

Business opportunities 0.95

(0.15 - 1.70)

Government job offers 0.65

(0.10 - 1.20)

Magazines 0.65

((x)c - 1.50)

Clothing and apparel 0.55

((x) - 1.10)

Computers: hardware and software 0.45

((x) - 1.00)

Cars and automobile accessories 0.45

((x) - 1.00)

Information services provided over the telephone 0.45

((x) - 0.95)

Health care products 0.40

((x) - 0.85)

Travel services (including vacations) 0.30

((x) - 0.65)

CDs, video tapes, or DVDs 0.25

((x) - 0.70)

Information services provided via the Internet 0.15

((x) - 0.45)

Real estate (including timeshares) 0.05

((x) - 0.20)

Notes. 

a Projections are based on U.S. population of 217.76 million adults aged 18 and over as of July 1, 2003. (See U.S. 

Census Bureau, Population Division, Table ST-EST2003-01res: Annual Estimates of the Resident Population by 

Selected Age Groups of the United States and States: July 1, 2003 and April 1, 2000.) 

 The sum of the estimates in the table are less than the total number of incidents shown in Table 3-2, because 

some incidents could not be assigned to any of the product categories.

b Numbers are rounded to the nearest 0.05 million. Numbers in parentheses are 95 percent confidence intervals.

c (x) denotes a value of less than 0.05.
Chapter 3: Which Types of Frauds Are the Most Common?

37

products in Table 3-4 are also the top frauds in Table 3-2.104 Among the top dozen 

categories in Table 3-4, however, we also find “Household and kitchen items” 

(number 8), “Magazines” (number 11), and “Clothing and apparel” (number 12), 

which do not appear in Table 3-2.105

Media Employed

The survey 

also asked how 

consumers first 

learned about the 

frauds to which 

they fell victim. 

This information, 

set forth in Table 

3-5 and Figure 

3-3, further 

contributes to our 

understanding of 

consumer fraud.106 

Print advertising – including newspaper and magazine advertising, direct 

mail solicitations, catalogs, and posters – was the most frequently cited source of 

information for offers that turned out to be fraudulent, accounting for one third of 

the fraudulent offers covered by the survey. Telemarketing was the second most 

commonly cited source, at 17 percent, and the Internet accounted for 14 percent. 

The Internet figure includes instances in which consumers learned of the offer 

through an auction site, a non-auction web site, or email. Finally, television and 

radio advertising, including television infomercials, was cited as the initial source 

of information for just over ten percent of fraudulent offers.

104. The only change in rank among these seven involves the product identified as “Telephone and 

Internet Services” in Table 3-4. The largest portion of this category is the seventh-ranked fraud category in 

Table 3-2, “Billed for Internet services you did not agree to purchase.” In some cases, however, consumers 

who indicated that they were victims of the general categories of unauthorized billing for products other 

than those specified elsewhere and paid for a product that was never received identified the product as being 

“telephone and Internet services.” Adding these experiences to the unauthorized billing for Internet services 

category makes this category number four on the product list in Table 3-4.

105. We also note that the number of incidents involving business opportunities in Table 3-4 is greater 

than the number of incidents for “Purchased a business opportunity where promised earnings were not 

realized or promised assistance was not provided” in Table 3-2. This result reflects responses to the questions 

about products that consumers had paid for but never received, in which a few survey participants indicated 

that they had paid for business opportunities but never received them. 

106. These data are based on responses for incidents of fraud and do not include unauthorized changing 

of long distance telephone service. Approximately 85 percent of survey participants who reported being 

slammed said that they first learned of the slamming when they received their telephone bill.

Figure 3-3

Media Used to Promote Frauds

Print Advertising

33.0%

Telemarketing

16.8%

Internet and Email

14.0%

Television or Radio 

Advertising

10.6%

Only Realized 

Being Charged 

When Received a 

Bill

7.3%

Other Media

18.4%

Source: Table 3-5
Consumer Fraud in the United States: An FTC Survey

38

The Cost of an Incident of Fraud

It is also useful to consider the costs to consumers from the different types 

of frauds examined here. In reporting victims’ costs, we rank monetary losses 

in ascending order and look at the costs incurred by victims in the 25th, 50th, and 

75th percentiles of those who reported losing money as a result of a particular type 

of fraud.107 We use this approach because a few participants reported very large 

losses from the fraud.108 Because we have been unable to verify these very large 

amounts,109 we believe that our approach provides a more representative picture of 

the losses victims typically incur than would the average of the reported values or 

the totals of reported losses. 

107. Participants who indicated that they experienced one of the types of problems covered by the survey 

were asked separately how much they had paid and how much they had lost in connection with the incident. 

(Survey question 64) In computing the losses, we used the smaller of the amount paid and the amount lost.

108. Seventy-five percent of the 320 survey participants who reported that they experienced one or more 

of the types of fraud investigated here and who said that they paid or lost money as a result incurred a loss 

of $630 or less. Six of the victims each reported losses of $5,000 or more; two of these six victims reported 

losses in excess of $40,000, while two more reported losses between $15,000 and $16,000. These six victims 

accounted for almost one half of the total losses for all 320 victims. Clearly, these values would substantially 

affect any average or total value.

109. We attempted to recontact nine participants who had reported that they had paid and lost very large 

amounts. Of these nine, we reached two. One was an elderly woman whose initial responses indicated that 

she had paid $16,000 for credit card insurance. When asked whether this figure was correct, she indicated 

(continued...)

Table 3-5: How Victims First Learned About the Product or Service Involved in Fraudsa

Media Number of Incidents

(millions)b Percentb

Total, All Fraud Incidents (Specific and More General) 35.45 100%

Print advertisingc 11.65

(9.05 - 14.60)

33.0%

(26.0% - 39.9%)

Telemarketing 5.95

(3.90 - 8.20)

16.8%

(11.2% - 22.3%)

Internet and Emaild 4.90

(3.10 - 6.85)

14.0%

(8.8% - 19.1%)

Television or radio advertisinge 3.70

(2.10 - 5.50)

10.6%

(6.1% - 15.2%)

Only realized being charged when received a bill 2.55

(1.25 - 4.05)

7.3%

(3.4% - 11.1%)

Other media 6.50

(4.50 - 8.75)

18.4%

(12.7% - 24.2%)

Notes. 

a Numbers are rounded to the nearest 0.05 million and percentages to the nearest 0.1 percent. Estimates for 

individual categories may not add to totals due to rounding.

b Numbers in parentheses are 95 percent confidence intervals. 

c Includes newspaper and magazine advertising, direct mail advertising including catalogs, and posters.

d Includes Internet auction sites as well as other Internet sites.

e Includes television infomercials.
Chapter 3: Which Types of Frauds Are the Most Common?

39

Among those participants who lost money as a result of one or more of the 

frauds considered here, the median victim lost $220.110 That is, fifty percent of 

those who lost money as a result of one or more of these frauds had total losses 

of $220 or less, while the other fifty percent had total losses of $220 or more.111 

The 25 percent of victims who lost the least lost a maximum $40 in total (the 

25th percentile amount), while the 25 percent of victims who lost the most lost a 

minimum of $630 in total (the 75th percentile amount).

In addition to estimating overall losses per victim, we provide estimates of 

losses per incident for several of the types of fraud we investigated.112 These 

figures, set forth in Table 3-6 and in Figure 3-4, provide estimates of the losses 

incurred each time a consumer is a victim of a particular type of fraud. 

The median (50th percentile) estimates show that the level of loss differs 

substantially depending on the type of fraud. Of the types of fraud for which we 

can provide estimates, only one involved a median payment in excess of $100 – 

credit repair fraud. The median loss for victims of this fraud was $300. Twentyfive percent of victims of this type of problem reported paying $100 or less, while 

another quarter reported paying $1,000 or more. The median payment by those 

who purchased a membership in a pyramid scheme was the second highest – $100 

– with 25 percent of the victims of this type of fraud losing $700 or more. For 

the other four specific fraud categories we examined, the median value ranged 

between $50 and $60.

109. (...continued)

that she was quite old and that she could only remember that she had purchased the insurance and that it did 

not do what she had been told it would do. She could not remember what she had paid.

The second person indicated that he had been billed four times during the previous year for a 

membership in a buyers’ club that he had not agreed to purchase and had been billed once for an Internetrelated service that he had not agreed to buy. His initial interview indicated that the last time he received an 

unauthorized bill for a membership in a buyers’ club (which was supposed to allow him to purchase books, 

records, or compact discs), he paid $2,695 for the membership. His interview also indicated that he had 

paid $2,695 for the unauthorized Internet service for which he had been billed. When we contacted this 

individual again, he indicated that he had actually only paid $39.95 for the buyers’ club membership, though 

he may initially have been billed for $2,695. When asked about the incident that involved being billed for an 

unauthorized Internet-related service, he indicated that he simply could not remember the transaction.

Thus, we could not verify any of the large loss figures. Rather, we established that there were potential 

problems with two of the figures. Another indication of potential problems with some of the high-value 

loss figures came from a comparison of the open-ended responses to survey question 11 and the responses 

to the closed-ended questions about fraud experiences. The interview report on one individual indicated 

that this person had paid $3,995 for a pyramid scheme. The person described the same event in responding 

to question 11, however, and there the amount paid was indicated to be $40 – probably indicating an actual 

payment of $39.95.

110. This is our estimate of the individual’s total loss across all of the types of fraud and reflects the fact 

that some individuals had multiple experiences with the same type of fraud. The figures in the subsequent 

discussion, and in Table 3-6, are on a per incident basis.

111. We do not include in these figures any amounts paid to a telephone company to which a consumer’s 

long distance telephone service was changed without permission. As discussed previously (see page 18, 

above), the amount paid for such service is not a measure of the injury caused by slamming. In addition, the 

survey did not ask about any costs consumers may have incurred to switch back to their preferred carrier.

112. We do not provide figures for the other types of fraud because there were too few observations – less 

than ten – to provide meaningful figures.
Consumer Fraud in the United States: An FTC Survey

40

Table 3-6: Distribution of Estimated Losses Per Incident for Different Types of Fraudsa

Type of Fraud

Percentile Number 

25th 50th 75th of Obs.

Specific Types of Fraud Included in the Surveya

Purchased credit repair $100 $300 $1,000 14

Purchased a membership in a pyramid scheme $40 $100 $700 14

Purchased credit card insurance $30 $60 $300 18

Billed for Internet services you did not agree to purchase $40 $60 $100 11

Paid an advance fee to obtain a loan or credit card that you were 

promised or guaranteed you would receive

$30 $60 $125 32

Billed for buyers’ clubs memberships that you did not agree to 

purchase

$25 $50 $100 22

More General Types of Fraud Included in the Survey

Billed for a product you did not agree to purchase or billed 

significantly more than you expected, other products

$80 $100 $300 30

Paid for a product but did not receive it $30 $40 $130 18

Notes. These estimates are based on responses about the amount paid or lost on the last time a person was a 

victim of a particular type of fraud and include only those who were classified as being a victim the last time they had 

a particular type of experience.

a Values were not computed for other types of fraud because there were fewer than 10 observations.

Figure 3-4

Median Dollars Lost 

By Specific Type of Fraud

$50 $60 $60 $60

$100

$300

$0

$50

$100

$150

$200

$250

$300

$350

Credit Repair Pyramid

Schemes

Credit Card

Insurance

Internet

Services

Advance Fee

Loans

Buyers' Clubs

Source: Table 3-6
Chapter 3: Which Types of Frauds Are the Most Common?

41

Open-Ended Descriptions of Fraudulent Experiences

The description of consumers’ fraud experiences set forth above is based 

on responses to specific questions about specific types of potentially fraudulent 

transactions. Prior to asking those specific questions, the survey also asked 

consumers about their experiences with fraud more generally. Participants were 

asked if they had ever thought they were the subject of a consumer fraud.113 In 

response, 28 percent of participants indicated that they had been a victim at some 

point in time, and just over 40 percent of those participants – 12 percent of all 

survey participants – reported that this had happened in the last year.

114

A random sample of approximately one half of those who indicated that they 

felt they had been the victim of a fraud were then asked to describe what had 

happened.115 The responses to this question are tabulated in Tables 3-7 and 3-8. 

In coding the responses, we first attempted to classify responses as describing 

a fraud, describing some kind of identity theft, or describing a bad purchase 

experience.116 For those who appeared to be describing some form of fraud, staff 

then sought to classify the type of fraud involved.117

113. Survey question 9.

114. Survey question 10. Roughly 20 percent of participants who indicated that they felt that they had 

been a victim of a consumer fraud said that the incident occurred one to two years ago and another 20 percent 

said it happened two to five years ago. An additional 15 percent said that the experience occurred more than 

five years ago. We focus on incidents within the last year for two reasons. First, consumers are more likely 

to accurately recall events that occurred in the last year. Second, these responses should match those in the 

closed-ended questions which only asked about events in the last year.

115. Survey question 11. This question was limited to half of participants because of budgetary 

considerations. 

116. Examples of responses that were coded as bad purchase decisions include “I bought a golf club and 

called around and found out they charged 30 percent more” and “I purchased a product from an infomercial, a 

forty dollar literature book. When I received it, I was absolutely speechless. It had some information, but not 

forty dollars’ worth.”

117. The responses to this question were independently coded by two Bureau of Economics’ research 

assistants. Disagreements in the coding were resolved in discussion with the primary author of this study.

Table 3-7: Responses to Open-Ended Question About The Type of Fraud Experienced

Number of Responses

Total Incident Occurred in

Last Year

Number Percent of 

Total

Number Percent of 

Total

Total Number of Responses 286 119

Described a fraud 71 24.8% 32 26.9%

Described an identity theft 26 9.1% 11 9.2%

Described a bad purchase experience 55 19.2% 19 16.0%

Response is unclear or describes none of the above 134 46.9% 57 47.9%
Consumer Fraud in the United States: An FTC Survey

42

As shown in Table 3-7, only about 25 percent of survey participants who 

described an incident described one that appeared to be actual consumer fraud. 

This was true both for experiences that occurred in the last year and for all 

experiences. Another 9 percent described incidents of some type of identity theft. 

Nineteen percent of those answering this question – 16 percent of those who said 

the incident had occurred in the last year – reported events that appeared to be 

more of a bad purchase experience than an actual fraud. Finally, in nearly one 

half of cases, the survey participant did not provide enough information to enable 

us to categorize the experience.

Table 3-8 shows the particular type of fraud described by those whose 

experience appeared to involve an incident of fraud. The table provides this 

information both for all incidents of fraud, as well as just those that occurred in 

the last year. For the latter, we have further examined the participants’ responses 

to the survey’s specific fraud questions to determine whether those participants 

also included the incident in their specific responses.118 

In more than half of the 32 cases where a participant’s response to the general 

question described an incident of fraud that happened in the last year, the incident 

involved a fraud that was not covered by the more specific questions in the survey. 

This result strongly suggests that the survey questions do not capture all types 

of consumer fraud and that care must be taken in generalizing the results of this 

survey to reflect all consumer fraud.

In seven of the 17 cases of frauds not specifically covered by the survey, 

the participant described a situation that involved fraudulent fund-raising for a 

charity. We did not include this type of fraud in the specific survey questions 

because we were concerned that most consumers would have no way of knowing 

that the charity to which they had contributed was not legitimate or that the 

money was not being used in the way they had been told. However, the large 

number of participants who described a fraudulent charitable solicitation may 

suggest that at least some consumers can identify fraudulent solicitations and that 

fraudulent charitable solicitations may be a significant problem.119

In 15 responses to the general question, the participant described a type of 

fraud covered by the specific questions included in the survey. Table 3-8 shows 

that nearly three-quarters of these participants also described these events in their 

responses to the specific questions. 

The survey asked about fraud both in an initial, more general question, and 

then in a series of specific questions. This structure allows us to learn something 

about the ability of the more general approach to capture the full extent of fraud. 

This question is of interest because some surveys have only used the more general 

118. Because the specific questions asked only about events that occurred in the last year, it is not 

possible to do a similar analysis for events that occurred more than a year ago.

119. In any future survey, it may be useful to consider asking about charity fraud.
Chapter 3: Which Types of Frauds Are the Most Common?

43

Table 3-8: Closed-End Responses of Survey Participants Who Described Frauds That Occurred 

in the Last Year in Answer to Open-Ended Question

Type of Fraud

Number of 

Open-Ended 

Responses

Matching ClosedEnd Responses

Does 

Not Fit 

Questions 

Total Asked Last 

Year Yes No

Charity frauds 9 7 – – 7a

Shop-at-home / Catalog sales 8 1 – – 1b

Unauthorized changing of telephone service 6 3 3 0 0

Magazines 6 3 1 2 0

Prizes / Sweepstakes 6 2 2 0 0

Travel / Vacations 5 2 – – 2c

Advanced fee loans or credit cards 4 1 1 0 0

Buyers’ clubs 4 3 2 0 1d

Internet auctions 3 3 1 1 1e

Pyramids / Multi-level marketing schemes / Chain letters 2 2 1 1 0

Telephone: pay-per-call services 2 0 – – –

Office supplies / Toner 1 0 – – –

Other 13 5 – – 5

Totalf 70 32 11 4 17

Notes.

a Closed-ended questions in the survey did not ask about bogus charity solicitations.

b The consumer described a situation in which a seller called and claimed that the consumer owed the seller money. 

The consumer insisted that she did not owe the money.

c One consumer’s response referred to a call about a trip to Las Vegas, to which the consumer never responded. 

The other said that someone called to say that the consumer had won a free trip for which she had purportedly 

applied. The consumer informed the caller that she had not applied for any such trip. Neither of these situations 

would have been covered by the closed-end questions.

d One consumer’s response described a situation in which the consumer had in fact purchased something that may 

have been a membership in a buyers’ club which had not delivered the promised savings. The closed-end questions 

only asked about buyers’ clubs that the consumer had been billed for but had not agreed to purchase.

e One consumer’s response dealt with a situation in which a purchase had been made, after which the consumer 

was informed that the item was already gone. Later the item arrived, though the consumer was no longer interested 

in the item. The seller told the consumer to return the item and that the seller would reimburse the consumer for 

the shipping costs. However, the shipping costs have not yet been returned. The closed-end questions dealt with 

situations in which the consumer had paid for the product but not received it or been charged substantially more than 

expected. However, they did not deal with a dispute over shipping costs.

f Numbers may not add to totals because individual observations are weighted and then rounded.
Consumer Fraud in the United States: An FTC Survey

44

approach. In addition, if the more general approach is sufficient, researchers 

considering future surveys could use it and avoid the extra cost and complexity of 

the detailed, specific questions.

To address this issue, we examined the responses to the general question 

about whether the participant had been the “subject of a consumer fraud.” We 

compared these responses to the answers to the specific fraud questions. We 

found that only one-third of victims, as measured by the specific fraud questions, 

also reported that they had been a victim in response to the more general 

questions.120 That is, two-thirds of those who met our definition of fraud from the 

specific questions did not indicate that they were victims when the question was 

posed more generally. This strongly suggests that the general approach should 

not be used in attempting to measure the overall level of fraud experienced by 

consumers.121 It appears necessary to probe specifically about the particular 

events that the researcher considers to be fraud to accurately draw out this 

information in a survey context.

120. More precisely, only one-third of victims both answered “yes” to question 9, which asked whether 

there ever was a time when the participant felt that he or she was the subject of a consumer fraud,” and 

“during the last year” to question 10, which asked about the last time the participant felt that he or she was a 

subject of a fraud. Another 27 percent said that they had been a victim of consumer fraud but not in the last 

year, while almost 40 percent said that they had never been the subject of a consumer fraud in answering the 

general question. 

121. The general approach is even less successful, in fact, in capturing the desired information than 

the one-third figure suggests. Those who answered the general question in the affirmative often described 

something other than fraud when asked to describe the event that led them to conclude that they had been 

the subject of a fraud. We found that only about 40 percent of these responses described experiences that we 

considered to be frauds. Combining these two pieces of information, we find that only a small fraction – 13 

percent (40 percent of one-third) – of fraud victims indicated that they were victims of fraud in response to 

the more general question.
Methodological Appendix to Chapter 3

45

Methodological Appendix to Chapter 3

To estimate the number of victims and the number of incidents of the various 

frauds covered by the survey, we needed to determine whether a participant in the 

survey experienced a particular type of fraud and, if so, how many times in the 

last year. Given that we only considered an event to be a fraud if the victim lost 

money, we also needed to know whether money was lost.

Accordingly, the survey specifically asked participants whether they had 

experienced various events that could have been frauds and also asked for some 

information about the amount of money that had been paid and the amount lost. 

For example, question 13 sought to elicit information about the extent of credit 

repair fraud.122 This question asked participants whether “[i]n the past year, [they 

had] paid money to anyone who promised or guaranteed to remove negative, 

but true, information from [their] credit record, but failed to get the information 

removed.” Participants who answered this question in the affirmative were then 

asked how many times they had this experience in the past year. 

Individuals who answered question 13 in the affirmative also were asked for 

additional details about their experience, including how much money they had 

paid and how much money they had lost.123 Participants who indicated that they 

had the relevant experience more than once in the last year, however, were only 

asked the follow-up questions about the most recent incident. Thus, assuming 

that the participant provided answers to all of the questions, we have information 

on the amount of money that was lost the last time, but not for prior occurrences.

Based on their survey responses, it is easy to determine whether some 

participants were victims of fraud. For example, those who reported that they 

did not have the relevant experience – such as those who had not paid anyone for 

credit repair services – were obviously not victims. Similarly, participants who 

said that they had paid to have their records repaired but then either indicated that 

they had paid nothing or that they had not lost anything also were not considered 

victims for purposes of this study.124 (For purposes of this appendix, we will say 

that these participants experienced an incident, but not a money-losing incident. 

In the context of the overall report, these participants are not victims of fraud.) 

On the other hand, each participant who said that he or she had the experience 

once and lost money – i.e., the person had a money-losing incident – was 

considered a victim.

122. Credit repair includes both promises to repair an existing credit record, which is covered by question 

13, and the sale of information about how to create a new credit record, which is covered by question 14.

123. Survey question 64.

124. In determining the amount of money lost, we used the smaller of the amount that was said to be paid 

and the amount that was lost. However, if one or the other of these figures was missing, we used the figure 

that was provided.
Consumer Fraud in the United States: An FTC Survey

46

Making this determination is more difficult for participants who indicated 

that they had been involved with multiple incidents, because we only collected 

information about monetary loss for the most recent incident. Those who lost 

money as a result of the last incident were clearly victims during the year, but 

we do not know how many money-losing incidents they experienced because we 

did not ask whether they lost money in the previous incidents. Moreover, where 

participants did not lose money in the last incident, not only can we not determine 

how many money-losing incidents were experienced, we cannot even tell for 

certain whether the participant was ever a victim.

Although the limitations of the data collected in the survey do not permit us 

to determine whether an individual is a victim and/or how many incidents he or 

she experienced in these situations, we can make certain assumptions about the 

probability that such a person is a victim and the expected number of moneylosing incidents. Using these assumptions, we can then estimate the total number 

of consumers who were victims and the total number of money-losing incidents 

that occurred during the year.

In developing the estimates, we assume that the likelihood that a consumer 

lost money in a particular incident for which we lack data is equal to the 

percentage of money-losing incidents for which we do have data. That is, if we 

have data showing that consumers lost money in 8 of 20 incidents, we assume that 

there is a 40 percent probability that money was lost in each incident for which 

we do not have data.

Using this information, we can then determine the likelihood that a 

participant was a victim and the estimated number of money-losing incidents 

experienced based on the number of incidents reported by other survey 

participants. For example, a participant who indicated that she experienced 

multiple incidents and that she lost money as a result of the last incident was 

obviously a victim. Furthermore, her most recent experience was an incident 

of fraud because she lost money. There is also some likelihood that previous 

incidents were incidents of fraud. Given that money was lost in 40 percent of 

incidents for which we have information, we assume that there is a 40 percent 

likelihood that each of this participant’s prior incidents also involved lost money. 

Thus, if this participant reported a total of two encounters, we assign an expected 

value of 1.4 money-losing incidents to her.125 If she reported three or more 

encounters, the estimated number of total money-losing incidents is set equal to 

one for the most recent incident, which we know involved the loss of money, plus 

0.4 times the number of incidents in excess of one.

Next, consider a participant who had multiple incidents but did not lose 

money as a result of the most recent incident. We know that this participant 

was not a victim the last time, but we do not know whether he was a victim the 

125. By assigning the average value in each case where we do not know whether money was lost, we 

undoubtedly understate the variance in our estimates of the number of victims.
Methodological Appendix to Chapter 3

47

previous times. Assuming again that money is lost 40 percent of the time, there 

is a 40 percent probability that he was a victim in each earlier incident. Thus, if 

he had a total of two encounters, there is a 40 percent likelihood that he was a 

victim in the first incident and therefore a 40 percent chance that he was a victim 

overall. Furthermore, the expected number of money-losing incidents involving 

this participant is 0.4. If he had a total of three encounters and did not lose money 

on the last one, the probability that he was a victim rises to 64 percent, and the 

expected number of money-losing incidents rises to 0.8.126

Additional complications arise because survey participants sometimes did 

not know the answer to a question or refused to answer. As with the problem 

discussed above, we deal with these problems by assuming that missing values are 

equal to the mean of the values for those who gave information. Thus, for those 

who said that they did not know whether they had experienced a particular type 

of fraud or who refused to answer the question, we assume that the likelihood that 

they were victims equaled the percent of victims among those who had answered 

the question. We also estimate the number of money-losing incidents for such 

participants as being equal to the probability of being a victim times the average 

number of money-losing incidents among those who reported that incident. 

Similarly, when participants indicated that they had the experience in question 

but did not know how many times, we assumed that the number of incidents was 

equal to the average number of incidents reported by those who answered the 

question.127

Finally, where participants indicated that they had experienced at least one 

incident of a particular type of problem, but did not answer the question about 

the amount of money that was involved, we do not know whether the participants 

were victims as a result of the last incident. We treat such participants the same 

way we treat participants whom we know were not victims in the last incident. 

However, in this situation, we are uncertain about the results of each incident the 

participant experienced. Thus, again assuming that money was lost in 40 percent 

of incidents, we assume that there is a 40 percent probability of being a victim 

for those participants who experienced one incident, but did not indicate whether 

money was lost. For participants who had two incidents and did not indicate 

whether money was lost the most recent time, the probability of being a victim is 

64 percent.

Given the assumptions listed above, we determined the likelihood that 

each participant in our survey was a victim of each of the types of fraud we 

126. In general, the likelihood that a person is a victim in at least one of n incidents about which we do 

not know whether money was lost is (1 - (1-P)n) where P is the probability that money is lost in any single 

incident. If we know that no money was lost in the most recent incident, n is equal to the total number of 

incidents encountered by the consumer minus one.

127. The fact that we simply assume that each missing value is equal to the mean of the reported values 

rather than using a value drawn from a random distribution with the mean and variance of the relevant 

distribution will lead us to understate the variance in the number of victims and the number of incidents.
Consumer Fraud in the United States: An FTC Survey

48

considered. We also estimated the number of money-losing incidents involving 

that individual. Computing the mean and variance of these values across the 

individuals in the survey gives us estimates of the percent of participants who 

were victims of each type of fraud and of the number of incidents per hundred 

participants. We also have estimates of the variance in these two figures, so we 

can calculate the confidence intervals reported in Tables 3-1 and 3-2.

Given the approach discussed above, our estimates of the number of incidents 

experienced by an individual are not limited to integer values. In Table 3-3, we 

have rounded fractional values to the nearest integer value.
Chapter 4: Who is a Victim of Fraud?

49

Chapter 4: Who is a Victim of Fraud?

This chapter examines the characteristics of survey participants who were 

victims of fraud or who experienced an unauthorized change in their long distance 

telephone service.

Characteristics Analyzed

The survey included questions about the racial and ethnic background of 

participants. We use this information to examine whether members of particular 

minority groups face different risks of being a victim than non-Hispanic whites.128 

The survey asked about standard demographic variables, including age, education, 

gender, and marital status, and we include those variables in our analysis.

We also asked about participants’ financial situation. In addition to the 

commonly-used measure of current income, we asked about two novel measures 

of consumers’ financial well being. First, we asked survey participants how 

they expected their income to change in the next three years.129 We included this 

question to determine whether consumers who expected their incomes to fall face 

a greater risk of becoming victims of fraud, or whether they may be less willing to 

take financial risks and thus are less likely to become victims.

Second, we asked participants about the amount of debt they had. As with 

future income, this measure is based on the consumer’s perception. Participants 

were asked how comfortable they were with their current level of debt – did they 

have more debt than they could handle or could they handle more debt?130 Here, 

128. Information on the racial and ethnic backgrounds of survey participants was gathered from 

two different questions. First, question 84 asked whether the person was of “Hispanic or Latino origin.” 

Question 85 then asked participants to select one or more racial categories that best indicated their race. We 

pooled the responses to these two questions. Those who indicated that they were of Hispanic or Latino origin 

were considered to be Hispanic, while those who did not indicate that they were Hispanic were assigned to 

racial categories on the basis of their responses to question 85. 

In collecting information on the races of survey participants, we used the five minimum categories 

recommended by the Office of Management and Budget. (See, “Provisional Guidance on the Implementation 

of the 1997 Standards for Federal Data on Race and Ethnicity,” December 15, 2000.) Given the size of our 

survey and our focus on the national population, these basic racial and ethnic categories are sufficiently large 

to allow statistical analysis if there are sizable differences between the groups.

We note that question 85 permitted participants to indicate that they belonged to more than one racial 

group. A small percentage of participants indicated that they belonged to multiple racial groups, and we have 

included them in the “Other race” category.

129. Survey question 80 asked “Thinking ahead to three years from now, how do you think your income 

will compare to your income today? Do you think it will be (a) Much lower, (b) Slightly lower, (c) About the 

same, (d) Slightly higher, or (e) Much higher?”

130. The question asked was “And thinking for a moment about your personal debt on which you 

currently make interest payments. I am talking about your debts you partially pay-off each month for things 

like mortgages, credit cards, personal loans or car loans. Would you say the amount of debt you currently 

have is (a) More than you can handle financially, (b) About as much as you can handle financially, or (c) You 

could handle more debt than you currently have?” (Survey question 81)
Consumer Fraud in the United States: An FTC Survey

50

Table 4-1: Distribution of Values for Explanatory Variablesa

Observations By Characteristic

Number Percentb

Race and Ethnicity 

Hispanics 158 6.3%

African Americans 162 6.5%

American Indians or Alaska Natives 28 1.1%

Non-Hispanic Whites 1,777 71.1%

Other 95 3.8%

Not known 300 11.2%

Gender

Female 1,303 52.1%

Male 1,197 47.9%

Not known 0 0.0%

Marital Status

Single 1,147 45.9%

Married 1,353 54.1%

Not known 0 0.0%

Age

18 - 24 190 7.6%

25 - 34 390 15.6%

35 - 44 411 16.4%

45 - 54 494 19.8%

55 - 64 367 14.7%

65 and over 505 20.2%

Not known 143 5.7%

Education

Did not complete high school 200 8.0%

Graduated from high school 813 32.5%

Attended some college or post-secondary technical or vocational school 637 25.5%

Graduated from college or more 744 29.8%

Not known 106 4.2%

Current Income

Less than $20,000 359 14.4%

$20,000 - $40,000 586 23.4%

$40,000 - $60,000 359 14.4%

$60,000 - $80,000 292 11.7%

$80,000 - $100,000 211 8.4%

Over $100,000 189 7.6%

Not known 504 20.2%

(Table continued on next page)
Chapter 4: Who is a Victim of Fraud?

51

Table 4-1 (cont.)

Observations By Characteristic

Number Percentb

Expected Future Income

Will be much lower 99 4.0%

Will be slightly lower 172 6.9%

Will be about the same 759 30.4%

Will be slightly higher 870 34.8%

Will be much higher 334 13.4%

Not known 266 10.6%

Current Debt

More debt than can comfortably handle 181 7.2%

About as much debt as can comfortably handle 923 36.9%

Could handle more debt than currently have 778 31.1%

Do not have any personal debt 349 14.0%

Not known 268 10.8%

Total Sample Size 2,500 100.0%

Notes. 

a The numbers and percentages in this table are based on unweighted responses. Numbers reported elsewhere 

are weighted, unless otherwise noted. 

b Percentages may not add to 100 percent due to rounding.
Consumer Fraud in the United States: An FTC Survey

52

we sought to determine whether consumers who feel pressured by their current 

debt level are willing to take greater risks in an attempt to eliminate the debt or 

behave more cautiously to avoid increasing their debt further.

Table 4-1 shows the distribution of survey participants by each of these 

characteristics.131

Methodology

Using the survey responses, we examine whether the characteristics described 

above affect the likelihood that consumers have experienced one or more of the 

types of fraud studied and/or slamming. In this analysis, we principally examine 

two aggregate measures of victimization. First, we examine whether a participant 

was a victim of one or more of these problems – i.e., experienced at least one type 

of fraud and/or experienced the unauthorized switching of his or her long distance 

service.132 Second, we then consider only whether a participant experienced one 

or more of the frauds – that is, we exclude participants who were victims only of 

slamming. Then, we briefly examine separately several of the specific frauds and 

slamming.133

In conducting our analysis, we have used two different statistical 

methodologies.134 The first approach was to focus on each of a number of 

characteristics – age, gender, income level, education, race and ethnicity – and to 

scrutinize simple cross-tabulations that show the percentage of participants within 

each group (e.g., aged 18 to 24, or with an income between $40,000 and $60,000, 

or college-educated) who were victims of a particular type of fraud or slamming. 

This formulation provides information about whether the problem being examined 

occurred more often in certain groups.

131. Unlike most of the numbers provided in this report, the numbers in Table 4-1 are not weighted. 

For each characteristic, the table also shows the number of participants who did not provide answers to the 

relevant questions and whom we therefore cannot categorize.

132. In this analysis, participants are considered to be a victim of a particular type of fraud if they 

indicated that they had a particular experience at least once and had lost money as a result the last time they 

had the experience. Participants who did not have the experience or who had the experience only once and 

did not lose any money as a result (or said that they received a refund) are not considered to be victims. As 

discussed previously, those who indicated that they had a particular experience more than once in the last 

year were only asked about the amount of money they lost the last time they had the particular experience. 

Therefore, it was not possible to determine whether participants who indicated that they had an experience 

multiple times, but who said that they had not lost money the last time it occurred, were victims or not. These 

participants were therefore excluded from the relevant analysis, as were those who indicated that they did not 

know whether they had a particular experience.

133. As discussed in footnote below, we also did some preliminary analysis of the number of incidents 

experienced by those who were victims.

For some types of frauds, there were so few victims among the survey participants that reasonable 

statistical inferences could not be drawn from the data. We did not attempt to estimate relationships when we 

had complete data for fewer than ten victims of the particular type of fraud.

134. In examining the determinants of the various specific types of fraud, we only use the probit analysis 

discussed below.
Chapter 4: Who is a Victim of Fraud?

53

This approach has at least one limitation, however. Consider, for example, 

participants in different age groups. The simple cross-tabulation methodology 

does not tell us whether any differences in the prevalence of a particular problem 

in fact flow from the precise characteristic under review – here, one’s age group 

– or whether such differences arise from other attributes that may differ between 

one age group and another. For example, those in the 18-to-24 group – the 

youngest age group in our survey – tend to have lower incomes and less education 

than those in older groups (at least in part because they are still in school or 

are just beginning their careers).135 Thus, if we found that those in the 18-to24 group were, say, more likely to be victims, we would not know whether this 

phenomenon arose merely from the fact that these victims are young, or whether 

perhaps it resulted from this group’s lower income or education level.

To help determine which factors are ultimately responsible for the 

results we find, we also used a second approach – a probit regression analysis 

that simultaneously measures the differences associated with each of the 

characteristics.136 This technique allowed us to ascertain, for example, whether 

135. Only about 7 percent of survey participants in the 18 to 24 group have a college degree, whereas 17 

to 19 percent of those between 25 and 54 have a college degree. Almost one quarter of the 18 to 24 year olds 

have an income of less than $20,000. In contrast, only 12 percent of those between 45 and 54 years of age 

had incomes of this level.

136. We use a probit analysis because, for each individual included in the regression, the dependent 

variable has one of two values, indicating that the person has been a victim within the last year or the person 

has not been a victim. In such situations, technical considerations mandate that a technique like probit 

be used. (For a detailed treatment of probit analysis, see John H. Aldrich and Forrest D. Nelson, Linear 

Probability, Logit, and Probit Models, Sage University Paper Series on Quantitative Applications in the 

Social Sciences, No. 07-045, Sage Publications, 1984, or William H. Greene, Econometric Analysis 3rd

edition, Prentice Hall, Inc., 1997.)

As is common in using regression analysis to analyze survey results, problems arise because not 

every participant answers every question asked. We have used two common approaches to deal with 

this problem. First, we use Complete Case Analysis, where we only include in the analysis observations 

for those who provided answers to all of the questions used in the analysis. If missing values occur at 

random, complete case analysis will provide unbiased, though inefficient, estimates of the parameters of 

interest. If there is a correlation between missing values on one variable and the value of other variables, 

however, the resulting estimates may be biased. The second approach we use is known as Conditional Mean 

Imputation. This approach uses the relationships among the various variables in a model to estimate the 

most-likely value for those instances where the value of a variable is missing. This approach improves the 

efficiency of our estimates and reduces the likelihood of biased estimates. However, the estimated variances 

on the coefficients may be biased downward with the result that the measures of statistical significance 

are overstated. (See Roderick J.A. Little and Donald B. Rubin, “The Analysis of Social Science Data 

With Missing Values,” in Modern Methods of Data Analysis, John Fox and J. Scott Long, editors, Sage 

Publications, 1990, pp. 374-409. See also Roderick J.A. Little and Donald B. Rubin, Statistical Analysis With 

Missing Data, Second Edition, Wiley-Interscience, 2002. For a recent application of this approach, see Philip 

DeCicca, Donald Kenkel and Alan Mathios, “Putting Out the Fires: Will Higher Taxes Reduce the Onset of 

Youth Smoking?,” Journal of Political Economy, 110 (February 2002), pp. 144-169.)

In implementing the conditional-mean-imputation procedures with our categorical variables, when 

it was possible to convert a categorical variable to a continuous variable, we did so prior to performing the 

imputation. After the imputation, we then recreated the categorical variable by assigning an observation 

to the category implied by the imputed value. When this was not possible, we created separate dummy 

variables for each of the values of the categorical variables and generated imputed values for each of the 

dummy variables. We then use these values, which can be considered estimates of the likelihood that the 

individual fell within each category, in the final regression.
Consumer Fraud in the United States: An FTC Survey

54

younger consumers are more likely to be victims than older consumers with 

comparable levels of income, education, etc. In other words, we can determine 

more precisely the likely cause(s) of any differences in victimization.

Depending on the question posed, one or the other of these approaches 

– simple cross-tabulation or probit regression analysis – may be the more 

appropriate way to measure the association between two variables. For example, 

if we want to evaluate whether to undertake an educational campaign in Spanish 

aimed at teaching consumers how to avoid being victims of fraud, it may be 

more important just to know that Hispanics are at greater risk of becoming 

victims – and less important to determine whether the elevated risk stems from 

different levels of education or income. Similarly, the simple cross-tabulation 

results may be more useful in deciding whether to run an educational campaign 

in a publication directed at senior citizens. On the other hand, to gain a more 

comprehensive understanding of differences among victims, we would use the 

more complex probit regression methodology – which controls for the effects 

of other factors – to determine which factor has the greatest association with the 

likelihood of becoming a victim.

Analysis of Aggregate Measures of Risk

Tables 4-2 and 4-3 present the results of our analysis of the likelihood of 

being a victim of fraud or slamming and of fraud alone. In addition, Figures 

4-1 through 4-4 highlight some of the more interesting results. Table 4-2 and 

the figures set forth the results of the simple cross-tab analysis, showing the 

relationships between the percentage of participants who were victims and the 

single characteristic being analyzed. Table 4-3 provides the results of our probit 

analysis.137

137. Table 4-4 provides the results of probit analyses for individual types of frauds and for the 

unauthorized changing of long distance service. The numbers in both Tables 4-3 and 4-4 are the estimated 

marginal effects for each group. For example, in the first column of figures in Panel A of Table 4-3, the 

coefficient for “African Americans” is 0.0738. This indicates that the results from the conditional-meanimputation estimation show that African Americans are 7.38 percentage points more likely to be victims 

of a fraud or slamming than non-Hispanic whites. (The coefficients in the table are reported as decimals, 

not percentages.) The marginal effect of each variable is calculated by computing the estimated likelihood 

of being a victim for each survey participant, assuming that the participant has the baseline value of the 

characteristic examined and further assuming the participant’s actual characteristics for the other variables in 

the equation. Averaging these estimated probabilities across all individuals gives us the average likelihood of 

being a victim in the base case. We then estimate the likelihood that a participant would be a victim if he or 

she has the characteristic for which the marginal effect is being calculated and his or her actual characteristics 

for the other variables in the equation. Again, averaging across all individuals gives us the estimated average 

likelihood under this scenario. The difference between these two averages is then the estimated marginal 

effect.
Chapter 4: Who is a Victim of Fraud?

55

Figure 4-1 

Likelihood of Being a Victim

By Race and Ethnicity

Fraud and Unauthorized Changes in Long Distance Service

12.5% 11.7%

38.0%

24.1%

26.7%

0%

10%

20%

30%

40%

Hispanics African

Americans

American Indians

/ Alaska Natives

Non-Hispanic

Whites

Others

Fraud Only

6.4% 7.3%

33.8%

17.1%

14.3%

0%

10%

20%

30%

40%

Hispanics African

Americans

American Indians

/ Alaska Natives

Non-Hispanic

Whites

Others

Source: Table 4-2

Race and Ethnicity

Members of 

several minority 

groups are 

significantly more 

likely to be victims 

than are nonHispanic whites. 

Whether we look 

at the likelihood of 

being a victim of 

fraud or slamming, 

or the likelihood 

of being a victim 

of fraud alone, 

the differences 

across racial and 

ethnic groups are 

jointly significant 

at the 1 percent 

level. We found 

that consumers in 

certain minority 

groups are more 

likely to be victims 

both in the simple 

cross-tab analysis 

and in the more 

sophisticated probit 

analysis, and in both 

the analysis of fraud 

or slamming and 

fraud alone. The 

cross-tab results for race and ethnicity are presented in Figure 4-1 and in Panel A 

of Table 4-2. 
Consumer Fraud in the United States: An FTC Survey

56

Table 4-2: Percent of Survey Participants Who Are Victims, By Single Characteristica

A. By Race and Ethnicity

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Hispanics 26.7% 14.3%

African Americans 24.1% 17.1%

American Indians or Alaska Natives 38.0% 33.8%

Non-Hispanic Whites 12.5% 6.4%

Others 11.7% 7.3%

Number of Observations 1864 1852

B. By Current Income

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Less than $20,000 17.5% 8.7%

$20,000 to $40,000 18.2% 12.5%

$40,000 to $60,000 14.3% 6.7%

$60,000 to $80,000 16.1% 10.8%

$80,000 to $100,000 11.3% 5.2%

Over $100,000 15.3% 6.8%

Number of Observations 1698 1684

C. By Expected Income Three Years in the Future

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Will be much lower 21.3% 11.0%

Will be slightly lower 12.7% 7.2%

Will be about the same 11.4% 5.0%

Will be slightly higher 15.3% 9.6%

Will be much higher 23.5% 14.2%

Number of Observations 1889 1873

D. By Comfort with Current Level of Debt

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

More debt than can comfortably handle 27.3% 19.2%

About as much debt as can comfortably handle 15.4% 9.1%

Could handle more debt than currently have 15.1% 8.1%

Do not have any personal debt 8.6% 2.7%

Number of Observations 1882 1869

(Table continued on next page)
Chapter 4: Who is a Victim of Fraud?

57

Table 4-2 (cont.)

 E. By Age

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

18 - 24 11.4% 8.3%

25 - 34 18.4% 11.1%

35 - 44 18.2% 11.1%

45 - 54 17.4% 8.7%

55 - 64 10.7% 6.1%

65 and over 10.9% 4.7%

Number of Observations 1979 1967

F. By Marital Status

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Single 13.6% 8.1%

Married 16.0% 8.5%

Number of Observations 2101 2089

G. Gender

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Male 14.8% 8.3%

Female 14.9% 8.4%

Number of Observations 2101 2089

H. By Education

Fraud and Unauthorized 

Changes in Long 

Distance Service

Fraud Only

Did not complete high school 14.6% 7.5%

Graduated from high school 14.4% 7.7%

Attended some college or post-secondary technical or 

vocational school

17.1% 11.1%

Graduated from college or more 13.7% 7.0%

Number of Observations 2014 2003

Note. 

a Based on all observations where it is clear whether the person was a victim or not and where we know the specific 

characteristic for that individual.
Consumer Fraud in the United States: An FTC Survey

58

American Indians or Alaska Natives138

Among survey participants, American Indians or Alaska Natives had the 

greatest likelihood of reporting that they had been a victim. As shown in the top 

part of Figure 4-1, 38.0 percent of American Indians or Alaska Natives indicated 

that they had been victims of fraud or slamming within the last year.

139 Compared 

to the 12.5 percent of non-Hispanic whites who were victims, American Indians 

or Alaska Natives were 25.5 percentage points more likely to be victims. This 

difference is statistically significant at the 1 percent level.140 Considering only 

consumers who were victims of one or more of the frauds examined in the survey 

(Fraud Only), we again find that the American Indian or Alaska Native group has 

the greatest likelihood of being a victim. Almost 34 percent of this group were 

victims in the last year – a figure that is more than 27 percentage points above that 

for non-Hispanic whites. (These values are shown in the bottom part of Figure 4-

1.) Again, the difference is significant at the 1 percent level. In sum, these simple 

results suggest that American Indians or Alaska Natives are more than three times 

as likely as non-Hispanic whites to be victims of fraud or slamming and more 

than five times as likely to be victims of fraud alone.

The probit analysis presented in Table 4-3 paints a very similar picture. The 

conditional-mean-imputation results in Panel A show that American Indians or 

Alaska Natives were 28 percentage points more likely than non-Hispanic whites 

to have been a victim of fraud or slamming, and the results in Panel B show that 

they were 31 percentage points more likely to have been a victim of fraud alone. 

These differences are both significant at the 1 percent level.141 The complete case 

analyses show essentially the same: after controlling for other variables, we find 

that American Indians or Alaska Natives are more than three times as likely to 

have been a victim of fraud or slamming as a non-Hispanic white and more than 

five times as likely to have been a victim of fraud alone.142

138. Among the categories OMB suggests using to collect racial data is “American Indians or Alaska 

Natives.” Because we used this category collecting the data, we use this term consistently throughout this 

report.

139. As in the previous chapter, results here are based on a weighted analysis.

140. Some caution may be advised in interpreting this result. Although the result is statistically 

significant, the survey included only 28 American Indians or Alaska Natives.

141. The level of significance for coefficients in the various regressions are reported in the tables that 

contain the regression results.

142. This conclusion is true in both the complete case and the conditional-mean-imputation equations. In 

calculating the ratio of the likelihood of being a victim, we use the average likelihoods for the two groups as 

described in footnote above.
Chapter 4: Who is a Victim of Fraud?

59

Table 4-3: Likelihood of Being a Victim, Probit Estimation, Marginal Effects, Aggregate Measures

A. All Frauds and Unauthorized Changes in Telephone Service

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites) 

Hispanics 0.1302 *** 0.1432 ***

African Americans 0.0738 ** 0.0748 **

American Indians or Alaska Natives 0.2797 *** 0.3137 ***

Other -0.0109 -0.0038

 Joint Significance *** ***

Gender (Relative to Male)

Female 0.0041 0.0002

Marital Status (Relative to Married)

Single -0.0438 ** -0.0486 **

Age (Relative to 35 - 44)

18 - 24 -0.0781 ** -0.0836 **

25 - 34 -0.0189 -0.0111

45 - 54 0.0006 0.0314

55 - 64 -0.0504 * -0.0481

65 and over -0.0184 -0.0088

 Joint Significance * **

Education (Relative to High School Graduate)

Did not complete high school 0.0030 -0.0108

Attended some college or post-secondary technical or 

vocational school 0.0199 0.0039

Graduated from college or more 0.0084 -0.0072

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0586 ** 0.0720 **

$20,000 - $40,000 0.0480 ** 0.0581 **

$60,000 - $80,000 0.0168 0.0167

$80,000 - $100,000 -0.0327 -0.0291

Over $100,000 0.0184 0.0283

 Joint Significance * ns

Expected Future Income (Relative to Future Income Unchanged)

Will be much lower 0.1070 *** 0.1121 **

Will be slightly lower 0.0332 0.0532

Will be slightly higher 0.0346 * 0.0356

Will be much higher 0.1196 *** 0.1213 ***

 Joint Significance *** ***

Current Debt (Relative to Having Too Much Debt)

About as much debt as can comfortably handle -0.0740 ** -0.0751 **

Could handle more debt than currently have -0.0601 * -0.0654 * 

Do not have any personal debt -0.1290 *** -0.1114 ***

 Joint Significance *** * 

Number of Observations 2101 1509

Percent Positive Values 14.86% 16.76%

Chi-square for Overall Significance 102.94 *** 80.76 ***

(Table continued on next page)
Consumer Fraud in the United States: An FTC Survey

60

Table 4-3 (cont.)

B. All Frauds

 

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics 0.0581 ** 0.0617 **

African Americans 0.0605 *** 0.0662 **

American Indians or Alaska Natives 0.3125 *** 0.3518 ***

Other 0.0031 0.0050

 Joint Significance *** ***

Gender (Relative to Male)

Female 0.0037 -0.0021

Marital Status (Relative to Married)

Single -0.0194 -0.0211

Age (Relative to 35 - 44)

18 - 24 -0.0371 -0.0401

25 - 34 -0.0194 -0.0134

45 - 54 -0.0225 -0.0042

55 - 64 -0.0338 -0.0340

65 and over -0.0228 -0.0145

 Joint Significance ns ns

Education (Relative to High School Graduate)

Did not complete high school 0.0104 -0.0007

Attended some college or post-secondary technical or 

vocational school 0.0287 * 0.0177

Graduated from college or more 0.0104 0.0041

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0286 0.0389

$20,000 - $40,000 0.0514 *** 0.0638 ***

$60,000 - $80,000 0.0291 0.0353

$80,000 - $100,000 -0.0215 -0.0192

Over $100,000 0.0086 0.0145

 Joint Significance ** **

Expected Future Income (Relative to Future Income Unchanged)

Will be much lower 0.0544 * 0.0761 **

Will be slightly lower 0.0391 0.0596 **

Will be slightly higher 0.0396 *** 0.0416 **

Will be much higher 0.0832 *** 0.0959 ***

 Joint Significance *** ***

Current Debt (Relative to Having Too Much Debt)

About as much debt as can comfortably handle -0.0526 ** -0.0547 * 

Could handle more debt than currently have -0.0583 ** -0.0656 **

Do not have any personal debt -0.1143 *** -0.1120 ***

 Joint Significance *** ***

Number of Observations 2089 1492

Percent Positive Values 8.33% 9.67%

Chi-square for Overall Significance 110.49 *** 83.92 ***

Notes.

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test
Chapter 4: Who is a Victim of Fraud?

61

Hispanics

Hispanics have the second highest likelihood of being a victim of fraud or 

slamming. The results of the cross-tab analysis, set forth in both Figure 4-1 and 

Table 4-2, show that 26.7 percent of Hispanic survey participants were victims. 

The rate of victimization among Hispanics is more than 14 percentage points 

greater than the percentage of non-Hispanic whites and is somewhat greater 

than the figure for African Americans. Considering victims of fraud alone, the 

percentage of Hispanics who were victims is still almost 8 percentage points 

higher than for non-Hispanic whites. Thus, whether we examine fraud alone or 

include slamming, Hispanics are more than twice as likely to be victims as nonHispanic whites, and the differences are statistically significant at the 1 percent 

level.143

The probit regression results in Table 4-3 again paint a very similar picture: 

We estimate that Hispanics have a 13 or 14 percentage point greater likelihood of 

being a victim of fraud or slamming than non-Hispanic whites, and a 6 percentage 

point greater risk of being a victim of fraud alone. These differences are both 

statistically significant.144 After controlling for all other factors, Hispanics are 

twice as likely to be victims of fraud or slamming as non-Hispanic whites. For 

fraud alone, the risk for Hispanics is about 1.8 or 1.9 times that for non-Hispanic 

whites.

African Americans

As with Hispanics and American Indians or Alaska Natives, African 

Americans have a greater likelihood of being a victim than do non-Hispanic 

whites. The cross-tab results indicate that African Americans are almost 12 

percentage points more likely to be victims of fraud or slamming, and more 

than 10 percentage points more likely to be victims of fraud alone. For both 

measures, the risk faced by African Americans is significantly greater than that 

faced by non-Hispanic whites at the 1 percent level of statistical significance. 

The regression results in Table 4-3 also show that African Americans are more 

likely to be victims than non-Hispanic whites, and the differences are statistically 

significant.145

143. The differences between Hispanics and African Americans are not statistically significant.

144. When looking at the combination of victims of fraud and/or slamming, the differences are 

significant at the 1 percent level. Looking only at victims of fraud, the differences are significant at the 5 

percent level.

145. Comparing the data for Hispanics and African Americans, the cross-tab results in Table 4-1 show 

that Hispanics are 2.6 percentage points more likely to be victims if we look at fraud and slamming together. 

When we look at fraud alone, Hispanics are 2.8 percentage points less likely to be victims. Neither of these 

differences is statistically significant. After controlling for other factors, the regression results in Table 4-2 

show that Hispanics are 6 to 7 percentage points more likely to be a victim of fraud or slamming, and less 

than one-half of one percentage point less likely to be a victim of fraud alone. Again, these differences are 

not statistically significant.
Consumer Fraud in the United States: An FTC Survey

62

Thus, in the simple cross-tab analysis, African Americans are almost twice 

as likely to be victims of fraud or slamming and more than 2.5 times as likely to 

be victims of fraud alone as compared to non-Hispanic whites. In the regression 

analysis, they are just over 1.5 times as likely to be victims of fraud or slamming 

and 1.85 to 1.90 times as likely to be victims of fraud alone.

Asians, Native Hawaiians or Other Pacific Islanders, and Multi-Racial

A small number of participants identified themselves as Asians, Native 

Hawaiians or Other Pacific Islanders, American Indians or Alaska Natives, or 

as belonging to more than one racial group. Only the group of participants who 

identified themselves as American Indian or Alaska Native were statistically 

different from the base group in cross-tabulation tests to examine whether these 

small groups had a statistically significant higher or lower incidence of fraud 

or slamming compared to non-Hispanic whites. For this reason, the remaining 

smaller racial groups were combined into a category titled “Other” for the analysis 

contained in this report. This combination is consistent with standard statistical 

practice. Of participants included in the “Other” category, 39 percent identified 

themselves as Asian, 11 percent identified themselves as Native Hawaiian or 

Other Pacific Islander, and 50 percent identified themselves as belonging to two or 

more racial categories.

We find that the small number of participants who are included in this 

“Other” group are no more or less likely to be a victim than are non-Hispanic 

whites. Whether we consider fraud alone or include slamming in addition to 

fraud, the victimization rate for this group is within 1.1 percentage points of the 

rate for non-Hispanic whites. None of the differences are statistically significant. 

This is the case in both the cross-tab analysis and in the regressions.

Current Income

The simple cross-tab analysis suggests that current income has little 

effect on a consumer’s risk of being a victim. Panel B of Table 4-2 presents 

the differences in the percentage of participants who were victims of fraud or 

slamming, categorized according to their current income. These differences are 

not statistically significant, either individually or jointly. Considering victims 

of fraud alone, the overall relationship between income and the percentage of 

victims is significant at the 5 percent level. However, there is no clear pattern 

to the relationship. Those with incomes between $20,000 and $40,000 have the 

highest likelihood of victimization – 12.5 percent – while those with incomes 

between $60,000 and $80,000 face the second highest likelihood – 10.8 percent. 

Consumers in the intervening group – with incomes between $40,000 and $60,000 

– have the second lowest rate of victimization – 6.7 percent.146

146. The only statistically significant difference is between the $20,000 to $40,000 income group and the 

$40,000 to $60,000 group. That difference is significant at the 5 percent level.
Chapter 4: Who is a Victim of Fraud?

63

The results of the probit analysis in Table 4-3 suggest that, after controlling 

for factors other than income, consumers with lower incomes – incomes of 

$40,000 or below – may be somewhat more likely to be a victim of fraud or 

slamming than consumers with incomes in the $40,000 to $60,000 range. In 

those regressions, the coefficients for incomes of less than $20,000 and those for 

incomes between $20,000 and $40,000 are both significantly greater than zero 

and suggest that consumers in these income groups have a 5 to 7 percentage point 

increased risk of being a victim.147 The regression results suggest that consumers 

with incomes under $20,000 are about 50 percent more likely to be a victim 

of fraud or slamming than those with incomes between $40,000 and $60,000. 

Consumers with incomes in the range of $20,000 to $40,000 have an increased 

risk of about 40 percent.

The probit analysis of the likelihood of being a victim of fraud alone yields 

the same result as the cross-tabs: Consumers with incomes in the $20,000 to 

$40,000 range are more likely to be victims of fraud than those with incomes of 

$40,000 to $60,000. However, the difference in risk between those with incomes 

under $20,000 and those with incomes of $40,000 to $60,000 is not statistically 

significant.

Future Income

Consumers’ expectations about future changes in their incomes have a 

statistically significant effect on the likelihood that they will become a victim. 

The pattern is consistent whether we look at victims of fraud or slamming or at 

victims of fraud alone, and for both the cross-tab and the probit results.148

As shown in Figure 4-2 and in Panel C of Table 4-2, the simple cross-tab 

analysis finds that the rate of victimization is lowest for consumers who expect 

their incomes to remain steady over the next three years. Consumers who expect 

their incomes to be either slightly higher or slightly lower have a somewhat 

greater risk of being victims.149 Finally, consumers who expect large changes in 

their incomes – either large increases or large decreases – have the highest risk 

147. The coefficients for incomes under $20,000 and for those between $20,000 and $40,000 are both 

significant at the 5 percent level in the regressions analyzing the likelihood of being a victim of fraud or 

slamming.

148. The effect of expected changes in future income is jointly significant at the 1 percent level in all of 

the cross-tab and regression results.

149. The difference between those who expect their incomes to be slightly higher in the next three years 

and those who expect their incomes to remain stable is significant at the 5 percent level when we examine 

both fraud and slamming. When we examine fraud alone, the difference is significant at the 1 percent level. 

The differences between those who expect their incomes to be slightly lower and those who expect them to 

be the same are not statistically significant.
Consumer Fraud in the United States: An FTC Survey

64

of being victims.150 

The probit results 

in Table 4-3 present 

the same picture.151 

Regardless of 

whether we look 

simply at the 

relationship between 

the likelihood of 

being a victim and 

expected future 

income changes 

or use regression 

analysis to control 

for other factors, we 

find that consumers 

who anticipate 

large changes in 

their incomes are, 

roughly, at least 

twice as likely be a 

victim as consumers 

who anticipate 

stable incomes.152

150. The difference 

between those who 

expect large declines in 

their incomes and those 

who expect no change is 

significant at the 5 percent 

level for both fraud and slamming combined and fraud alone. The difference between those who expect a 

large increase in income and those who expect no change is significant at the 1 percent level in both cases.

151. In the probit analysis, the differences in risk for those who expect a slight decline in their future 

income and those who expect their incomes to remain about the same are significant only in the complete 

case analysis of being a fraud victim alone. The differences for those who expect a slight increase in income 

are significant when we look only at victims of fraud alone. When we look at fraud and slamming, the 

coefficient is only significant at the 10 percent level in the conditional-mean-imputation results and, as noted 

previously, this methodology may overstate significance. Those who expect to have much lower future 

incomes face an increased risk that is significant at the 5 percent level whether we are looking at victims 

of fraud or slamming or victims of fraud alone in three of the four reported regressions, while those who 

expect to see much higher incomes face an increased risk that is significant at the 1 percent level in all four 

regressions.

152. Looking at both fraud and slamming, the simple analysis suggests that those who expect large 

declines in their incomes face an 85 percent higher risk than those who expect their incomes to be stable. In 

the complete case regression analysis, this group has a 90 percent increase in risk.

Figure 4-2 

Likelihood of Being a Victim

By Expected Change in Future Income

Fraud and Unauthorized Changes in Long Distance Service

23.5%

15.3%

11.4% 12.7%

21.3%

0%

10%

20%

30%

40%

Much Lower Slightly Lower About the Same Sightly Higher Much Higher

Fraud Only

14.2%

9.6%

5.0%

7.2%

11.0%

0%

10%

20%

30%

40%

Much Lower Slightly Lower About the Same Sightly Higher Much Higher

Source: Table 4-2
Chapter 4: Who is a Victim of Fraud?

65

The reasons for this pattern of results are not clear. The fact that consumers 

who expect their incomes to decline significantly are more likely to be victims 

is consistent with the hypothesis that these consumers are willing to take greater 

risks to avoid the decline.153 This hypothesis does not explain why those who 

anticipate large future increases in income are at greater risk, however. One 

possible explanation for this result is that many consumers who say they expect 

their incomes to rise significantly in the future may be overly optimistic about 

their futures. They may also be overly optimistic about their ability to distinguish 

between fraudulent and honest offers from which they can profit.154

The Burden of Debt

How consumers feel about their ability to handle their existing debt is also 

significantly related to the likelihood that they will be victims. Specifically, those 

who feel that they have more debt than they can handle are the most likely to be 

victims. The data presented in Panel D of Table 4-2 and in Figure 4-3 suggest 

that consumers who feel that they have too much debt are more than three times 

as likely to be victims of fraud or slamming compared to consumers who have 

no debt – 27.3 percent of survey participants with too much debt were victims 

versus 8.6 percent of those with no debt. The effect is even greater for fraud 

alone, where those who felt they had too much debt were more than 7 times as 

likely to have been victims.155 Consumers who stated that their level of debt was 

about right or that they could handle additional debt were less likely to be victims 

than those whose debt level was too high, but were more likely than those with 

no debt.156 Overall, consumers’ perception of the burden of their debt bears a 

significant relationship to the likelihood of being victims.157

153. This effect should be present in particular when we look at frauds such as business opportunities, 

in which purchasers believe that the offering will allow them to earn money or make profits in the future. 

However, we do not have sufficient data regarding these types of frauds from which to estimate statistical 

relationships for them alone.

154. If we had found an increased risk for those who expect large increases in their incomes only in 

the simple cross-tab results and not in the regression results, we might conclude that the greater risk applies 

primarily to young consumers who are just starting out. However, the fact that the increased risk also appears 

in the regression results – where we controlled for age and education – suggests that this hypothesis is not the 

explanation.

Interestingly, in Table 4-4, which provides the results of probit analysis for specific types of frauds, we 

find that consumers who anticipate much higher levels of income in the future are significantly more likely to 

be victims of credit record fraud and of advance fee loan scams.

155. In both cases, the differences between those with too much debt and those with no debt are 

statistically significant at the 1 percent level.

156. Comparing the likelihood of being a victim for those with about as much debt as they can handle 

and those who say they can handle additional debt to the risk faced by those who said they had no debt, we 

find that the differences are significant at the 1 percent level.

157. We also examined whether consumers who had more debt than they could handle were more likely 

to be victims of specific types of fraud. As shown in Table 4-4, we found that these consumers were more 

likely to have purchased credit card insurance than consumers who were more comfortable with their debt. 

This type of fraud was the only one for which these consumers faced a significantly higher risk.
Consumer Fraud in the United States: An FTC Survey

66

Figure 4-3 

Likelihood of Being a Victim

By Comfort with Current Level of Debt

Fraud and Unauthorized Changes in Long Distance Service

8.6%

15.4% 15.1%

27.3%

0%

10%

20%

30%

40%

More Debt Than Can

Comfortably Handle

About As Much Debt

As Can Comfortably

Handle

Could Handle More

Debt Than Currently

Have

Do Not Have Any

Personal Debt

Fraud Only

2.7%

8.1% 9.1%

19.2%

0%

10%

20%

30%

40%

More Debt Than Can

Comfortably Handle

About As Much Debt

As Can Comfortably

Handle

Could Handle More

Debt Than Currently

Have

Do Not Have Any

Personal Debt

Source: Table 4-2

Although the 

probit analysis 

presented in 

Table 4-3 paints 

a similar picture, 

the differences in 

risk among the 

various levels of 

perceived debt are 

somewhat smaller 

once we control 

for other factors.158 

The cross-tab 

results suggest that 

consumers with too 

much debt are more 

than three times 

as likely to have 

been a victim of 

fraud or slamming. 

However, the ratio 

falls to 1.9 after we 

control for other 

factors. Looking 

at fraud alone, the 

regression results 

show that those who 

feel overburdened 

by their debt are 2.7 

times as likely to 

have been a victim, 

compared to 7 times 

as likely in the 

simpler analysis.

These results are also consistent with the hypothesis that consumers who are 

worried about their financial futures are more likely to take risks. For example, 

consumers who struggle to meet their current debt obligations may be more 

likely to fall for schemes that promise to provide a way out of their present 

158. Whether considering victims of fraud or slamming or victims of fraud alone, and whether 

considering the simple cross-tabs or the probit results, the overall effect of the consumer’s perceived ability 

to service existing debt is jointly significant at the 1 percent level, with one exception. (In the complete case 

regression analysis of all frauds and slamming, the level of debt variables are jointly significant at only the 10 

percent level.) Analyzing individual effects in the cross-tab results, the proportion of victims is significantly 

lower, at the 1 percent level, for consumers who say that the level of their debt is about right, that they could 

handle more debt, or that they have no debt, as compared to those who say that they have more debt than they 

can handle. 
Chapter 4: Who is a Victim of Fraud?

67

situation.159 The 

results may also 

reflect a general 

difference among 

consumers with 

respect to their 

willingness to take 

risks. Consumers 

who are more 

willing to take 

risks may be more 

likely to have 

uncomfortably high 

levels of debt and 

may also be more 

likely to be victims 

of fraudulent offers. 

At the other end 

of the spectrum, 

consumers who 

report having 

no existing debt 

may be more 

conservative in most 

financial matters, 

which in turn may 

explain why they 

are less likely to be 

victims.160

Figure 4-4 

Likelihood of Being a Victim

By Age

Fraud and Unauthorized Changes in Long Distance Service

10.7% 10.9%

18.2% 17.4% 18.4%

11.4%

0%

10%

20%

30%

40%

18 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 and over

Fraud Only

4.7% 6.1%

8.7%

11.1% 11.1%

8.3%

0%

10%

20%

30%

40%

18 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 and over

Source: Table 4-2

159. As noted earlier, we were not able to estimate the risk of victimization for most specific frauds, 

including business opportunity fraud. The purchase of credit card insurance is the only specific type of fraud 

for which we found that consumers with too much debt faced a significantly increased risk of victimization. 

(See Table 4-4.) 

160. We also estimated a version of the probit equations that included variables that would allow an 

interactive effect between having too much debt and the consumer’s expectations of changes in future 

income. This version of the equation, which was run only for fraud alone and using only the complete case 

analysis, suggests that consumers who believe that they currently have more debt than they can comfortably 

handle and who expect their incomes to be much lower three years from now are at a significantly greater 

risk of being victims than either those who have too much debt but expect their incomes to remain stable or 

those who expect their incomes to fall but do not currently have more debt than they can comfortably handle. 

Indeed, for consumers who do not have too much debt, expecting a future decrease in income does not seem 

to lead to an increased risk. For those who expect their incomes to rise significantly in the next three years, 

there is an increased risk of being a victim. However, this effect appears to be independent of whether the 

consumer has too much debt. There is no additional effect of both anticipating a large positive change in 

income and having too much debt.
Consumer Fraud in the United States: An FTC Survey

68

Age

Not controlling for other factors, we find that older consumers – those 

aged 55 or over – are less likely to be victims than younger consumers. These 

data are reported in Figure 4-4 and in Panel E of Table 4-2. Although 17 to 19 

percent of survey participants between 25 and 54 years old were victims of fraud 

or slamming, the proportion falls to just under 11 percent for those who are 55 

or older.161 Similarly, we find that 11 percent of participants in the 25 to 44 age 

group were victims of fraud alone, compared with only 5 or 6 percent of those 

in the 55 and over age group.162 The data also suggest that consumers in the 

youngest age group – 18 to 24 years of age – are somewhat less likely to have 

been a victim than those in the 25 to 54 age group. This effect is only significant 

when looking at both fraud and slamming, and then is only significant at the 10 

percent level.

After we control for other factors, age does not have as much of an effect 

on the likelihood of being a victim of fraud or slamming. Although age was 

significant at the 1 percent level in the simple analysis, the overall relationship is 

significant only at the 5 or 10 percent level in the regression results reported in 

Table 4-3. Of particular interest, we find that the significantly lower likelihood for 

consumers aged 55 and older that we found in the simple analysis falls away once 

we control for other factors. Although the regression results suggest that the risk 

to older consumers is slightly lower than for those aged 35 to 44, the differences 

are generally not statistically significant.163 The only significant age relationship 

in the regression results is that the youngest consumers – those between 18 and 24 

– are less likely to be a victim of fraud or slamming.164

For fraud alone, age was even less important once we control for other 

factors. None of the age coefficients reported in Panel B of Table 4-2 are 

statistically significant and overall the age variables are not significant.

Perhaps the most noteworthy finding here is that consumers aged 65 or over 

do not appear to be at greater risk of being a victim than those who are somewhat 

younger. Indeed, the cross-tab results suggest that seniors face the lowest risk 

of being a victim. In the probit results in Table 4-3, however, we find that 

161. The difference in the fraction of consumers who were victims is significant at the 1 percent level if 

we compare the rates for those aged 55 to 64 or those aged 65 and above to the rate for those aged 35 to 44.

162. The differences for those aged 55 to 64 and those aged 65 and over compared to those between 35 

and 44 are significant at least at the 5 percent level.

163. The only significant coefficient is for those between 55 and 64 in the conditional-mean-imputation 

equation. However, we cannot be confident that this result is not an artifact of the estimation technique 

we used because the statistical significance of coefficients tends to be overstated when conditional mean 

imputation is used.

164. The results in Table 4-4 also show that the younger consumers are less likely to be victims of 

slamming alone. 
Chapter 4: Who is a Victim of Fraud?

69

seniors have about the same risk as younger consumers once we control for other 

factors.165

Marital Status

There is some suggestive evidence that consumers who are married may be 

at somewhat greater risk of being victims than those who are single. Panel F 

of Table 4-2 shows that, without controlling for other effects, the proportion of 

survey participants who are married and who were victims of fraud or slamming 

is more than 2 percentage points higher than for those who are single. The 

proportion who were victims of fraud alone is less than 1 percentage point greater. 

Neither of these differences is statistically significant. 

When we control for other factors in the probit analyses, as shown in Table 

4-3, we find slightly stronger results – married consumers face a 4 to 5 percentage 

point greater risk of being a victim of fraud or slamming and about a 2 percentage 

point increase in the risk of being a victim of fraud alone. Only the difference in 

the risk of fraud or slamming combined is statistically significant.

It is not clear why consumers who are married should be at greater risk. One 

possibility is that survey participants who are married reported both their own 

experiences and those of their spouse. If that is the case, it could reflect either a 

weakness in the survey design or the fact that both spouses suffer financial loss 

when either one is a victim of the type of problems investigated here.166

Other Characteristics

In addition to the characteristics discussed above, we also examined the 

relationship between gender and education level and the likelihood of being a 

victim of fraud and/or slamming.167 We present the results of the simple crosstab analysis on these two variables in Panels G and H of Table 4-2. Gender had 

no significant effect on the likelihood of being a victim regardless of whether 

165. The finding that seniors are not more likely to be victims is consistent with the findings of the earlier 

studies. See, Richard M. Titus, Fred Heinzelmann, and John M. Boyle, “Victimization of Persons by Fraud,” 

Crime & Delinquency, 41 (January 1995), p. 60, and American Association of Retired Persons, The Behavior 

of Older Consumers: An AARP Study, 1994, pp. 3, 9.

166. In the analysis of specific types of problems in Table 4-4, we find only one specific problem for 

which we can identify a statistically significant increased risk for married consumers – slamming. By 

contrast, those who are married are significantly less likely to be victims of credit repair or credit card 

insurance frauds. In each of these cases, however, the effects are only significant at the 10 percent level in 

one of the regressions and are insignificant in the other one. Thus, these results should be taken as quite 

tentative.

167. In addition, we conducted some preliminary analysis of whether the number of incidents 

experienced by victims varied based on the victims’ particular characteristics. Because the number of 

observations in this analysis is limited – between 144 and 159 depending on the particular variable when 

we include only victims of fraud and between 271 and 296 when we include victims of slamming – we only 

examined the effect of each characteristic individually. Even then, there were no statistically significant 

relationships between demographic characteristics and the average number of incidents experienced, with one 

exception. 

(continued...)
Consumer Fraud in the United States: An FTC Survey

70

we looked at fraud and slamming or just fraud alone or whether we controlled 

for other factors using the more complex probit analysis. With two very minor 

exceptions, education also had no effect on any of the measures.168

The Likelihood of Being a Victim of Specific Frauds

In Table 4-4, we report the results of probit analyses of the likelihood of 

being a victim of four individual types of frauds, as well as the likelihood of 

being a victim of an unauthorized change in long distance telephone service.169 

We also conducted statistical tests to determine whether the effect of the various 

consumer characteristics included in the analysis differs depending on the 

type of fraud or slamming examined. Some earlier studies have found that 

consumers at the greatest risk of becoming a victim of one type of fraud have 

different characteristics than consumers who are most likely to fall for a different 

type of fraud. In particular, in its most recent study on consumer fraud, AARP 

reported that consumers who are most likely to fall for a foreign lottery fraud 

have different characteristics than those most likely to fall for an investment 

fraud.170 Our survey includes different frauds than those investigated by AARP. 

In addition, the AARP study was limited to persons aged 45 or older, while our 

167. (...continued)

Although our analysis is therefore only suggestive of differences that may exist, some apparent 

differences are worth mentioning. For example, we find that American Indian or Alaska Native victims, on 

average, appear to experience more incidents per victim than non-Hispanic white victims. The difference is 

statistically significant at the 5 percent level when we look at both fraud and slamming – an average of 2.15 

incidents per victim for American Indians or Alaska Natives and 1.45 for non-Hispanic whites. Considering 

frauds alone, American Indian or Alaska Natives victims average 1.95 incidents while non-Hispanic whites 

average 1.50 incidents. This difference is not statistically significant. Care must be taken in interpreting 

both of these results, however, because the number of American Indian or Alaska Native victims in the 

sample is small. The data also suggest that Hispanic victims of fraud alone experienced somewhat fewer 

incidents per victim than non-Hispanic white victims – 1.25 incidents per victim on average for Hispanics 

and 1.45 incidents per victim for non-Hispanic whites. Again, however, the difference here is not statistically 

significant.

The extent to which the average number of incidents per victim varies with current income is also 

interesting, though the differences are not statistically significant. Consumers with incomes under $20,000 

appear to have more incidents per victim than those with incomes in excess of $40,000. Victims of frauds 

alone with incomes under $20,000 averaged 1.75 incidents, while victims with incomes over $40,000 

averaged 1.40 incidents. 

Finally, victims between 25 and 34 averaged 1.65 incidents per fraud victim – the highest average for 

any age group. In comparison, fraud victims aged 45 to 54 averaged 1.40 incidents per victim and those aged 

65 or over averaged 1.50 incidents per victim. None of these differences is statistically significant.

168. In the cross-tab analysis results for fraud alone in Panel H of Table 4-2, consumers who had taken 

some college courses or had attended technical school after high school had a higher risk of being a victim 

than those who had recently graduated from high school. This difference was significant at the 10 percent 

level, and the overall relationship between education level and likelihood of being a victim was significant 

at the 10 percent level. We find a similar weak relationship in the regression analysis of fraud only in the 

conditional-mean-imputation results.

169. As discussed in footnote above, we chose to conduct the probit analysis of these frauds because we 

felt that we had data for enough victims to permit meaningful statistical analysis.

170. AARP (2003).
Chapter 4: Who is a Victim of Fraud?

71

survey included consumers as young as 18. We therefore sought to determine 

whether our survey yielded similar findings. 

In investigating this issue, we conducted two sets of tests. First, we 

compared the characteristics of victims of slamming to those of victims of fraud 

alone. Second, we examined whether there were significant differences in victim 

characteristics among four specific types of frauds.

Slamming vs. Frauds

We found significant differences in the characteristics of victims of slamming 

compared to victims of one or more of the frauds considered in the study.

171 In 

particular, we found that the racial and ethnic characteristics and consumers’ 

expectations about future changes in their incomes had differing relationships 

to the likelihood of being a victim of slamming and the risk of being a victim of 

fraud.172

We can understand some of the differences here by comparing the coefficients 

in the first column of Table 4-4 – which show the relationships between the 

various characteristics and the likelihood of being a victim of slamming – to those 

in Panel B of Table 4-3. We note that although African Americans and American 

Indian or Alaska Natives have a significantly higher risk of being victims of 

frauds than non-Hispanic whites, the same is not true for their risk of being 

slammed. The only group that shows a significantly higher risk of being slammed 

is Hispanics.

In addition, Panel B of Table 4-3 shows that expected future changes in 

income affect the likelihood of being a victim of fraud. By contrast, Table 4-

4 shows no significant relationship between expected future income changes 

and the likelihood of being a victim of slamming. These results are not 

necessarily surprising. If expected future income changes affect the likelihood 

of victimization because they reflect differences in the willingness to take risks, 

we should find this relationship only in the likelihood of being a victim of fraud. 

With slamming, the consumer’s long distance service is changed without the 

consumer’s approval or even knowledge – and it is therefore unrelated to the 

consumer’s willingness to take risks. As such, the likelihood of being slammed 

is unlikely to be related to consumers’ view of their future financial situation. In 

addition, we see a similar pattern in the relationship between consumers’ comfort 

with their current debt and the likelihood of being a victim of fraud, but not 

the likelihood of being slammed, although the differences are not statistically 

significant.

The simple cross-tab analysis shows similar results, as presented in Figure 

4-5.

171. We only conducted these tests using the observations for which we had complete data.

172. In the aggregate test, we found a difference that is significant at the 5 percent level. The differences 

in the effect of the race and ethnicity variables are significant at the 10 percent level, as are the differences in 

the effect of expected future income changes and current income levels.
Consumer Fraud in the United States: An FTC Survey

72

Table 4-4: Likelihood of Being a Victim, Probit Estimation, Marginal Effects, Individual Problemsa

Problem

Unauthorized 

Changes in 

Telephone 

Service

(1)

Credit Repair 

Fraud

(2)

Credit Card 

Insurance Fraud

(3)

Advance Fee 

Loan Fraud

(4)

Buyers’ Club 

Fraud

(5)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics 0.0991 *** 0.0228 *** 0.0197 -/** 0.0112 0.0122African Americans 0.0303 -0.0003 0.0028 0.0170 0.0163 * American Indians or Alaska Natives 0.0090 0.1223 *** (n)b 0.1661 *** 0.0438 **/*Other -0.0194 0.0051 (n) (n) 0.0022

Joint Significance *** *** ns/* *** */ns

Gender (Relative to Male)

Female 0.0000 0.0013 -0.0092 */** -0.0119 -0.0037

Marital Status (Relative to Married)

Single -0.0159 -/* 0.0029 -/* 0.0094 */- 0.0035 -0.0072

Age (Relative to 35 - 44)

18 - 24 -0.0404 */** -0.0019 -0.0048 (n) -0.004725 - 34 0.0012 0.0021 (n) 0.0042 -0.012645 - 54 0.0080 0.0044 -0.0024 -0.0211 ** -0.0170 **55 - 64 -0.0275 */- 0.0037 0.0059 -0.0260 * -0.0198 **65 and over -0.0008 0.0003 0.0096 (n) -0.0215 **

Joint Significance */** ns ns **/* * 

Education (Relative to High School Graduate)

Did not complete high school -0.0101 0.0001 -0.0052 -0.0177 -0.0047Attended some college or post-secondary technical or vocational school -0.0113 0.0037 -0.0014 0.0088 0.0012Graduated from college or more -0.0016 0.0003 0.0039 -0.0154 -/* -0.0009

Joint Significance ns ns ns ns/* ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0191 0.0018 -0.0012 0.0224 0.0094$20,000 - $40,000 -0.0009 0.0053 0.0057 0.0210 */- 0.0147 **$60,000 - $80,000 -0.0064 -0.0027 0.0211 **/- 0.0041 -0.0011$80,000 - $100,000 0.0012 (n) (n) (n) 0.0176 **Over $100,000 0.0069 0.0013 0.0055 (n) 0.0111

Joint Significance ns ns ns ns **/*
Chapter 4: Who is a Victim of Fraud?

73

Expected Future Income (Relative to Future Income Unchanged)

Will be much lower 0.0408 (n) (n) 0.0259 0.0134Will be slightly lower -0.0198 0.0055 -/** -0.0002 (n) 0.0076Will be slightly higher -0.0083 0.0028 -/** 0.0031 0.0147 -0.0008Will be much higher 0.0144 0.0173 *** -0.0008 0.0411 ***/** -0.0027

Joint Significance ns *** ns **/* ns

Current Debt (Relative to Having Too Much Debt)

About as much debt as can comfortably handle -0.0118 -0.0067 -0.0027 0.0013 0.0032Could handle more debt than currently have -0.0036 -0.0025 -0.0156 0.0086 -0.0043Do not have any personal debt -0.0190 -0.0073 -0.0187 */- -0.0044 (n)

Joint Significance ns ns ** ns ns

Number of Observations 2469 2150 1726 1288 2102Percent Positive Values 6.46% 7.54% 1.15% 2.62% 1.16%Chi-square for Overall Significance 45.79 ***/** 174.35 *** 144.85 *** 70.48 *** 123.52 ***

Notes.a Marginal effects are based on conditional-mean-imputation regressions. Where significance levels differ between conditional-mean-imputation and completecase regressions, the significance levels are indicated as a/b where “a” is the significance level of the conditional-mean-imputation regression and “b” is the significance of the complete-case regression. Reported coefficients as well as number of observations are reported only for the conditional-mean-imputation regressions. A “-“ in either “a” or “b” denotes that the coefficient was not significant in that regression.*** significant at 1 percent level ** significant at 5 percent level * significant at 10 percent level ns not significantly different from zero in joint testb (n) denotes that no victims who had this characteristic were victims of this type of fraud.
Consumer Fraud in the United States: An FTC Survey

74

Different Types of 

Frauds

Our second 

set of tests 

compared the effect 

of the various 

characteristics 

across four specific 

types of fraud 

included in the 

survey: (i) credit 

repair fraud, 

(ii) credit card 

insurance fraud, 

(iii) advance fee 

loan fraud, and 

(iv) unauthorized 

billing for a buyers’ 

club membership. 

These tests 

show significant 

differences, in total, 

in the effect of 

various individual 

characteristics 

on the likelihood 

of being a victim 

of one of these 

frauds.173

We find that 

the relationship 

with age differs 

significantly depending on the type of fraud involved.174 We can obtain some 

understanding of these differences by examining the coefficients for the probit 

regressions for individual types of fraud, which are reported in Table 4-4. For 

example, the likelihood of becoming a victim of credit card insurance fraud or 

credit card repair fraud does not vary across age groups. However, consumers in 

the 25 to 34 and 35 to 44 age groups are significantly more likely to be victims of 

advance fee loan fraud than those between 45 and 54. In addition, those aged 35 

173. Testing for whether there are differences in any of the coefficients included in the model, we find 

that we can reject the hypothesis that there are no differences at the 1 percent level.

174. The differences in the coefficients on the age variables across the four individual types of fraud are 

jointly significant at the 1 percent level. 

Figure 4-5 

Likelihood of Being a Victim

Fraud Compared to Slamming

By Race and Ethnicity

6.4% 7.3%

33.8%

17.1%

14.3%

3.9% 5.6%

7.4% 8.9%

14.4%

0%

10%

20%

30%

40%

Hispanics African

Americans

American Indians

/ Alaska Natives

Non-Hispanic

Whites

Others

Fraud Only Slamming

By Expected Change in Future Income

14.2%

9.6%

5.0%

7.2%

11.0%

8.4%

6.0% 6.6%

4.4%

9.4%

0%

10%

20%

30%

40%

Much Lower Slightly Lower About the Same Slightly Higher Much Higher

Fraud Only Slamming
Chapter 4: Who is a Victim of Fraud?

75

to 44 are significantly more likely to have been a victim of unauthorized billing 

for a buyers’ club membership than are older consumers.

Race and ethnicity also have differing relationships with the likelihood of 

being victim of various types of fraud, though the differences are only jointly 

significant at the 10 percent level. The results reported in Table 4-4 show that 

Hispanics have a significantly higher likelihood of being a victim of credit 

repair fraud and credit card insurance fraud than non-Hispanic whites. African 

Americans have a significantly greater likelihood of becoming a victim of 

unauthorized billing for a buyers’ club membership, while American Indians or 

Alaska Natives are more likely to experience credit repair fraud, advance fee loan 

fraud, or unauthorized billing for a buyers’ club membership.

The Role of Language

One group that may be particularly vulnerable to fraudulent offers is 

consumers who have limited English-language proficiency. This may include 

people who have only been in this country for a short amount of time. The survey 

did not elicit information about whether participants were recent immigrants or 

had limited proficiency in English. Therefore, we cannot say anything definitive 

about this possibility.175 The survey did, however, ask about languages other 

than English that were spoken in the participant’s home. Using this information 

we may be able to obtain some preliminary insight into the role of English 

proficiency in the risk of becoming a victim of fraud. 

Using the responses to the question about languages spoken, as well as the 

responses to the racial and ethnic questions, we identified those participants who 

said that they were of Hispanic or Latino origin and who also said that Spanish 

and English were the only languages spoken at home.176 This group may include 

a relatively high percentage of recent immigrants or consumers with limited 

English proficiency. We would, of course, expect that any finding of vulnerability 

to fraud is generally applicable to all immigrant populations with limited English 

proficiency. However, Spanish speaking Hispanics were the only group for which 

we had enough observations to conduct a meaningful test.

175. Another factor that limits our ability to address this issue is that the survey was only conducted in 

English. As a result, consumers who have serious problems communicating in English are unlikely to have 

participated. Some consumers with limited proficiency may have participated in the survey anyway, while 

others may reasonably have declined to do so.

176. Survey question 78 asked participants “Other than English, what other languages, if any, are spoken 

in your home?” In responding to this question, participants could identify multiple languages that were 

spoken in their homes. When participants indicated that, in addition to English, they spoke Spanish and one 

or more other languages at home, we excluded them from the variable for Hispanics who spoke Spanish at 

home, which we were using as a proxy for limited English language proficiency. It seemed less likely that 

consumers living in households where multiple languages other than English are spoken would be the recent 

immigrants who have difficulty with the English language.
Consumer Fraud in the United States: An FTC Survey

76

In an attempt to measure the effect of language, we experimented with a 

variant of the victim equations reported in Table 4-3 that included a variable 

denoting those Hispanics who said that Spanish was spoken at home.177 The 

results of this estimation suggest that Hispanics who speak Spanish at home are 

more likely to have been victims of fraud or slamming than Hispanics who do 

not speak Spanish at home – specifically, either 4.6 or 5.6 percentage points more 

likely, depending on whether we look at the complete-case or conditional-meanimputation results. For fraud alone, we find virtually no difference between 

Hispanics who speak Spanish at home and those who do not – either 0.3 or 0.1 

percentage points depending on which regression we examine. Finally, for 

slamming alone, we find that Hispanics who speak Spanish at home are between 

4.5 and 5.0 percentage points more likely to have been victims.

None of the differences are statistically significant. In part this may be a 

result of the small number of Hispanic survey participants who did not speak 

Spanish at home or who spoke other languages in addition to Spanish: 110 (of 

157) Hispanic participants indicated that Spanish was the only language other 

than English spoken in their homes. Furthermore, as noted above, our measure 

of whether a consumer is likely to have limited English proficiency is not very 

precise. Because the differences are not significant, our findings can only be 

taken as suggestive that a difference may exist.

The fact that we find tentative evidence suggesting that those who speak 

Spanish at home are more likely to be victims of the unauthorized switching of 

long distance telephone service is perhaps important, because telephone service 

is almost exclusively marketed by telemarketing. If limited English proficiency 

causes some consumers to be at greater risk for fraud or slamming, we would 

expect that this would be particularly true in telemarketing where the ability to 

understand a verbal offer quickly is particularly important.178

Conclusion

The likelihood that consumers will become victims of one or more of the 

frauds covered by our survey or that their long distance telephone service will 

be changed without their approval is related to consumers’ characteristics. For 

example, members of several minority groups – American Indians or Alaska 

Natives, Hispanics, and African Americans – are more likely to be victims than 

non-Hispanic whites.

177. We do not presume that Hispanics who speak Spanish at home necessarily have limited English 

proficiency. We do expect, however, that a larger percentage of those in the Spanish-speaking Hispanic group 

have limited English proficiency than would be true for Hispanics who report that they do not speak Spanish 

in their homes. Thus, a finding that consumers in the Spanish-speaking Hispanic group are more likely to 

be victims would be consistent with the hypothesis that having a limited command of the English language 

increases the risk of being a victim.

178. Although consumers who are victims of slamming have not agreed to have their long distance 

service switched from one carrier to another, they have often been contacted by the competing carrier who 

seeks to get them to agree to change.
Chapter 4: Who is a Victim of Fraud?

77

We also find that consumers aged 65 and over do not appear more likely to 

be victims than younger consumers. While not unique to our results, this finding 

runs contrary to some conventional wisdom about the relationship between age 

and the likelihood of being a victim of fraud.

The likelihood of being a victim also depends on consumers’ perceptions 

of their present and future financial health. Those who anticipate large changes 

in their future income – whether positive or negative – are more likely to be 

victims than those who anticipate that their incomes will remain about the same. 

Furthermore, those who feel that they have more debt than they can comfortably 

handle are more likely to be victims.

Finally, we find that the demographic characteristics we have examined are 

related to the likelihood of experiencing different problems in different ways. 

The characteristics of those who are most likely to have had their long distance 

telephone service changed without authorization differ from the characteristics 

of those who face the greatest risk of being the victim of a fraud. Similarly, the 

characteristics of those at the greatest risk vary depending on the type of fraud.
Consumer Fraud in the United States: An FTC Survey

78
Chapter 5: Who Complains?

79

Chapter 5: Who Complains?

This chapter examines whether and to whom consumers complain when they 

experience an incident that appears to be fraud or slamming. We first consider 

what actions, if any, survey participants took in response to their experience. 

We then examine how the likelihood of complaining varies with the individual 

characteristics of the victim and with the type of fraud or slamming at issue. 

Finally, we consider the extent to which consumers who did complain were 

satisfied with the outcome of their complaints.

Complaint Data Collected 

Survey participants who indicated they had experienced an incident of 

apparent fraud or slamming were asked what actions, if any, they took in an effort 

to resolve the incident.179 If participants provided only a general response – such 

as saying that they did nothing, stopped buying from the company, or talked to 

their family or friends – they were then asked whether they had “reported” their 

experiences to anyone, and if so to whom.180 We have combined the responses to 

these questions to form the data on complaining behavior.

In this chapter, we examine a somewhat broader set of incidents than we 

examined in earlier chapters. Specifically, in previous chapters we counted as 

incidents of actual fraud only those incidents in which consumers lost money.

181 

We recognize, however, that whether consumers lose money as a result of 

a particular incident may depend on whether they complain. For example, 

consumers who use a credit card to pay for a transaction may be able to avoid 

paying for the item in question if they complain to their credit card company. 

Similarly, consumers may obtain a refund of any money they paid if they 

complain to the company with which they transacted business. As such, whether 

consumers complained may have affected whether we counted their experience 

as an incident of fraud in our earlier analyses. In this chapter, we examine all

instances in which survey participants reported experiencing an apparent fraud 

– regardless of whether they ultimately lost money – in order to more fully 

understand complaining behavior. 

179. Survey question 66. This question was asked each time a survey participant indicated that he or 

she had experienced a type of fraud or had experienced slamming. The question was asked in an open-ended 

form, and participants were invited to provide multiple responses.

180. Survey question 67 and 68. Participants were asked the two follow-up questions if their response 

to question 66 only included the following: (1) Did nothing, (2) Asked for a refund or replacement, (3) 

Stopped payment or refused to pay, (4) Stopped buying from the company, (5) Consulted a lawyer or other 

professional, (6) Complained to family or friends / told family or friends not to buy from the seller, (7) Other, 

or (8) Don’t know / refused.

181. The one exception involved slamming.
Consumer Fraud in the United States: An FTC Survey

80

To Whom Do Consumers Complain?

Table 5-1 provides statistics on the percentages of incidents of apparent 

fraud or slamming in which survey participants complained to various entities. 

Specifically, the table shows the percentage of cases in which consumers 

complained to (1) a seller or manufacturer, (2) an institution responsible for 

making payment for the item – i.e., a bank or credit card company, and (3) “an 

official source,” defined as a local, state, or federal government agency, or a Better 

Business Bureau.182 

182. The unit of observation for these statistics is experiencing one of the problems covered by the 

survey. Those consumers who experienced more than one of the types of problems examined in the survey 

will account for more than one observation in this analysis. Because participants who indicated that they 

suffered the same type of problem more than one time in the last year were only asked about any actions they 

took in response to the most recent incident of that type, a participant who had the same problem multiple 

times will only be a single observation in the analysis. On the other hand, participants who experienced none 

of the problems examined in the survey will not be represented at all.

Only about 15 percent of consumers who complained to one of the three entities – a seller or 

manufacturer, a bank or credit card company, or an official source – also complained to another of these 

entities. In only three instances did a consumer report complaining to all three entities.

Table 5-1: To Whom Did Consumers Complain?

Percent of Victims

Did Not Complain 29.3%

Did nothing 23.6%

Stopped buying from the company 4.1%

Talked with family or friends, told them not to buy from the seller 2.0%

Complained to an Official Source 8.4%

Complained to a Better Business Bureau 3.5%

Complained to a local consumer agency or local police 2.4%

Complained to the state Attorney General or state consumer agency 1.6%

Complained to a federal agency, including the Federal Trade Commission 1.4%

Complained to a Seller or Manufacturer 53.7%

Complained to a sales person or someone else at the firm that sold the product 30.6%

Asked for a refund or replacement 14.2%

Complained to the phone company 12.4%

Complained to the product manufacturer 3.2%

Complained to a Bank or Credit Card Company 18.6%

Complained to a credit card company 9.0%

Stopped payment or refused to pay 7.3%

Complained to a bank 3.5%

Other 2.4%

Consulted a lawyer or other professional 2.4%

Note. 

Based on 753 incidents of fraud reported by survey participants. Includes both incidents where the victim lost money 

as a result of the incident and those where no money was lost. Figures may sum to more than totals because 

individuals may have taken more than one of the listed actions.
Chapter 5: Who Complains?

81

In 29.3 percent of incidents consumers did not complain to any of the entities 

listed. In almost 24 percent of cases, consumers say that they did not do anything, 

while others said that they stopped buying from the company or talked with 

family or friends and suggested that they not buy from the company.

In 53.7 percent of incidents, consumers complained to the relevant seller or 

manufacturer. Parsing these complaints down further, we find that consumers 

complained to the seller in 30.6 percent of all cases and to a telephone company in 

12.4 percent of all cases.183 In another 14.2 percent of cases, consumers indicated 

generally that they requested a refund or replacement.184 In 18.6 percent of cases, 

consumers complained to a bank or credit card company.

Consumers complained to an official source only 8.4 percent of the time. The 

most frequently cited official source was the Better Business Bureau; consumers 

filed complaints with a BBB in 3.5 percent of incidents. Consumers complained 

to a federal agency, including the Federal Trade Commission, in only 1.4 percent 

of cases.185

Our analysis indicates that the likelihood that consumers complain when 

they experience an apparent fraud or slamming varies depending on the type of 

problem experienced. As illustrated by Table 5-2, consumers who were billed 

for an Internet-related service that they had not agreed to purchase were the 

most likely to complain – more than 88 percent complained to someone. By 

contrast, consumers who had purchased a pyramid scheme were the least likely to 

complain – less than one-quarter indicated that they had complained.186

183. We have included consumers who complained to the telephone company with those who 

complained to a seller, rather than with credit card companies and banks, because more than 75 percent of the 

complaints filed with the telephone company involved situations in which the telephone company was likely 

acting as a seller.

184. Presumably, requests for refunds or replacements were directed to the seller or manufacturer, 

although the survey did not ask whether such was the case.

185. AARP also collected information about complaints filed by consumers who were victims of frauds 

as part of their 1993 survey of consumer behavior. (American Association of Retired Persons, The Behavior 

of Older Consumers: An AARP Study, 1994.) In general, the pattern of complaints reported by consumers in 

that survey are not significantly different from the pattern we found in this survey. There are no significant 

differences between the surveys in terms of the share of consumers who reported that they did nothing in 

response to being a victim of fraud. There are also no significant differences in the share of consumers who 

contacted a local consumer agency or local consumer help line, the Better Business Bureau, or an agency 

of the federal government. The only significant difference involved those who said that they reported their 

experience to a state Attorney General or state consumer protection agency: whereas 6 percent of consumers 

in the 1993 AARP survey said they reported their experience to state authorities, only 2 percent of consumers 

in the current survey said they did so. This difference is significant at the 1 percent level of statistical 

significance. 

186. The Chi-square test for differences in the rate of complaining by type of problem is statistically 

significant at the 1 percent level. (In conducting this test it was necessary to drop the government jobs and 

business opportunities categories because there are too few consumers who experienced these types of frauds 

to meet the necessary statistical properties to conduct a Chi-square test.)

(continued...)
Consumer Fraud in the United States: An FTC Survey

82

Table 5-2: Percent of Consumers Who Complained, By Type of Problem

Type of Problem Percent Who 

Complained

Billed for Internet services you did not agree to purchase 88.4%

Long distance service changed without permission (“Slamming”) 75.3%

Billed for information services provided either over the Internet or by pay-per-call that you 

had not agreed to purchase

75.0%

Billed for a buyers’ club membership that you had not agreed to purchase 71.3%

Purchased credit repair 65.4%

Paid an advance fee to obtain a loan or credit card that you were promised that you would 

receive

44.9%

Purchased credit card insurance 39.1%

Made a payment to someone who represented that you would receive a government joba 37.5%

Paid money or made a purchase to receive a promised prize and did not receive the prize 

or prize was not as promised

34.8%

Purchased a business opportunity where promised earnings were not realized or promised 

assistance was not provided

33.3%

Purchased a membership in a pyramid scheme 22.7%

Other problems

 Paid for a product but did not receive it 83.3%

 Billed for a product that you did not agree to purchase, other than products included 

 above

83.2%

Note. 

a Based on fewer than ten incidents.

186. (...continued)

We find similar variations across types of fraud when we examine the percentage of consumers who 

complained to a seller or manufacturer or to a bank or credit card company. The correlation between the 

percentage of consumers who complained to sellers when they experienced different problems and the 

percentage who did not complain at all is -0.9233. The correlation between the percentage who complained 

to a bank or credit card company and those who did not complain is -0.6474.

Characteristics of Those Who Complain

As with our analysis of victimization in the previous chapter, we use both 

simple cross-tabulations and probit regression analysis here to examine the 

relationship between the likelihood that the consumer complained and the 

characteristics of the consumer as well as the type of transaction involved. Table 

5-3 provides the cross-tab results showing the relationship between the percentage 

of incidents in which a consumer complained and the individual characteristic 

being analyzed – whether a characteristic of the consumer or of the transaction. 

Figures 5-1 through 5-4 show the results of this analysis for a few of the most 

interesting variables. In both the figures and Table 5-3, we do not differentiate 

among complaints filed with different entities. Rather, we include all cases in 

which the consumer complained to at least one source, whether an official source, 

a seller or manufacturer, or a bank or credit card company.
Chapter 5: Who Complains?

83

As we discussed earlier, cross-tabs tell us whether consumers with a 

particular characteristic are more or less likely to complain than those who do 

not have that characteristic.187 However, the cross-tabs do not tell us whether any 

relationship is truly due to that particular characteristic or whether it is the result 

of other characteristics that occur frequently along with the first one. To address 

this limitation, we also used probit regressions in an effort to isolate more clearly 

which factors are actually related to the likelihood that a consumer will complain.

Table 5-4 provides the results of the probit analyses showing the marginal 

effects of the various characteristics on the likelihood that the consumer 

complained to one or more of the entities listed in Table 5-1. We also ran separate 

regressions for complaints to the three types of entities – a seller or manufacturer, 

a bank or credit card company, and an official source. These results are reported 

in Tables 5-5 to 5-7.188

In our analysis of complaining behavior, we consider many of the same 

characteristics that we used in analyzing victimization, including race and 

ethnicity, education, age, gender, and marital status.189 We also include two 

additional variables – Internet use and method of payment.190 

With respect to Internet use, we expect that consumers who are comfortable 

using the Internet may be more likely to file complaints. It is possible to file 

complaints online for some entities.191 Because this method of complaining may 

be more convenient and less burdensome than complaining in writing or over the 

telephone, consumers who use the Internet may be more likely to complain. 

In measuring Internet use, we draw upon responses to a question that asked 

whether survey participants had used the Internet to make any purchases in the 

187. See page 52, above.

188. As in our analysis of victimization, the regressions here are probits, because the dependent variable 

indicates either that a complaint was filed or that one was not filed. As in the earlier analysis, we have run 

regressions using only those observations for which we had values for all of the included variables (complete 

case analysis) and also regressions in which conditional mean imputation was used to provide estimates for 

missing values of the independent variables. Because of a limitation in the statistical package we were using 

and the number of variables included in the equations being estimated here, it was not possible to include all 

variables in the imputation estimation. In order to reduce the number of variables to a number our software 

could handle, we first used a step-wise regression routine to identify those variables that were making the 

least contribution in the imputation equation. Based on the results of this analysis, we then dropped enough 

variables from the imputation routine to meet the limitations of the statistical program.

189. We have not included the future income or debt level variables in the model here because it is not 

clear why these variables should affect complaining behavior.

190. In our regression analysis of complaining behavior, we also allow the proportion of consumers who 

complain to vary across different types of frauds. The marginal effects for various types of fraud and for 

slamming are reported in Table 5-11.

191. For example, victims of frauds can complain to the Federal Trade Commission by visiting 

http://www.ftc.gov/complaint, and victims of Identity Theft can file a complaint at 

http://www.consumer.gov/idtheft. Complaints about telemarketing calls received after a consumer’s phone 

number has been placed on the National Do Not Call Registry can be filed at http://www.donotcall.gov.
Consumer Fraud in the United States: An FTC Survey

84

last year, and if so, how many.192 From these responses we have constructed a 

variable indicating whether the person (i) made no Internet purchases, (ii) made 

one to three Internet purchases, or (iii) made four or more Internet purchases.193

We also examined the relationship between the method of payment and 

the likelihood of complaining. For example, some consumers who pay for a 

transaction with a credit card can complain about the transaction to their credit 

card company. In fact, federal law provides consumers with certain rights when 

they have paid for a transaction with a credit card.194 Thus, consumers who use a 

credit card to pay for a fraudulent offer may be more likely to complain than those 

who use other means of payment.195

We next discuss how various consumer characteristics are related to the 

likelihood that consumers will complain.

Internet Usage

The simple 

cross-tab analysis, 

which is reported 

in Figure 5-1 and 

Panel A of Table 

5-3, suggests that 

consumers who 

make greater use 

of the Internet are 

more likely to file 

a complaint. For 

example, complaints 

were filed in 78 

percent of cases 

when consumers 

192. Survey question 4. The survey did not ask whether participants actually filed a complaint online.

193. In any future surveys, it may be useful to ask consumers what method they used for filing 

complaints rather than constructing such a variable.

194. For a discussion of consumers’ billing dispute rights, see Federal Trade Commission, Bureau of 

Consumer Protection, Office of Consumer and Business Education, FTC Facts for Consumers: Fair Credit 

Billing, March 2002, at http://www.ftc.gov/bcp/conline/pubs/credit/fcb.htm.

195. In addition to creating variables for the various types of payment mechanisms, we created an 

additional variable to indicate situations in which the consumer was not asked about payment mechanism. 

The survey only asked about the payment mechanism if consumers indicated that they had actually paid 

money in the course of the transaction at issue. This approach may not have captured instances in which 

consumers disputed a charge to their credit card, because an individual who disputes a fraudulent charge does 

not actually pay the disputed amount. As such, it is not clear how survey participants who used credit cards 

and disputed the charges would have answered the question about how much they paid – some may have 

answered that they paid nothing, and thus were not asked how they paid for the item. 

(continued...)

Figure 5-1

Likelihood of Complaining

By Internet Usage

77.8%

68.1% 64.6%

0%

20%

40%

60%

80%

100%

No Internet Purchases One to Three Internet Purchases Four or More Internet Purchases

Source: Table 5-3
Chapter 5: Who Complains?

85

said that they made four or more purchases on the Internet in the last year, while 

complaints were filed in only 65 percent of cases when consumers made no 

Internet purchases. Overall, the difference in complaint levels across the three 

levels of Internet usage is significant at the 1 percent level using this method of 

analysis.196

Once we control for other characteristics that might affect the likelihood of 

complaining, however, the relationship between Internet use and the likelihood 

of filing a complaint is no longer significant. These results are shown in Table 

5-4. Although there may be a slight increase in the likelihood a consumer who 

made a purchase online will file a complaint, these differences are not statistically 

significant, either jointly or individually.197

The relationships between Internet usage and several of the other variables 

included in our regressions may explain this, at least in part. Younger consumers 

and those with higher levels of education are more likely to have made Internet 

purchases.198 In addition, Internet users are more likely to have paid for the 

fraudulent transaction with a credit card and less likely to have used cash 

195. (...continued)

We considered including the amount paid as an additional determinant of whether a complaint 

was filed, because the benefit of complaining should be greater when more money is at stake. We were 

concerned, however, that in some cases the figures reported for amount paid may not reflect the amount 

charged for the fraudulent offer, but rather the amount that the consumer lost as a result of the transaction. 

This possibility seems particularly likely when a credit card is used to pay for a transaction. Consumers who 

use a credit card and who realized that they have been the victim of a fraud before paying the bill have the 

opportunity to dispute the charge and to refuse payment. As a result, we suspect that some consumers who 

used credit cards would answer that they had not paid anything for the item in question (rather than report the 

price of the item). It is the price of the item – that is, the amount of money that would be lost if no complaint 

is made – that should affect the likelihood of complaining. Therefore, in those cases, the available data 

would not reflect the appropriate price. Thus, we did not include the amount paid in the final model.

196. The difference in the likelihood of complaining between consumers who made four or more 

Internet purchases and those who made no Internet purchases is significant at the 1 percent level. There 

is no significant difference between those with no online purchases and those who made one to three such 

purchases.

197. The coefficient on four-or-more Internet purchases is significant at the 10 percent level in the 

conditional-mean-imputation equation. As noted previously, however, the conditional-mean-imputation 

technique tends to overstate significance levels. Therefore, one should probably rely more on the 

insignificance of the coefficient in the complete case regression. When we look at the separate regression 

analyses of complaints to official sources, complaints to sellers or manufacturers, and complaints to banks or 

credit card companies in Tables 5-5 to 5-7, we find no significant effect of Internet usage.

198. The percentage of survey participants who said that they had made four or more Internet purchases 

in the last year rose from 5.8 percent for those who did not have a high school diploma to 43.5 percent 

for those with a college degree. The relationship between the level of Internet purchases and the level of 

education is significant at the 1 percent level. Looking at the relationship between age and Internet use, we 

find that the percentage of consumers making four or more Internet purchases falls from 38.1 percent of those 

between 25 and 34 to 8.3 percent for those who were 65 or over. The relationship between age and the level 

of Internet use is also significant at the 1 percent level.
Consumer Fraud in the United States: An FTC Survey

86

Table 5-3: Percent of Consumers Who Complain, By Single Characteristic

A. By Purchases Made on the Internet in the Last Year

Percent Who Complained

None 64.6%

One to three purchases 68.1%

Four or more purchases 77.8%

Number of Observations 753

B. By Education

Percent Who Complained

Did not complete high school 66.0%

Graduated from high school 61.7%

Attended some college or post-secondary technical or vocational school 69.8%

Graduated from college or more 78.1%

Number of Observations 733

C. By Age

Percent Who Complained

18 - 24 72.9%

25 - 34 73.1%

35 - 44 70.8%

45 - 54 72.2%

55 - 64 55.4%

65 and over 62.5%

Number of Observations 730

D. By Gender

Percent Who Complained

Male 64.2%

Female 74.5%

Number of Observations 753

E. By Marital Status

Percent Who Complained

Single 66.7%

Married 71.5%

Number of Observations 753

(Table continued on next page)
Chapter 5: Who Complains?

87

Table 5-3 (cont.)

F. By Current Income

Percent Who Complained

Less than $20,000 65.8%

$20,000 to $40,000 65.3%

$40,000 to $60,000 73.3%

$60,000 to $80,000 73.3%

$80,000 to $100,000 61.4%

Over $100,000 88.3%

Number of Observations 671

G. By Race and Ethnicity

Percent Who Complained

Hispanics 70.8%

African Americans 55.7%

American Indians or Alaska Natives 64.7%

Non-Hispanic Whites 72.1%

Others 71.4%

Number of Observations 702

H. By Method of Payment

Percent Who Complained

Credit card 72.1%

Cash 62.9%

Check 70.3%

Online payment system 75.0%

Seller took money directly from the consumer’s checking account 76.9%

Seller placed charge on consumer’s telephone bill 66.7%

Money order 52.8%

Number of Observations 440
Consumer Fraud in the United States: An FTC Survey

88

Table 5-4: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, Complaints Filed 

with Anyonea

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics 0.0171 0.0108

African Americans -0.0942 * -0.1319 **

American Indians or Alaska Natives 0.0106 0.0649

Other 0.0090 -0.0321

 Joint Significance ns ns

Gender (Relative to Male)

Female 0.0833 *** 0.0816 **

Marital Status (Relative to Married)

Single -0.0390 -0.0665 *

Age (Relative to 35 - 44)

18 - 24 0.1044 0.0737

25 - 34 0.0575 0.0085

45 - 54 0.0301 -0.0507

55 - 64 -0.1201 ** -0.1624 **

65 and over -0.0487 -0.0679

 Joint Significance ** *

Education (Relative to High School Graduate)

Did not complete high school 0.0601 0.0585

Attended some college or post-secondary technical or 

vocational school 0.0488 0.0977 **

Graduated from college or more 0.0849 * 0.1049 **

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 -0.0055 -0.0218

$20,000 - $40,000 0.0035 0.0232

$60,000 - $80,000 0.0270 0.0654

$80,000 - $100,000 -0.1322 ** -0.1631 **

Over $100,000 0.1257 * 0.1266 *

 Joint Significance ** **

Internet Purchases in Last Year (Relative to No Purchases)

One to three purchases 0.0245 0.0098

Four or more purchases 0.0754 * 0.0361

 Joint Significance ns ns

Payment Mechanism Used (Relative to Paying with Credit Card)

Cash -0.0596 -0.0832

Check 0.0033 -0.0195

Online payment service -0.0292 -0.0407

Seller took money directly from checking account 0.0439 0.0221

Amount charged on telephone bill -0.0223 0.0639

Money order -0.0374 -0.1051

Question not asked 0.0334 0.0050

 Joint Significance ns ns

Number of Observations 753 598

Percent Positive Values 69.32% 70.74%

Chi-square for Overall Significanceb 168.46 *** 128.92 ***

(Notes on next page)
Chapter 5: Who Complains?

89

Table 5-4 (cont.)

Notes. 

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test

a Regressions also controlled for the type of fraud involved. 

 Marginal effects by fraud type for equation (1) are reported in Table 5-11. In both equations, the type of fraud 

variables are jointly significant at the 1 percent level and the likelihood of complaining is significantly higher than for 

consumers who paid an advance fee for a loan or credit card, the control group, at the 5 percent level or above, for 

(i) consumers who received an unauthorized bill for Internet-related services (“Q19”), (ii) consumers who received an 

unauthorized bill for a product other than those specifically listed (“Q22”), (iii) consumers who paid for a product that 

they never received (“Q48”), or (iv) consumers whose long distance service was changed without their authorization 

(“Q28”). The likelihood of complaining is significantly below that for the control group for consumers who purchased 

a membership in a pyramid scheme (“Q33”). In addition, in equation (1), the likelihood of complaining is significantly 

greater for consumers who (i) were victims of a credit improvement fraud (“Q13”) or (ii) were billed for a buyers’

club membership that they had not agreed to join (“Q21”). In equation (2), no one who had purchased a business 

opportunity where false claims about earnings or assistance were made (“Q35”) filed a complaint.

b Includes the effect of type of fraud variables.
Consumer Fraud in the United States: An FTC Survey

90

Table 5-5: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, Complaints Filed 

with Official Sourcesa

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics -0.0270 -0.0419

African Americans -0.0264 -0.0269

American Indians or Alaska Natives 0.1155 0.1708 *

Other 0.0727 0.0849

 Joint Significance ns *

Gender (Relative to Male)

Female -0.0312 * -0.0366

Marital Status (Relative to Married)

Single 0.0105 -0.0039

Age (Relative to 35 - 44)

18 - 24 0.0303 0.0430

25 - 34 -0.0327 -0.0461

45 - 54 0.0052 -0.0199

55 - 64 0.0057 -0.0173

65 and over -0.0055 -0.0060

 Joint Significance ns ns

Education (Relative to High School Graduate)

Did not complete high school -0.0190 -0.0488

Attended some college or post-secondary technical or 

vocational school -0.0168 -0.0297

Graduated from college or more 0.0246 0.0226

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0294 0.0316

$20,000 - $40,000 0.0282 0.0279

$60,000 - $80,000 0.0138 0.0092

$80,000 - $100,000 -0.0033 -0.0230

Over $100,000 0.0686 0.0475

 Joint Significance ns ns

Internet Purchases in Last Year (Relative to No Purchases)

One to three purchases -0.0139 -0.0436

Four or more purchases 0.0109 0.0041

 Joint Significance ns ns

Payment Mechanism Used (Relative to Paying with Credit Card)

Cash 0.1223 ** 0.1116 **

Check 0.0588 ** 0.0521 *

Online payment service 0.3386 *** 0.2733 **

Seller took money directly from checking account 0.1443 ** 0.1263 **

Amount charged on telephone bill 0.0878 0.1156

Money order 0.0662 0.0123

Question not asked 0.0358 ** 0.0599 **

 Joint Significance ** ns

Number of Observations 742 545

Percent Positive Values 8.49% 8.26%

Chi-square for Overall Significanceb 51.28 * 48.71 ns

(Notes on next page)
Chapter 5: Who Complains?

91

Table 5-5 (cont.)

Notes. 

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test

a Regressions also controlled for the type of fraud involved.

 Marginal effects by fraud type for equation (1) are reported in Table 5-11. In both equations, the type of fraud 

variables are not jointly significant. However, in equation (1), the likelihood of complaining to an official source is 

significantly greater for victims of Q13. In equation (2), none of the fraud type variables was individually significant. 

In both equations, no one who (i) was a victim of Q35 or (ii) paid someone who promised that the consumer would 

get a government job (“Q38”) complained to an official source. Therefore these observations were not used in the 

estimation.

b Includes the effect of the type of fraud variables.
Consumer Fraud in the United States: An FTC Survey

92

Table 5-6: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, Complaints Filed 

with Seller or Manufacturera

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics -0.0317 0.0043

African Americans -0.1406 ** -0.1636 **

American Indians or Alaska Natives -0.0824 -0.0297

Other -0.0396 -0.0538

 Joint Significance ns ns

Gender (Relative to Male)

Female 0.0744 ** 0.1006 **

Marital Status (Relative to Married)

Single 0.0062 -0.0183

Age (Relative to 35 - 44)

18 - 24 0.0847 0.0606

25 - 34 0.0736 0.0543

45 - 54 0.0119 -0.0749

55 - 64 -0.1260 ** -0.1164

65 and over -0.1056 -0.1291 *

 Joint Significance *** *

Education (Relative to High School Graduate)

Did not complete high school 0.1018 0.0744

Attended some college or post-secondary technical or 

vocational school 0.0579 0.1096 **

Graduated from college or more 0.0416 0.0597

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 -0.1082 * -0.1150 *

$20,000 - $40,000 -0.0462 -0.0291

$60,000 - $80,000 0.0382 0.0582

$80,000 - $100,000 -0.1545 ** -0.1727 **

Over $100,000 0.0761 0.0807

 Joint Significance  

Internet Purchases in Last Year (Relative to No Purchases)

One to three purchases -0.0053 0.0178

Four or more purchases 0.0329 0.0220

 Joint Significance ns ns

Payment Mechanism Used (Relative to Paying with Credit Card)

Cash -0.1291 -0.1435

Check -0.0235 -0.0352

Online payment service 0.1291 0.0784

Seller took money directly from checking account -0.1064 -0.1015

Amount charged on telephone bill 0.0783 0.1571

Money order -0.0451 -0.0875

Question not asked -0.1708 ** * -0.1671 ***

 Joint Significance  

Number of Observations 753 552

Percent Positive Values 53.65% 54.71%

Chi-square for Overall Significanceb 169.29 ** * 137.10 ***

(Notes on next page)
Chapter 5: Who Complains?

93

Table 5-6 (cont.)

Notes. 

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test

a Regressions also controlled for the type of fraud involved.

 Marginal effects by fraud type for equation (1) are reported in Table 5-11. In both equations the type of fraud 

variables are jointly significant at the 1 percent level, and victims of (i) Q19, (ii) Q22, (iii) Q28, and (iv) Q48 are 

significantly more likely to complain to a seller or manufacturer than are those in the control group at the 5 percent 

level or above. In addition, in equation (1), victims of Q21 are significantly more likely to complain to a seller or 

manufacturer than are those in the control group, while victims of Q33 are significantly less likely to complain to a 

seller or manufacturer than those in the control group. In equation (2), no victims of Q35 complained to a seller or 

manufacturer. Therefore, these observations were dropped in estimating the equations.

b Includes the effect of the type of fraud variables.
Consumer Fraud in the United States: An FTC Survey

94

Table 5-7: Likelihood of Filing a Complaint, Probit Estimation, Marginal Effects, Complaints Filed 

with Bank or Credit Card Companya

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics -0.0044 0.0092

African Americans 0.0716 0.0490

American Indians or Alaska Natives 0.1571 0.1610

Other 0.1292 ** 0.1410 *

 Joint Significance ns ns

Gender (Relative to Male)

Female 0.0383 0.0110

Marital Status (Relative to Married)

Single -0.0776 ** -0.0696 *

Age (Relative to 35 - 44)

18 - 24 0.1073 * 0.0927

25 - 34 0.0156 -0.0150

45 - 54 0.0396 0.0304

55 - 64 0.0468 0.0329

65 and over 0.0451 0.0403

 Joint Significance ns ns

Education (Relative to High School Graduate)

Did not complete high school -0.0107 0.0269

Attended some college or post-secondary technical or 

vocational school -0.0384 -0.0594

Graduated from college or more 0.0093 0.0066

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0446 0.0280

$20,000 - $40,000 -0.0262 -0.0266

$60,000 - $80,000 0.0240 0.0236

$80,000 - $100,000 0.0606 0.0171

Over $100,000 0.0070 0.0089

 Joint Significance ns ns

Internet Purchases in Last Year (Relative to No Purchases)

One to three purchases -0.0093 -0.0154

Four or more purchases 0.0275 0.0229

 Joint Significance ns ns

Payment Mechanism Used (Relative to Paying with Credit Card)

Cash -0.1718 ** -0.1675 *

Check -0.1244 *** -0.1283 ***

Online payment service 0.0531 0.0468

Seller took money directly from checking account -0.0098 -0.0036

Amount charged on telephone bill -0.0604 0.0324

Money order -0.1887 ** -0.1929 **

Question not asked 0.0573 0.0613

 Joint Significance *** ***

Number of Observations 719 526

Percent Positive Values 19.47% 21.10%

Chi-square for Overall Significancec 119.79 *** 89.25 ***

(Notes on next page)
Chapter 5: Who Complains?

95

Table 5-7 (cont.)

Notes. 

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test

a Regressions also controlled for the type of fraud involved.

 Marginal effects by fraud type for equation (1) are reported in Table 5-11. In both equations, the type of fraud 

variables are jointly significant at the 1 percent level. In both equations, victims of Q28 are significantly less likely to 

complain to a bank or credit card company than those in the control group. In addition, in equation (1), victims of Q19 

are significantly more likely to complain than those in the control group. In both equations, no victims of (i) Q35, (ii) 

Q38, or (iii) Q44 filed complaints with a bank or credit card company. Therefore these observations were not used in 

estimating the equation.

b (n) indicates that no complaints were filed with a bank or credit card company by victims with this characteristic. 

Therefore, these observations were dropped in estimating the equation.

c Includes the effect of the type of fraud variables.
Consumer Fraud in the United States: An FTC Survey

96

Figure 5-2

Likelihood of Complaining

By Education

78.1%

69.8%

61.7% 66.0%

0%

20%

40%

60%

80%

100%

Did Not Complete High

School

High School Graduate Some College or

Technical/Vocational

College Graduate or More

Source: Table 5-3

or a money order.199 Since we also find that younger consumers, those with 

higher levels of income, and those who use credit cards are more likely to file 

complaints, it is difficult to identify which factor is actually leading to the higher 

level of complaints.

Education Level

Figure 5-2 and Panel B of Table 5-3 show the simple relationship between 

the likelihood of complaining and the consumer’s educational level. These 

cross-tab results suggest that education beyond the high school level is associated 

with an increase 

in complaints 

filed. Overall, the 

relationship between 

complaining and 

educational level 

is statistically 

significant. 

Although 

consumers who 

had only graduated 

from high school 

complained in 

62 percent of 

cases, those who 

had attended 

some college or had attended a post-secondary technical or vocational school 

complained 70 percent of the time. Consumers who had graduated from college 

complained 78 percent of the time.200 However, consumers with less than a 

high school education were not less likely to complain than were high school 

graduates.

199. Just over half of those who said that they had made Internet purchases in the last year also said that 

they had used a credit card to pay for the fraudulent transaction. In comparison, less than 25 percent of those 

who had not made any Internet purchases said that they had paid with a credit card. By contrast, those who 

used cash to pay for the transaction falls from 12 percent for those who had no Internet purchases to 3 percent 

for those who had 4 or more such purchases, while the use of money orders falls from 11 percent to 5 percent.

200. The percentage of consumers with some post-secondary education who file a complaint is 

significantly greater, at the 10 percent level, than the percentage of consumers with a high school degree. If 

the consumer has a college degree, the proportion of those filing a complaint is significantly greater, at the 1 

percent level, than the percentage of those who only have a high school diploma. Overall, the relationship 

between the percentage of consumers filing a complaint and education level is significant at the 1 percent 

level.
Chapter 5: Who Complains?

97

Figure 5-3

Likelihood of Complaining

By Age

62.5%

55.4%

72.2% 70.8% 72.9% 73.1%

0%

20%

40%

60%

80%

100%

18 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 and over

Source: Table 5-3

As shown in Table 5-4, the effect of education on the likelihood of filing a 

complaint is smaller and less significant when we control for other factors. We 

still find that consumers with college degrees are more likely to complain than 

those with a high school degree. However, the difference is only about 8.5 

percentage points and is only significant at the 5 or 10 percent level (depending 

on the equation used) rather than the 1 percent level in the cross-tabs. Similarly, 

consumers with some post-secondary education are 5 or 10 percentage points 

more likely to complain, though the results are only significant in one of the two 

equations.201

Age

The cross-tab relationship between age and the share of consumers who 

complain is shown in Figure 5-3 and in Panel C of Table 5-3. This analysis 

suggests that about 

70 percent of 

consumers under 

age 55 complain. 

The likelihood of 

filing a complaint 

drops to around 50 

to 60 percent for 

consumers aged 55 

to 64.202 Those over 

age 65 are more 

likely to complain 

than the 55 to 64 

year old group but 

less likely than the 

younger consumers.

The results of the more sophisticated probit analysis in Table 5-4 show a 

smoother relationship between age and the likelihood that a consumer complains. 

In both equations, consumers aged 18 to 24 were the most likely to complain, 

and the likelihood falls rather steadily through the 55 to 64 year old group.203 As 

in the cross-tab results, those who are 65 or older appear somewhat more likely 

to complain than those in their late 50s and early 60s. The relationship between 

201. Looking at the analyses of the separate types of complaints in Tables 5-5 through 5-7, we find that 

the effect of education is also insignificant in each of them.

202. The percentage of instances in which a complaint was filed when the consumer was less than 55 

years old is significantly higher than the complaint rate where the consumer was 55 or over. This difference 

is significant at the 1 percent level. Overall, the relationship between age and the percentage of those filing a 

complaint is significant at the 5 percent level in the cross-tab analysis.

203. The one exception is that those between 45 and 54 are found to have a 3 percentage point greater 

likelihood of complaining than those who are 35 to 44 in the conditional-mean-imputation equation. 

However, this difference is far from being statistically significant.
Consumer Fraud in the United States: An FTC Survey

98

age and the likelihood of complaining, however, is only statistically significant 

at the 10 percent level in the complete case equation, and many of the individual 

differences are not statistically significant.

Examining Tables 5-5 to 5-7, which show complaints to each of the three 

types of entities separately, we find that younger consumers are more likely to 

complain to a seller or manufacturer than older consumers.204 There is no clear 

relationship between age and the likelihood of complaining to a bank or credit 

card company, however. There is also no clear relationship when we examine 

complaints to official sources.205

Income

Panel F of Table 5-3 shows the simple relationship between income and the 

likelihood of complaining.206 In both the cross-tab and the probit results (set forth 

in Table 5-4), there appears to be little variation in the likelihood of complaining 

at income levels below $80,000. Those with lower incomes – particularly those 

with incomes under $20,000 – may be slightly less likely to complain. Regardless 

of the estimation technique used, however, the differences are not statistically 

significant. 

There are some differences in the rate of complaining at income levels above 

$80,000. While it is not clear why such differences should exist, both the crosstab and the probit results show that consumers with incomes between $80,000 and 

$100,000 are less likely to complain than those with lower income levels. On the 

other hand, consumers with incomes in excess of $100,000 are the most likely to 

complain.207

204. See Table 5-6 where the age variables are jointly significant at the 1 percent level in the conditionalmean-imputation equation and at the 10 percent level in the complete case equation.

205. The overall relationship between complaints and age is not significant in either Table 5-5, which 

examines complaints to official sources, or Table 5-7, which examines complaints to banks or credit card 

companies.

206. The relationship between the income variables and the likelihood of filing a complaint is jointly 

significant at the 1 percent level in the simple cross-tabs and at the 5 percent level in both regression 

equations.

207. The difference between the likelihood of complaining for those with incomes of $80,000 to 

$100,000 and those with incomes of $40,000 to $60,000 is significant at the 10 percent level in the simple 

cross-tabs and is significant at the 5 percent level in both regression analyses. Comparing the over-$100,000 

group with the $40,000 to $60,000 group, the differences are significant at the 5 percent level in the simple 

cross-tabs and at the 10 percent level in the regression results.

Looking separately at complaints to the three different types of entities, we see that those with incomes 

between $80,000 and $100,000 are significantly less likely to complain to a seller or manufacturer than 

those with incomes of $40,000 to $60,000. For complaints to official sources and to banks or credit card 

companies, the differences are not statistically significant.
Chapter 5: Who Complains?

99

Figure 5-4

Likelihood of Complaining

By Gender

74.5%

64.2%

0%

20%

40%

60%

80%

100%

Male Female

Source: Table 5-3

Gender and Marital Status

Women are 

more likely to 

complain about 

fraud or slamming 

than men. The 

simple relationship 

between 

complaining and 

gender, as set forth 

in Panel D of Table 

5-3 and in Figure 

5-4, indicates 

that women who 

experienced fraud 

or slamming 

are about ten 

percentage points more likely to complain than are men. The regression results 

show virtually the same difference. Furthermore, this difference is statistically 

significant in both the regression equations and the cross-tabs.208

Considering complaints to each of the three types of entities separately, Table 

5-6 shows that women are a statistically significant 7.5 to 10 percentage points 

more likely to complain to a seller or manufacturer than men.209 The results in 

Table 5-7 also suggest that women are more likely to complain to a bank or credit 

card company than men, although the difference is not statistically significant. 

On the other hand, the results in Table 5-5 suggest that women are somewhat less 

likely to complain to official sources, although the difference is only statistically 

significant in the conditional-mean-imputation equation. 

The estimates in Panel E of Table 5-3 suggest that married consumers are 

more likely to complain about fraud or slamming than singles. However, the 

difference in complaint rates is only 4 percentage points in the cross-tabs and 

between 4 and 7 percentage points in the regressions. In none of the cases is the 

difference statistically significant.

208. The level of significance is 1 percent in the simple comparisons and at 1 or 5 percent in the 

regressions.

209. The difference is significant at the 5 percent level.
Consumer Fraud in the United States: An FTC Survey

100

Race and Ethnicity

The results of 

our simple crosstab analysis by race 

and ethnic group are 

reported in Panel G 

of Table 5-3 and in 

Figure 5-5. We find 

that complaint rates 

are the lowest for 

African Americans. 

The simple analysis 

suggests that 

the likelihood of 

complaining is a 

statistically significant 16 percentage points lower for African Americans than for 

non-Hispanic whites.210 The regression results in Table 5-4 also show that African 

Americans are the least likely to complain and that they are 9 to 13 percentage 

points less likely to complain than non-Hispanic whites, depending on which 

equation one examines. The differences are significant at the 10 percent level.211

The simple cross-tab results presented in Table 5-3 suggest that American 

Indians or Alaska Natives, Hispanics, and those in the “Other” racial category are 

slightly less likely to complain than non-Hispanic whites. For American Indians 

or Alaska Natives, the difference is about 7.5 percentage points – 64.7 percent 

versus 72.1 percent. For Hispanics and “Others,” the difference is approximately 

1 percentage point. In none of these cases are the results statistically significant. 

By contrast, the regression results suggest that, after controlling for other factors, 

Hispanics and American Indians or Alaska Natives may be more likely to 

complain than non-Hispanic whites. Again, however, the differences are small 

and are not statistically significant.212

210. The difference is significant at the 1 percent level. 

211. The separate analyses of complaints to different types of entities show that African Americans are 

significantly less likely to complain to a seller or manufacturer than are non-Hispanic whites (Table 5-6). 

The results also suggest that they are less likely to complain to an official source, though the difference there 

is not statistically significant (Table 5-5). The results in Table 5-7 suggest that African Americans may be 

somewhat more likely to complain to a bank or credit card company, though the differences again are not 

statistically significant.

212. With two exceptions, members of these three groups are neither significantly more or significantly 

less likely to complain to any of the three types of complaint entities, when we look at them individually. 

The results in Table 5-7 indicate that those in the “Other” category are significantly more likely to complain 

to a bank or credit card company, while the results in Table 5-5 suggest American Indians or Alaska Natives 

are more likely to complain to official sources. In both cases, the differences are only significant at the 10 

percent level if we focus on the complete case analysis, which gives more reliable measures of statistical 

significance.

Figure 5-5

Likelihood of Complaining

By Race and Ethnicity

72.1% 71.4%

64.7%

55.7%

70.8%

0%

20%

40%

60%

80%

100%

Hispanics African

Americans

American Indians

/ Alaska Natives

Non-Hispanic

Whites

Others

Source: Table 5-3
Chapter 5: Who Complains?

101

As with our analysis of victimization, we also attempted to investigate the 

role of language on the likelihood of filing a complaint. If victims of fraud are 

not fluent in English, they may be less likely to complain about a fraudulent 

experience. We therefore examined whether Hispanics who said that they spoke 

Spanish at home were less likely to file a complaint than other Hispanics.213 

When we added a Spanish-language variable to the regressions in Table 5-4, the 

results suggested that Hispanics who spoke Spanish were only about 60 percent 

as likely to complain as other Hispanics. This difference is significant at the 5 

percent level in a one-tailed test.214

Method of Payment

The results in Panel H of Table 5-3 do not appear to provide much support 

for the hypothesis that consumers who paid with a credit card would be the most 

likely to complain. Although complaint rates appear to be slightly higher when 

consumers paid by credit card than when they paid with cash, the differences are 

not statistically significant. Indeed, the only statistically significant result is that 

those who pay by money order are significantly less likely to complain than those 

who use other methods of payment.215 Similarly, the probit analyses presented in 

Table 5-4 suggest that the method of payment does not have a significant effect on 

the likelihood of complaining, either jointly or individually. 

In Table 5-7, however, we find that consumers who paid with a credit card 

are significantly more likely – 3 to 4 times as likely – to complain to a bank or 

credit card company as those who paid with cash, a check, or a money order. 

By contrast, Table 5-5 shows that consumers who paid with a credit card are 

significantly less likely to complain to an official source than are those who used 

any of the other means of payment. Indeed, those who paid with cash were 4.5 

to 5 times as likely to complain to an official source as were those who paid with 

a credit card. It may be that consumers who used a credit card are more likely to 

complain to the credit card company and have their problem adequately resolved. 

As a result, there may be less need to complain to an official source.216

213. As with the analysis of victimization, we limit Spanish-speaking Hispanics to those who said that 

Spanish was the only language other than English spoken in their homes.

214. A one-tailed test – i.e., a test of whether Hispanics who spoke Spanish at home were less likely 

to complain than Hispanics who did not speak Spanish at home – is appropriate here, rather than a test of 

just whether there are differences between the two groups, because the hypothesis is that Spanish-speaking 

Hispanics will be less likely to complain than other Hispanics. We do not examine the effect of speaking 

Spanish separately for the three types of entities to whom complaints might be made because of the small 

number of non-Spanish speaking Hispanics in the sample.

215. In the simple comparisons, the complaint rate for those who paid with a money order is significantly 

lower than the rates for those who paid with a credit card or with a check (both significant at the 5 percent 

level), and those situations where the seller took the money directly from the consumer’s checking account 

(significant at the 10 percent level). 

216. As discussed on page 81, a simple comparison shows that complaint rates differ significantly by 

type of fraud. To determine whether this remained true after we controlled for the other characteristics in our 

regressions, we also included type-of-fraud variables in our regressions. Although the results for these 

(continued...)
Consumer Fraud in the United States: An FTC Survey

102

Another noteworthy feature of the relationship between complaints to 

official sources and the means of payment is that consumers who used an online 

payment service were the most likely to complain to an official source. Indeed, 

these consumers were about twice as likely to complain to an official source as 

those who paid with cash, and were 10 to 12 times as likely to complain to an 

official source as consumers who used a credit card.217 Again, this result suggests 

that consumers who are most comfortable using the Internet are more likely to 

complain than those who are not.

How Satisfied Are Those Who Complain?

Finally, the survey asked consumers who complained how satisfied they were 

with what happened as a result.218 The distribution of responses to this question 

are shown in Table 5-8. In about 60 percent of cases, consumers indicated that 

they were satisfied (either “Very Satisfied” or “Somewhat Satisfied”). In the 

remaining 40 percent of cases, consumers stated they were dissatisfied (either 

“Not too Satisfied” or “Not at All Satisfied”).219

We have also examined whether satisfaction with the outcome of filing a 

complaint varies depending on the entity to which the consumer complained, the 

characteristics of the transaction at issue, or the characteristics of the individual 

216. (...continued)

variables are not reported in the body of Tables 5-4 to 5-7, the footnotes to the tables report on the overall 

significance of these variables, as well as noting those types of fraud where complaints are more or less 

likely to be made. The marginal effects by fraud type are also reported in Table 5-11. When we examine 

total complaints, complaints to official sources, or complaints to sellers or manufacturers, the type-of-fraud 

variables are jointly significant at the 5 percent level or better. The type-of-fraud variables were not jointly 

significant when the variable analyzed was complaints to banks or credit card companies.

217. The difference between the rate of complaining to an official source for those who paid with an 

online mechanism and those who paid with a credit card is statistically significant at the 5 percent level in 

the complete case regression. The difference between the rates for those who paid with an online service and 

those who paid with cash is not significant in the complete-case regression.

218. Survey question 69. Survey participants who said that they had (1) asked for a refund or 

replacement, (2) stopped payment or refused to pay, (3) stopped buying from the company, (4) consulted a 

lawyer, or (5) complained to family or friends, were not asked about satisfaction. Participants who indicated 

that they had complained to multiple entities about the same incident were asked how satisfied they were 

with the outcome of their complaints to the first two entities they mentioned. Although this approach might 

have the potential to bias responses – because consumers may be more likely to mention reporting their 

experiences when they were particularly satisfied or dissatisfied with the experience – no significant problem 

appears to have been introduced with our data because very few consumers indicated they had complained to 

more than two entities. 

219. The 1993 AARP survey also asked consumers who had complained how satisfied they were with the 

results of their complaints. (AARP (1994)) The level of satisfaction reported by participants in our current 

survey appears to be somewhat higher than AARP found. Compared to nearly 60 percent of complaint-filers 

who said that they were very or somewhat satisfied in this survey, AARP found that only about 45 percent of 

complaint-filers were similarly satisfied. The difference in satisfaction levels is significant at the 5 percent 

level.
Chapter 5: Who Complains?

103

Table 5-8: Degree of Satisfaction with Results of Complaints

Percent

Satisfied 59.6%

Very satisfied 36.5%

Somewhat satisfied 23.1%

Not Satisfied 40.4%

Not too satisfied 7.2%

Not at all satisfied 33.2%

Figure 5-6

Complaint Satisfaction

By Party Complained To

53.7%

80.7%

54.0%

0%

20%

40%

60%

80%

100%

Offical Source Bank or Credit Card

Company

Seller or Producer

Source: Table 5-9

consumer. As with our earlier analyses, we have used both simple crosstabulation analysis and the more sophisticated probit regression analysis. We 

present the cross-tab results in Table 5-9 and the probit results in Table 5-10.220

Entity To Whom Complaint Was Made

The simple cross-tab analysis, which is reported in Panel A of Table 5-

9 and also in 

Figure 5-6, shows 

that consumers’ 

satisfaction with 

the outcome of 

their complaints 

varies significantly 

depending on the 

entity to whom 

the consumer 

complained. 

Satisfaction 

levels are highest 

– around 80 percent 

– for complaints 

made to a credit 

card company or a bank. This rate is significantly different from the 54 percent 

satisfaction rate when the consumer complained to an official source or to a seller 

or manufacturer.221

220. As with the earlier regression analyses, we have used both complete case analysis and conditional 

mean imputation. As with our analysis of complaining, we had to limit the number of variables included 

in the impute routine because of a limitation in our software. See footnote 188, above. Finally, as with our 

regression analysis of complaining, we also allow the proportion of consumers who are satisfied with the 

results of complaints to vary across different types of frauds. The marginal effects for various types of fraud 

and for slamming are reported in Table 5-11.

221. In both cases, the difference is significant at the 1 percent level.
Consumer Fraud in the United States: An FTC Survey

104

Table 5-9: Satisfaction with the Results of a Complaint, By Single Characteristic

A. By Who Complained To

Percent Satisfied

Complained to an official source 54.0%

Complained to a bank or credit card company 80.7%

Complained to a seller or producer 53.7%

Number of Observations 407

B. By Amount Lost

Percent Satisfied

$0 77.0%

$1 - $49 51.6%

$50 - $99 34.0%

$100 or more 28.2%

Number of Observations 390

C. By Purchases Made on the Internet in the Last Year

Percent Satisfied

None 55.6%

One to three purchases 66.7%

Four or more purchases 62.2%

Number of Observations 428

D. By Education

Percent Satisfied

Did not complete high school 43.5%

Graduated from high school 58.9%

Attended some college or post-secondary technical or vocational school 57.4%

Graduated from college or more 64.7%

Number of Observations 419

E. By Gender

Percent Satisfied

Male 59.5%

Female 59.7%

Number of Observations 428

F. By Marital Status

Percent Satisfied

Single 61.7%

Married 57.9%

Number of Observations 428

(Table continued on next page)
Chapter 5: Who Complains?

105

Table 5-9 (cont.)

G. By Age

Percent Satisfied

18 - 24 59.0%

25 - 34 55.9%

35 - 44 55.4%

45 - 54 64.0%

55 - 64 68.9%

65 and over 63.4%

Number of Observations 410

H. By Current Income

Percent Satisfied

Less than $20,000 65.6%

$20,000 to $40,000 51.0%

$40,000 to $60,000 66.2%

$60,000 to $80,000 57.8%

$80,000 to $100,000 58.1%

Over $100,000 66.7%

Number of Observations 376

I. By Race and Ethnicity

Percent Satisfied

Hispanics 57.1%

African Americans 48.7%

American Indians or Alaska Natives 27.3%

Non-Hispanic Whites 63.0%

Others 62.5%

Number of Observations 403

J. By Method of Payment

Percent Satisfied

Credit card 62.6%

Cash 28.0%

Check 49.4%

Online payment system 40.0%

Seller took money directly from the consumer’s checking account 41.7%

Seller placed charge on consumer’s telephone bill 50.0%

Money order 33.3%

Number of Observations 253
Consumer Fraud in the United States: An FTC Survey

106

Table 5-10: Satisfaction with Results of Complaints, Probit Estimation, Marginal Effectsa

Conditional Mean 

Imputation

(1)

Complete Cases 

Only

(2)

To Whom Complained (Relative to an Official Source)

Bank or credit card company 0.0534 0.1033

Seller or producer -0.1609 ** -0.1430 * 

 Joint Significance *** *** 

How Much Lost (Relative to $0)

$1 to $49 -0.2517 *** -0.1710 * 

$50 to $99 -0.4031 *** -0.3353 *** 

$100 or more -0.4733 *** -0.3762 *** 

 Joint Significance *** ***

Race and Ethnicity (Relative to Non-Hispanic Whites)

Hispanics -0.0084 0.0039

African Americans -0.0133 -0.0677

American Indians or Alaska Natives -0.2556 * -0.2101

Other -0.0420 -0.1050

 Joint Significance ns ns

Gender (Relative to Male)

Female 0.0877 * 0.1006 *

Marital Status (Relative to Married)

Single 0.0765 0.0632

Age (Relative to 35 - 44)

18 - 24 0.0425 0.0737

25 - 34 -0.0042 -0.0366

45 - 54 0.0044 -0.0097

55 - 64 0.1435 * 0.0905

65 and over -0.0350 -0.1640

 Joint Significance ns ns

Education (Relative to High School Graduate)

Did not complete high school -0.0126 -0.0397

Attended some college or post-secondary technical or 

vocational school -0.0012 -0.0153

Graduated from college or more -0.0147 0.0150

 Joint Significance ns ns

Current Income (Relative to $40,000 to $60,000)

Less than $20,000 0.0727 -0.0160

$20,000 - $40,000 -0.0381 -0.1107

$60,000 - $80,000 -0.0276 -0.0741

$80,000 - $100,000 -0.0211 -0.2517 **

Over $100,000 -0.0814 -0.1978

 Joint Significance ns ns

Internet Purchases in Last Year (Relative to No Purchases)

One to three purchases 0.0802 -0.0254

Four or more purchases 0.0640 0.0633

 Joint Significance ns ns

Payment Mechanism Used (Relative to Paying with Credit Card)

Cash -0.2077 * -0.2322 **

Check 0.0102 -0.0725

Online payment service -0.0527 -0.0645

Seller took money directly from checking account -0.0856 -0.0953

Amount charged on telephone bill 0.0031 -0.0061

Money order 0.0423 -0.0577

 Joint Significance ns ns

Number of Observations 406 299

Percent Positive Values 59.36% 60.20%

Chi-square for Overall Significanceb 135.56 *** 106.72 ***

(Notes on next page)
Chapter 5: Who Complains?

107

Table 5-10 (cont.)

Notes.

 *** significant at 1 percent level

 ** significant at 5 percent level

 * significant at 10 percent level

 ns not significantly different from zero in joint test

a Regressions also controlled for the type of fraud involved.

 Marginal effects by fraud type for equation (1) are reported in Table 5-11. In both equations, the type of fraud 

variables are jointly significant at the 1 percent level. In equation (1), the likelihood of being satisfied with the results 

of a complaint is significantly higher than for someone who paid an advance fee for a loan or credit card, the control 

group, at the 5 percent level or above, for (i) someone who received an unauthorized bill for Internet-related services 

(“Q19”), (ii) someone who received an unauthorized bill for a product other than those specifically listed (“Q22”), 

and (iii) someone whose long distance service was changed without their authorization (“Q28”). In equation (2), the 

likelihood of being satisfied with the results of complaining is significantly higher for victims of Q28 than for the control 

group. In both equations, no one who purchased a business opportunity that involved false earnings claims or false 

promises of assistance (“Q35”) or (ii) who was promised a government job (“Q38”) was satisfied with the results of 

their complaints. Therefore, these observations were not used in estimating the equation. 

b Includes the effect of type of fraud variables.
Consumer Fraud in the United States: An FTC Survey

108

The probit equations, which control for the effect of other characteristics, 

provide somewhat similar results. Again, we find statistically significant 

differences in the level of satisfaction depending on the entity to whom the 

consumer complained.222 Complaints to a seller or manufacturer yielded 

the lowest level of satisfaction.223 Unlike the cross-tab results, however, 

the regression results show no significant difference in satisfaction between 

complaining to a bank or credit card company and complaining to an official 

source.

Amount Lost

Not surprisingly, the percentage of consumers who are satisfied with the 

outcome of their complaints declines as the amount of money they lost increases. 

For consumers who lost no money as a result of the transaction at issue, just 

over 75 percent indicated they were satisfied, as shown in Panel B of Table 5-

9. In cases involving a loss of $100 or more, however, less than 30 percent 

of consumers who complained stated they were satisfied. This difference is 

statistically significant.224 The probit results provide a very similar picture 

– consumers who lost no money were almost 2.5 times as likely to be satisfied as 

those who lost $100 or more.

Internet Usage, Education, Marital Status, Gender, and Age

We find no statistically significant relationships between complaint 

satisfaction and Internet usage, education, marital status, or age, in either the 

cross-tab or regression analyses.225 Nor do we find any difference in satisfaction 

levels between men and women in the cross-tab analysis, as shown in Panel 

E of Table 5-9. In the probit equations in Table 5-10, the conditional-meanimputation results suggest that women are more likely than men to be satisfied 

with complaint outcomes and that the difference is statistically significant at the 

10 percent level. However, there is no such significant difference in the completecase regression, and we put more weight on the significance tests from that 

equation because of the tendency of the conditional-mean-imputation technique to 

overstate significance levels.

222. In both equations, the variables indicating to whom the consumer complained are jointly significant 

at the 1 percent level.

223. The differences in the level of satisfaction when a consumer complained to a seller or producer 

and when the consumer complained to either an official source or to a bank or credit card company are 

statistically significant at the 5 percent level or better.

224. Jointly, the relationship between the amount lost variables and satisfaction is significant at the 

1 percent level. In addition, for each of the three positive levels of loss, the degree of satisfaction is 

significantly lower than when no money was lost.

225. The simple cross-tab results are found in Panels C, D, F, and G of Table 5-9. 
Chapter 5: Who Complains?

109

Income

As shown in Panel H of Table 5-9, the cross-tab analysis of the relationship 

between complaint satisfaction and consumers’ income level suggests that those 

with incomes between $20,000 and $40,000 are the least likely to be satisfied. 

The difference in satisfaction between those with incomes between $20,000 and 

$40,000 and those with incomes of $40,000 to $60,000 is statistically significant 

at the 5 percent level. However, the relationship between consumers’ incomes 

and the level of satisfaction is not jointly significant in the cross-tab analysis.

The probit results in Table 5-10 show very different pictures of the 

relationship between income and complaint satisfaction, depending on which 

estimation technique is used. The complete-case results seem to suggest that 

income has a significant effect on complaint satisfaction. However, there is 

no consistent pattern to the relationship. Although the level of satisfaction of 

consumers with incomes in the $20,000 to $40,000 range is lower than for those 

in the $40,000 to $60,000 range, we find the lowest levels of satisfaction among 

those with higher levels of income. In particular, those with incomes of $80,000 

to $100,000 have the lowest rates of satisfaction – 45 percentage points lower 

than the rate for consumers with incomes of $40,000 to $60,000.

On the other hand, the results with conditional mean imputation seem to 

provide a more consistent pattern of declining satisfaction as income rises. 

Consumers with incomes under $20,000 are the most likely to be satisfied, and 

those with incomes over $100,000 are the least likely. The income variables, 

however, are not jointly or individually significant in this equation.

Race and Ethnicity

Our cross-tab analysis, set forth in Panel I of Table 5-9, shows that African 

Americans and American Indians or Alaska Natives are less likely to be satisfied 

with the outcome of their complaints than non-Hispanic whites. The difference 

is particularly striking for American Indians or Alaska Natives. The difference 

in the rate of satisfaction between American Indians or Alaska Natives and nonHispanic whites is 36 percentage points – 27.3 percent v. 63.0 percent. That 

is, non-Hispanic whites are twice as likely to be satisfied as American Indians 

or Alaska Natives.226 Once we control for other factors, the difference in 

satisfaction levels for American Indians or Alaska Natives and non-Hispanic 

whites falls to 23 percentage points – the level for American Indians or Alaska 

Natives is about 60 percent of that for non-Hispanic whites.227

226. The difference in satisfaction level between American Indians or Alaska Natives and non-Hispanic 

whites is significant at the 5 percent level in the simple analysis, although the number of observations for 

American Indians or Alaska Natives is small. Overall, the relationship between the level of satisfaction and 

the race and ethnicity is significant at the 10 percent level.

227. In the regression results, the difference in satisfaction levels between American Indians or Alaska 

Natives and non-Hispanic whites is significant at the 10 percent level in the conditional-mean-imputation 

case. It is not significant in the complete-case regression. In neither regression are the race and ethnicity 

variables jointly significant.
Consumer Fraud in the United States: An FTC Survey

110

Figure 5-7

Complaint Satisfaction

By Payment Mechanism

33.3%

50.0%

40.0% 41.7%

28.0%

62.6%

49.4%

0%

20%

40%

60%

80%

100%

Check Credit Card Cash Online

Payment

System

Seller Took

Money From

Checking

Account

Charged

Telephone Bill

Money Order

Source: Table 5-9

Satisfaction levels differ less between African Americans and non-Hispanic 

whites. As shown in Table 5-9, satisfaction levels between these groups differ 

by just over 14 percentage points, and the difference is statistically significant at 

the 10 percent level. Once we control for other factors in the regression analysis, 

the difference falls to 3 to 6 percentage points – and the differences are not 

statistically significant.

The percentage of Hispanics who indicated that they were satisfied with the 

outcome of their complaints was about 6 percentage points lower than the level 

for non-Hispanic whites, using the simple analysis. The probit analyses yield 

similar results – 1.5 percentage points lower in the conditional-mean-imputation 

results and 6 percentage points lower in the complete case analysis. None of these 

differences is statistically significant. In the cross-tab analysis, the satisfaction 

level for those in the “Other” group was less than 1 percent lower than that for 

non-Hispanic whites. In the regression results, the differences are somewhat 

higher, but are not statistically significant.

Payment Mechanism

Satisfaction 

levels also vary 

depending on the 

payment mechanism 

used. This finding 

is consistent with 

what we would 

have expected. The 

cross-tab results in 

Panel J of Table 5-9 

and Figure 5-7 show 

that consumers 

who paid with cash 

and money orders 

reported the lowest satisfaction levels, whereas consumers who paid with a credit 

card reported the highest satisfaction levels.228 The regression analysis provides a 

similar pattern of results with satisfaction rates lowest when cash is the payment 

mechanism and much higher when a credit card is used.229 The differences 

in satisfaction are not significant if we compare any of the other payment 

mechanisms to cash.

228. Jointly, the method of payment variables are statistically significant at the 5 percent level in 

the cross-tab analysis. (In performing this test, it was necessary to leave out the observations involving 

payment by an online payment service, because there were too few observations to satisfy the conditions for 

conducting a Chi-square test.) The level of satisfaction is significantly higher where credit cards and checks 

are the payment mechanism than with cash, at the 1 percent and 10 percent levels respectively. The level of 

satisfaction is also significantly higher, at the 5 percent level, where a credit card was the means of payment 

than where a money order was used.

229. The level of satisfaction when using a credit card is significantly greater than when paying with cash 

at the 5 percent level. 
Chapter 5: Who Complains?

111

Conclusion

Approximately 30 percent of consumers who have experienced one of the 

types of fraud examined in this study or slamming did not file a complaint about 

their experience. Just over 50 percent of consumers complained to the seller 

or manufacturer. Only 8 percent complained to an official source such as a 

governmental agency or the Better Business Bureau.

Women are about 10 percentage points more likely to complain than men. In 

addition, younger consumers are more likely to complain than older consumers. 

Rates of complaining are lowest for consumers between 55 and 64 years of age.

Finally, we examined the extent to which consumers who complained 

were satisfied with the outcome of their complaints. We find that those who 

complained to a bank or credit card company were more likely to be satisfied than 

those who complained to a seller or manufacturer. Similarly, consumers who 

ultimately did not lose money or who lost only a small amount were more likely 

to be satisfied than those who suffered larger losses.
Consumer Fraud in the United States: An FTC Survey

112

Table 5-11: Marginal Effects by Fraud Type, Conditional-Mean-Imputation Probit Equationsa

Table 5-4

Likelihood 

of Filing a 

Complaint, 

Complaints Filed 

with Anyone

Table 5-5

Likelihood 

of Filing a 

Complaint, 

Complaints Filed 

with Official 

Sources

Table 5-6

Likelihood 

of Filing a 

Complaint, 

Complaints Filed 

with Seller or 

Manufacturer

Table 5-7

Likelihood 

of Filing a 

Complaint, 

Complaints Filed 

with a Bank 

or Credit Card 

Company

Table 5-10

Satisfaction 

with Results of 

Complaining

Specific Types of Fraud Included in SurveyPurchased credit repair 0.1853 * 0.1928 ** 0.0719 0.0073 0.1960Purchased credit card insurance -0.0435 0.0177 -0.1598 * 0.0154 0.2457 *Billed for Internet services you did not agree to purchase 0.3682 *** -0.0055 0.2616 *** 0.1599 ** 0.2496 **Billed for information services provided either over the Internet or by pay-per-call that you had not agreed to purchase

0.2632 ** -0.0113 0.2178 * 0.0399 0.0459

Billed for buyers’ club memberships you did not agree to purchase

0.2419 *** 0.0062 0.2089 *** 0.0381 0.1660

Purchased a membership in a pyramid scheme -0.2719 ** -0.0047 -0.2435 ** -0.1324 0.1207Purchased a business opportunity where promised earnings were not realized or promised assistance was not provided

-0.0557

___

0.0174

___ ___

Made a payment to someone who represented that you would receive a government job

-0.1048

___

0.0015

___ ___

Paid money or made a purchase to receive a promised prize and did not receive the prize or the prize was not as promised

-0.1477 0.0778 -0.0528

___

-0.3161

More General Types of Frauds Included in SurveyBilled for a product or service you did not agree to purchase or billed an amount significantly more than you expected, products other than those identified above

0.3272 *** 0.0060 0.2512 *** 0.1009 * 0.1835 * 

Paid for a product but did not receive it 0.2977 ** 0.1225 * 0.2719 ** -0.0958 -0.0439Unauthorized Change in Long Distance Service 0.2770 *** 0.0135 0.3992 *** -0.1003 ** 0.2992 ***Chi-square for Joint Significance 87.95 *** 12.43 85.18 *** 33.90 *** 22.01 ***
Chapter 5: Who Complains?

113

Note. *** significant at 1 percent level ** significant at 5 percent level * significant at 10 percent level ns not significantly different from zero in joint testa Marginal effects relative to paid an advance fee to obtain a loan or credit card that you were promised or guaranteed you would receive (“Advance Fee Loans”). After controlling for all other variables included in the regression, predicted complaint rates for advance fee loans are 0.4870 for complaints to any source, 0.0657 for complaints to official sources, 0.3408 for complaints to sellers or manufacturers, and 0.1692 for complaints to a bank or credit card company. Of those who complained about an advance fee loan, predicted satisfaction rate is 0.3939 after controlling for other variables.
Consumer Fraud in the United States: An FTC Survey

114
Chapter 6: Conclusion

115

Chapter 6: Conclusion

This study provides the first systematic look in the last decade at the problem 

of consumer fraud. We examine both the extent of this problem and the degree to 

which certain groups of consumers may be more or less likely to become victims 

of fraud. Finally, we analyze the actions consumers take when they experience 

what appears to be a fraud: Do they complain to anyone? If so, to whom do they 

complain, and how satisfied are they with the results?

The underlying data for this report is drawn from an FTC-commissioned 

survey that was conducted in 2003. The survey asked consumers whether they 

had been a victim of any of ten specific types of fraud in the previous twelve 

months. In addition, consumers were asked about experiences with two more 

general types of fraud and whether their long distance telephone service had been 

changed without their authorization.

Based on the survey results, we estimate that in the year prior to the survey 

24.45 million adults in the United States – 11.2 percent of U.S. adults – were 

victims of one or more of the types of fraud we studied. We also estimate that 

there were 35.45 million incidents of these frauds during the year. The most 

common fraud – affecting 4.55 million consumers and occurring 6.55 million 

times – was the advance payment of money for a promised or guaranteed loan or 

credit card which the consumer never received. The second most common fraud 

was the unauthorized billing for a membership in a buyers’ club that the consumer 

had not agreed to purchase. An estimated 4.05 million consumers were victims of 

this fraud and an estimated 4.80 million incidents of this type of fraud occurred in 

the year before the survey. 

We also find that an estimated 13.90 million adults were “slammed” – that 

is, their long distance telephone service was changed without their authorization. 

Slamming occurred an estimated total of 17.60 million times during the year. 

In total, 35.60 million consumers – 16.3 percent of the adult population 

– encountered at least one type of fraud and/or slamming in the year preceding the 

survey.

One-third of fraud victims surveyed said that they first learned of the 

fraudulent offer through print advertising such as newspaper and magazine 

advertising, direct mail advertising and catalogs, and posters. Telemarketing was 

the second most frequently cited source, accounting for about one in six frauds, 

or 17 percent. The Internet and email were the next most common source at 14 

percent.

The likelihood of being a victim of one of the types of fraud investigated in 

this study varies with the consumer’s demographic characteristics. In particular, 

we find that members of several racial and ethnic minorities are more likely to be 

victims than are non-Hispanic whites. Even for non-Hispanic whites the risk is by 
Consumer Fraud in the United States: An FTC Survey

116

no means trivial. Of non-Hispanic whites, 6.4 percent had been a victim of one 

or more of the frauds covered by the survey during the last year. When we add 

slamming to the analysis, 12.5 percent of non-Hispanic whites had been a victim.

Our results suggest that American Indians or Alaska Natives faced the 

greatest risk. Almost 34 percent of the American Indians or Alaska Natives who 

participated in the survey had been a victim of one or more of the frauds covered 

by the survey in the last year; including slamming, 38 percent had been a victim.

Hispanics and African Americans are also significantly more likely to have 

been victims than were non-Hispanic whites. During the year prior to the survey, 

14.3 percent of Hispanics and 17.1 percent of African Americans had been victims 

of one or more of the frauds we examined. If we include slamming, 26.7 percent 

of Hispanics and 24.1 percent of African Americans were victims. On the other 

hand, members of the “Other” racial and ethnic category – which included Asians, 

Hawaiian and Other Pacific Islanders, and those who identified themselves as 

belonging to more than one racial group – were not significantly more likely 

to be victims than non-Hispanic whites. Including both fraud and slamming, 

11.7 percent of this group were victims; focusing only on fraud, the rate was 7.3 

percent.

The likelihood of being a victim also varied depending on how consumers 

expected their income to change in the next three years, and how comfortable 

they were with their current level of debt. Participants who expected their 

incomes to remain largely unchanged over the next three years and those who had 

no debt were the least likely to be victims – five percent of those who said that 

their incomes would remain steady and 2.7 percent of those with no debt were 

victims of one or more of the frauds we examined. Participants who anticipated 

a large increase or decrease in their incomes in the next three years were much 

more likely to have been a victim, with more than 10 percent of these consumers 

reporting they had been a victim. Participants who felt they had more debt than 

they could comfortably handle were even more likely to be victims, with 19.2 

percent of this group indicating that they had been a victim of fraud.

One group that we anticipated might be at greater risk of being a victim was 

older Americans. However, we find that consumers aged 65 or older did not face 

any greater risk than younger consumers. When we look simply at the percentage 

of consumers in various age groups who were victims of fraud, we find that those 

who are 55 or over were significantly less likely to be a victim than those who are 

younger. Once we control for other factors that we expect to affect the likelihood 

that a consumer will be a victim, we find that the risk of being a victim of fraud 

did not vary with age.
Chapter 6: Conclusion

117

Issues for Future Studies

As with any study, there are areas that could be improved. One area for 

improvement is the estimation of total dollars lost as a result of fraud. For several 

reasons, we concluded that we could not develop reliable estimates of total dollar 

losses in this survey. Instead, we limited ourselves to providing median estimates 

of the costs associated with each of the ten specific types of fraud.

The primary problem we faced in estimating total costs was that the monetary 

losses reported by a handful of victims accounted for a very high proportion of 

the apparent total losses suffered by survey participants. Specifically, the losses 

reported by six individuals accounted for almost half of the total losses reported 

by 320 fraud victims. Given the relative magnitude of these six loss figures, and 

evidence we had of potential problems with some of those figures, we opted not 

to use these figures unless we could verify them. Verification proved infeasible, 

however. In any future survey work, it would be useful to include checks within 

the survey instrument to verify any values that seem unusually large. 

Another problem with estimating total losses stemmed from the fact that the 

survey only asked victims how much they had paid as a result of each fraudulent 

transaction and how much they had lost. In some instances, participants indicated 

that they had lost more than they had paid. It is not clear what such responses 

mean. In any future survey, it might be worthwhile to craft the questions more 

carefully to ensure that the responses provide exactly the information that the 

researchers hope to obtain. It may also be useful to ask participants to verify their 

responses if the amount lost appears to be greater than the amount paid.

A final problem arose in cases where the survey participant had used a 

credit card to pay for a transaction that turned out to be fraudulent. The survey 

asked consumers how much they paid as a result of the fraudulent transaction. 

However, consumers who charge an item on a credit card and later dispute that 

charge with their credit card company may not ultimately pay for the transaction 

at all. In such instances, it is not clear how the consumer answered the survey 

question about how much money they paid. Some consumers may have reported 

the amount that appeared on their credit card statement, while others may have 

reported that they did not pay anything because they never actually paid that 

amount. In any future study, it would be useful to be clear about how such 

transactions should be reported.

Another area for improvement in future studies involves the question about 

how consumers learned about the fraud to which they fell victim. Our survey 

directed the person conducting the survey to read a list of possible sources of 

initial contact including “through an Internet auction site,” “from an Internet 

web site, other than an auction site,” “from an email,” “from a telemarketer,” and 

“from a television advertisement or infomercial.”230 With one exception, the list 

230. Survey question 62.
Consumer Fraud in the United States: An FTC Survey

118

was to be read in random order until the participant indicated that a particular 

response was how he or she learned about the fraud.

The exception was that “through an Internet web site, other than an auction 

site” always followed “from an Internet auction site.” We adopted this rule 

because we were concerned that participants might not correctly distinguish 

between Internet auction sites and other Internet web sites unless we asked the 

questions in that order. However, the survey responses suggest that the opposite 

problem occurred in some instances – that is, that some consumers heard the word 

“Internet” in “from an Internet auction site” and answered in the affirmative even 

if it was a non-auction site.

To avoid this problem in future surveys, we recommend that the questions 

not initially attempt to differentiate between auction and non-auction sites, but 

instead include only “from the Internet” as an initial option. If participants select 

this option, a follow-up question could then ask whether this was from an Internet 

auction site, a non-auction site, or an email.

Finally, our results show the importance of asking specific questions about 

different types of fraud. Consumers are unlikely to provide a full picture of their 

experiences with fraud if they are asked only general questions about whether 

they have been a victim. On the other hand, to obtain reliable figures on the 

extent of fraud from specific questions, it is important to ask questions that cover 

the spectrum of the types of fraud of interest. The responses to our open-ended 

questions indicated some types of fraud that were not covered by our closedended questions – in particular, problems with solicitations by bogus charities. 

Furthermore, the questions should be sufficiently specific to enable researchers 

to differentiate between the types of fraud being studied and other incidents that 

survey participants may believe constitute fraud.

Implementing all of our suggestions into a single future survey is likely to be 

difficult. In addition, administering such a comprehensive survey may take more 

time than consumers are generally willing to give. Thus, rather than attempting 

to obtain an overall picture of the problem of consumer fraud, the better approach 

for future studies may be to focus on a subset of types of frauds. This approach 

would permit more detailed questions without rendering the survey so long that 

consumers will be unwilling to complete it.
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 1 May 20, 2003 (12:05pm)

FTC NATIONAL SURVEY

DRAFT 4c

Project # 03151 May 20 - June 3, 2003

Public Opinion Strategies N= 2,500 Adults

Alexandria, Virginia Margin of Error = ± 2.0%

Hello, Im ____________________ of _______________, a national research firm. Were talking with

people around the country today, and would like to ask you a few questions on a confidential basis. We

are not calling to sell anything nor will this call result in any future sales calls. We are simply speaking to

people for research purposes only.

A. First, are you at least 18 years of age or older?

1 YES (CONTINUE TO QUESTION 1)

IF NO THEN ASK: May I please speak to someone in your household who is 18 years of age or

older?

(REPEAT QUESTION A WITH NEW RESPONDENT)

The first few questions are about some experiences you personally might have as a consumer...

1. Have you, yourself, received a telemarketing phone call in the past year?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 2 May 20, 2003 (12:05pm)

Now, please tell me whether, yes or no, you have done any of the following in the past YEAR.

In the past YEAR have you...(RANDOMIZE AND INSERT Q2-Q6 STATEMENTS)

YES YES YES YES YES YES YES (DNR)

NO ONCE TWICE THREE FOUR FIVE ETC. DK DK/REF

0 1 2 3 4 5 ETC. 998 999

(IF YES, ASK:) And how many such (purchases/contributions) would you estimate that you have made

in the last year? (RECORD EXACT NUMBER)

(IF Q1:1, ASK Q2) 

2. Purchased something in response to a telemarketing call from a company with whom you have

not previously done business

(IF Q1:1, ASK Q3)

3. Contributed to a charity to which you have not previously donated in response to a telemarketing

call.

4. Purchased something from an internet web site

5. Placed an order for a product by phone, internet, or mail after seeing a television advertisement or

infomercial

6. Placed an order for a product by phone, internet, or mail after receiving an unsolicited piece of

mail from a company with whom you have not previously done business
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 3 May 20, 2003 (12:05pm)

Talking some more about the internet...

7. Whether or not you use the internet, how likely do you think it would be that your credit card

information would be stolen and misused if you used your credit card to purchase something on

the Internet or World Wide Web (ROTATE TOP TO BOTTOM, BOTTOM TO TOP)  very

likely, somewhat likely, not very likely, or not likely at all?

1 VERY LIKELY

2 SOMEWHAT LIKELY

3 NOT VERY LIKELY

4 NOT LIKELY AT ALL

5 DONT KNOW/REFUSED (DO NOT READ)

Now, moving on...

8. In general, thinking about how your close friends or family would be most likely to describe the

way you deal with people you do NOT know, would they be more likely to describe you as

being... (ROTATE PUNCHES 1-2)

1 Trusting and Friendly

...or...

2 Cautious and Suspicious

3 BOTH (DO NOT READ)

4 NEITHER (DO NOT READ)

5 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 4 May 20, 2003 (12:05pm)

9. Now, thinking about YOUR experiences as a consumer, was there ever a time you felt you were

the subject of a consumer fraud?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q9:1, ASK)

10. When was the last time this happened? (DO NOT READ LIST, OPEN-END PRE-CODE)

1 During the past year

2 One to two years ago

3 Two to three years ago

4 Three to five years ago

5 More than five years ago

6 DONT KNOW/REFUSED

(IF Q9:1, ASK)

(ASK SAMPLE A)

11. Can you BRIEFLY tell me what kind of fraud it was? And can you tell me anything else you can

think of that is important about that experience?

RECORD RESPONSE VERBATIM
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 5 May 20, 2003 (12:05pm)

(ASK SAMPLE A)

12. Now if you learned there was a federal government web site or a toll free number that provides

consumers with information on how to recognize and avoid fraudulent or deceptive offers and

how to avoid becoming a victim of identity theft...How likely would you be to visit this web site

or call the toll free number? Would you be...(ROTATE TOP TO BOTTOM, BOTTOM TO

TOP)

1 VERY LIKELY 

2 SOMEWHAT LIKELY 

 3 NOT TOO LIKELY

4 NOT LIKELY AT ALL

...to visit this website or call the toll free number?

5 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 6 May 20, 2003 (12:05pm)

Now we would like to ask you about some types of fraud that happen to consumers. Since there are a lot

of ways in which a consumer might be cheated or be a victim of fraud, I am going to read you

descriptions of some ways in which consumers are sometimes cheated or become victims of fraud. Please

tell me which of these things, if any, have happened to YOU in the past YEAR.

(RANDOMIZE AS BLOCKS: Q13-Q17, Q18-Q30, Q31-Q38, AND Q39-Q44)

In the past YEAR, have you paid money to anyone who promised or

guaranteed...(RANDOMIZE)

(IF YES, ASK:) How many times has this happened to you in the past year?

YES YES YES YES YES (DNR)

ONCE TWICE THREE FOUR+ DK NO DK/REF

1 2 3 4 5 6 7

13. To remove negative, but true, information from your credit record, but failed to get the

information removed 

14. To provide information to help you create a new identity or new credit record 

15. To provide insurance to protect you against the unauthorized use of your credit cards 

16. To provide you with a credit card or loan, other than a mortgage loan, but required you pay a fee

before receiving the credit card or loan 

(IF Q16:1-5, ASK Q17 BEFORE CONTINUING WITH REST OF SERIES)

(IF Q16:1-5, ASK)

(IF Q16:2-5, READ:) Thinking now about the most recent time this happened to you...

17. Did you actually receive the promised loan or credit card?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 7 May 20, 2003 (12:05pm)

(RANDOMIZE AS BLOCKS: Q13-Q17, Q18-Q30, Q31-Q38, AND Q39-Q44)

18. In the past year, have you been billed for a product or service which you did not agree to

purchase or were you billed for an amount that was substantially more than you expected to pay? 

1 YES

2 NO (SKIP TO Q26)

3 DONT KNOW/REFUSED (DO NOT READ)(SKIP TO Q26)

(IF Q18:1, ASK Q19-Q22)

Did you have this experience while purchasing...(RANDOMIZE Q19-Q22)

(IF YES, ASK:) How many times has this happened to you in the past year?

(WHEN RETURNING TO Q19-Q22 FROM Q23-Q27 PROMPT: Thinking again about

being billed for a product or service which you did not agree to purchase or being billed for an

amount that was substantially more than you expected to pay...)

YES YES YES YES YES (DNR)

ONCE TWICE THREE FOUR+ DK NO DK/REF

1 2 3 4 5 6 7

19. Internet-related services, such as internet access or a web-site (IF Q19:1-5 ASK Q26 & Q27

BEFORE CONTINUING WITH REST OF SERIES)

20. 900 number pay per call or internet information services, such as adult entertainment, gambling

or psychic services (IF Q20:1-5 ASK Q26 & Q27 AFTER BEFORE CONTINUING WITH

REST OF SERIES)

21. A publication or membership in a club that the seller told you would allow you to purchase

something for a lower price than is generally available 

(IF Q21:1-5, ASK Q24-Q27 BEFORE CONTINUING WITH REST OF SERIES)

(ALWAYS ASK LAST)

22. Some other product or service
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 8 May 20, 2003 (12:05pm)

(IF Q22:1-5, ASK:)

(IF Q22:2-5, READ:) Thinking now about the most recent time this happened to you...

23. What was the product or service?

RECORD VERBATIM RESPONSES

(IF Q21:1-5, ASK)

(IF Q21:2-5, READ) Thinking now about the most recent time this happened to you...

24. Did the membership or the information in the publication enable you to purchase something for a

lower price as you had been promised?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q21:1-5, ASK)

25. And what kinds of products were you supposed to be able to purchase at a reduced price?

(DO NOT READ)(OPEN-END PRE-CODE)

1 Automobiles that had been seized by the government or had been repossessed.

2 Houses where the owner had fallen behind on their mortgage payments and the mortgage

holder had foreclosed

3 Travel services

4 Medical goods and services, such as dental care, eye care, or prescription drugs

5 Entertainment, such as restaurant meals or movie tickets

6 General Merchandise, like food or household products

7 OTHER (SPECIFY) ____________________

8 Dont know/refused
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 9 May 20, 2003 (12:05pm)

(IF Q19:1-5, Q20:1-5, Q21:1-5 OR Q22:1-5, ASK)

(IF Q19:2-5 OR Q20:2-5, READ:) Thinking now about the most recent time this happened to you...

26. Did you try to get the seller to give you a refund or otherwise make an adjustment?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q26:1, ASK)

27. And was the seller willing to provide a refund, or otherwise make an adjustment that satisfied

you?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 10 May 20, 2003 (12:05pm)

28. And in the past year, has your long distance telephone service been switched to another company

without your knowledge or consent?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q28:1, ASK:)

29. How many times has this happened to you in the past year?

1 ONCE

2 TWICE

3 THREE TIMES

4 FOUR OR MORE TIMES

5 DONT KNOW/REFUSED (DO NOT READ)

(IF Q28:1, ASK:)

(IF Q29:2-5, READ:) Thinking now about the most recent time this happened to you...

30. Was the first time you found out about this when you received a bill?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 11 May 20, 2003 (12:05pm)

(RANDOMIZE AS BLOCKS: Q13-Q17, Q18-Q30, Q31-Q38, AND Q39-Q44)

In the past year, have you paid anyone...(RANDOMIZE)

(IF YES, ASK:) How many times has this happened to you in the past year?

YES YES YES YES YES (DNR)

ONCE TWICE THREE FOUR+ DK NO DK/REF

1 2 3 4 5 6 7

31. For an opportunity to operate your own business, such as a work-at-home plan, a business

opportunity or a franchise?

(IF Q31:1-5, ASK Q33-Q37 BEFORE CONTINUING WITH REST OF SERIES)

32. Who promised that you would obtain a job at the U.S. Postal Service or another branch of state or

federal government?

(IF Q32:1-5, ASK Q38 BEFORE CONTINUING WITH SERIES)

(IF Q31:1-5, ASK)

(IF Q31:2-5, READ:) Thinking now about the most recent time this happened to you...

33. Were you led to believe that most of the money you earned from this business would be from

recruiting others to join the business, rather than from the sale of products?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q31:1-5, ASK)

34. And was the business to be operated out of your home?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 12 May 20, 2003 (12:05pm)

(IF Q31:1-5, ASK)

35. Were you led to believe that you would earn a certain amount of income or profit from this

business? 

(IF YES ASK:) Did you earn at least roughly as much money as you had been led to expect?

1 YES - Promised level of earnings was realized

2 YES - Promised level of earnings was NOT realized

3 NO

4 DONT KNOW/REFUSED (DO NOT READ)

(IF Q31:1-5, ASK)

36. Were you promised help in locating customers who would use your services or allow you to sell

your products from their premises? 

(IF YES ASK:) Did you obtain the promised assistance?

1 YES - Promised assistance was provided

2 YES - Promised assistance was NOT provided

3 NO

4 DONT KNOW/REFUSED (DO NOT READ)

(IF Q35:2 OR Q36:2, ASK:)

37. And how many months ago did you purchase this business?

__________________ RECORD NUMBER OF MONTHS

(IF Q32:1-5, ASK)

(IF Q32:2-5, READ:) Thinking now about the most recent time this happened to you...

38. Did you get the job that was promised?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 13 May 20, 2003 (12:05pm)

(RANDOMIZE AS BLOCKS: Q13-Q17, Q18-Q30, Q31-Q38, AND Q39-Q44)

39. In the past year, has anyone told you that you had won a prize or been selected to receive an

award such as money, a free vacation, or other product or service?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q39:1, ASK:)

40. Were you told that you had to pay something, purchase a good or service, or attend a sales

presentation in order to receive your prize or award?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q40:1, ASK:)

41. Did you make the required payment or purchase or did you attend the required sales presentation?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q41:1, ASK:)

42. How many times has this happened to you in the past year?

1 ONCE

2 TWICE

3 THREE TIMES

4 FOUR OR MORE TIMES

5 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 14 May 20, 2003 (12:05pm)

(IF Q41:1, ASK)

(IF Q42:2-5, READ:) Thinking now about the most recent time this happened to you...

43. Did you ever receive the prize or award?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q43:1, ASK)

44. And was the prize or award essentially what had been described to you? 

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 15 May 20, 2003 (12:05pm)

(ROTATE AS A BLOCK Q45-Q49 WITH Q50-Q55)

45. Other than the things we have already discussed, in the past year have you purchased something

which you paid for but NEVER received?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q45:1, ASK:)

46. How many times has this happened to you in the past year?

1 ONCE

2 TWICE

3 THREE TIMES

4 FOUR OR MORE TIMES

5 DONT KNOW/REFUSED (DO NOT READ)

(IF Q45:1, ASK)

(IF Q46:2-5, READ:) Thinking now about the most recent time this happened to you...

47. Did you try to get the seller to give you a refund or otherwise make an adjustment?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q47:1, ASK)

48. And was the seller willing to provide a refund or otherwise make an adjustment that satisfied

you?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 16 May 20, 2003 (12:05pm)

(IF Q45:1, ASK:)

49. What was the item that you purchased? (DO NOT READ LIST)(OPEN-END PRE-CODE)

1 Business opportunities / franchises / distributorships / work-at-home plans

2 Buyers clubs

3 Cameras (including digital cameras and camcorders)

4 CDs / video tapes / DVDs

5 Computers: equipment or software

6 Health care products and services

7 Information such as psychic or adult entertainment services delivered over the internet

8 Internet access services

9 Internet web site design / advertising on the internet

10 Investments

11 Magazines

12 Office supplies

13 Pay-per-call and information services such as adult entertainment, gambling or psychic

services delivered over the telephone or internet

14 Real estate (including timeshares)

15 Travel services / vacations

16 Other (SPECIFY) _______________________

17 DONT KNOW/REFUSED
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 17 May 20, 2003 (12:05pm)

(ROTATE AS A BLOCK Q45-Q49 WITH Q50-Q55)

50. Other than the things we have already discussed, in the past year have you purchased something

where the item you received turned out to be of substantially lower quality than what was

originally represented to you? 

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q50:1, ASK:)

51. How many times has this happened to you in the past year?

1 ONCE

2 TWICE

3 THREE TIMES

4 FOUR OR MORE TIMES

5 DONT KNOW/REFUSED (DO NOT READ)

(IF Q50:1, ASK:)

(IF Q51:2-5, READ:) Thinking now about the most recent time this happened to you...

52. Did you try to return the item or seek to get the seller to make some other kind of an adjustment?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q52:1, ASK)

53. And was the seller willing to take the item back or otherwise make an adjustment that satisfied

you? 

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 18 May 20, 2003 (12:05pm)

(IF Q50:1, ASK)

54. What was the item that you purchased? (DO NOT READ LIST) (OPEN-END PRE-CODE)

1 Business opportunities / franchises / distributorships / work-at-home plans

2 Buyers clubs

3 Cameras (including digital cameras and camcorders)

4 CDs / video tapes / DVDs

5 Computers: equipment or software

6 Health care products and services

7 Information such as psychic or adult entertainment services delivered over the internet

8 Internet access services

9 Internet web site design / advertising on the internet

10 Investments

11 Magazines

12 Office supplies

13 Pay-per-call and information services such as adult entertainment, gambling or psychic

services delivered over the telephone or internet

14 Real estate (including timeshares)

15 Travel services / vacations

16 Other (SPECIFY) _______________________

17 DONT KNOW/REFUSED

(IF Q54:1-16, ASK)

55. Could you please briefly describe how the item differed from what you expected?

RECORD RESPONSE VERBATIM
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 19 May 20, 2003 (12:05pm)

56. In the past year, has anyone misused your credit card or credit card number to place charges on

your account without your permission?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

57. In the past year, has anyone misused any of your existing accounts other than a credit card

account  for example, a bank or wireless telephone account  without your permission to run up

charges or to take money from your accounts?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

58. In the past year, have you been the victim of an Identity Theft that involved more than just the

misuse of existing accounts or numbers? That is, has anyone used your personal information

without your permission to obtain new credit cards or loans in your name, to run up debts in your

name, open other accounts, or otherwise commit theft, fraud, or some other crime?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 20 May 20, 2003 (12:05pm)

59. Now, weve been talking about some SPECIFIC ways in which you might have been cheated or

defrauded in the last year. Now Id like to know if there were any other occasions in the past year

that you felt a person or company cheated you out of money or property?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q59:1, ASK:)

60. How many times has this happened to you in the past year?

1 ONCE

2 TWICE

3 THREE TIMES

4 FOUR OR MORE TIMES

5 DONT KNOW/REFUSED (DO NOT READ)

(IF Q59:1, ASK)

(IF Q60:2-5, READ:) Thinking now about the most recent time this happened to you...

61. Can you briefly tell me what happened? And can you tell me anything else you can think of that

is important about that experience? 

RECORD RESPONSE VERBATIM
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 21 May 20, 2003 (12:05pm)

GENERAL FOLLOW-UP QUESTIONS (Q62-Q70) ARE TO BE ASKED AFTER

EACH INSTANCE OF FRAUD REPORTED BY A RESPONDENT IN Q19-Q53 

(IF Q13:1-5, Q14:1-5, Q15:1-5, Q16:1-5, Q19:1-5, Q20:1-5, Q21:1-5, Q22:1-5, (Q33:1 OR Q35:2 OR

Q36:2), Q38:2, (Q43:2 OR Q44:2), Q48:2, Q53:2, ASK:)

62. How did you first learn about [Insert language describing the product or service involved in the

fraud]? (RANDOMIZE, EXCEPT PUNCH 2 MUST FOLLOW PUNCH 1)

1 through an internet auction site

2 from an internet web site, other than an auction site

3 from an email

4 from a television advertisement or infomercial

5 from a mail advertisement or solicitation, including from a catalog

6 from a telemarketer

7 from a store you visited

8 from someone who came to your home

9 from a radio advertisement

10 from a poster or flier

11 from a magazine or newspaper advertisement

12 when you received the bill

13 other (SPECIFY) _________________

14 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 22 May 20, 2003 (12:05pm)

(IF Q13:1-5 OR Q14:1-5 OR Q15:1-5 OR Q16:1-5 OR Q19:1-5 OR Q20:1-5 OR Q21:1-5 OR

Q22:1-5 OR (Q33:1 OR Q35:2 OR Q36:2) OR Q38:2 OR Q48:2 OR Q53:2, ASK:)

(DO NOT ASK IF Q62:12)

63. And how did you purchase this product (RANDOMIZE)?

1 VISITED A STORE

2 ORDERED ON THE TELEPHONE

3 MAILED IN AN ORDER

4 ORDERED FROM INTERNET SITE

5 OTHER (SPECIFY) _________________

6 DONT KNOW/REFUSED (DO NOT READ)

(IF Q13:1-5, Q14:1-5, Q15:1-5, Q16:1-5, Q19:1-5, Q20:1-5, Q21:1-5, Q22:1-5, Q28:1, (Q33:1 OR

Q35:2 OR Q36:2), Q38:2, (Q43:2 OR Q44:2), Q48:2, Q53:2, ASK:)

64. How much money did you pay or lose as a result of the person or company who defrauded you? 

PAID _________________(RECORD EXACT AMOUNT, 9999999 FOR DK/REF)

LOST _________________(RECORD EXACT AMOUNT, 9999999 FOR DK/REF)

(IF PAID MONEY ON Q64, ASK) 

65. And how did you pay for this transaction? 

1 Credit Card

2 Cash

3 Check

4 On-line payment system like PayPal, 

5 Seller took money directly from my checking account

6 Charged to my telephone bill

7 Other SPECIFY) _________________

8 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 23 May 20, 2003 (12:05pm)

(IF Q13:1-5, Q14:1-5, Q15:1-5, Q16:1-5, Q19:1-5, Q20:1-5, Q21:1-5, Q22:1-5, Q28:1, (Q33:1 OR

Q35:2 OR Q36:2), Q38:2, (Q43:2 OR Q44:2), Q48:2, Q53:2, ASK:)

66. What actions, if any, did you take in attempting to resolve this incident?(DO NOT READ,

OPEN-END PRE-CODE) (PROBE FOR MULTIPLE RESPONSES by following up with

Anything else?)

1 Did nothing

2 Asked for a refund or replacement

3 Stopped payment or refused to pay

4 Stopped buying from the company

5 Consulted a lawyer or other professional

6 Complained to family or friends / told family or friends not to buy from the seller

7 Complained to salesperson, manager or owner of the company that sold the product

8 Complained to the product manufacturer

9 Complained to the Better Business Bureau

10 Complained to a bank

11 Complained to a credit card company

12 Complained to a local consumer agency

13 Complained to the local police department

14 Complained to the Department of Motor Vehicles

15 Complained to a local consumer help line

16 Complained to the state Attorney General or state consumer agency

17 Complained to the FTC (Federal Trade Commission)

18 Complained to another federal agency (SPECIFY) ________________

19 Complained to the phone company

20 Other (SPECIFY) _________________

21 DONT KNOW/REFUSED
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 24 May 20, 2003 (12:05pm)

(IF Q66:1-6, 20-21 ONLY, ASK)

67. And, did you report your experience to anyone?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q67:1, ASK)

68. To whom did you report your experience? 

(DO NOT READ OPEN-END PRE-CODE) (PROBE FOR MULTIPLE RESPONSES by

following up with Anything else?)

6 Family or friends / tell family or friends not to buy from the seller

7 Salesperson, manager or owner of the company that sold the product

8 The product manufacturer

9 The Better Business Bureau

10 A bank

11 A credit card company

12 A local consumer agency

13 The local police department

14 The Department of Motor Vehicles

15 A local consumer help line

16 The state Attorney General or state consumer agency

17 The FTC

18 Another federal agency (SPECIFY) _________________

19 Complained to the phone company

20 Other (SPECIFY) _________________

21 DONT KNOW/REFUSED
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 25 May 20, 2003 (12:05pm)

(IF Q66:7-19 OR Q68:7-20, ASK)

69. How satisfied were you with the result of your report of your experience with (INSERT FIRST

PUNCH FROM Q66 OR Q68)?...(ROTATE TOP TO BOTTOM, BOTTOM TO TOP) 

Very Satisfied, Somewhat Satisfied, Not Too Satisfied, or Not at all satisfied?

1 VERY SATISFIED

2 SOMEWHAT SATISFIED

3 NOT TOO SATISFIED

4 NOT AT ALL SATISFIED 

5 DONT KNOW/REFUSED (DO NOT READ)

(IF MORE THAN ONE PUNCH ON Q66:7-19 OR Q68:7-20, ASK)

70. How satisfied were you with the result of your report of your experience with (INSERT

SECOND PUNCH FROM Q66 OR Q68)?...(ROTATE TOP TO BOTTOM, BOTTOM TO

TOP)  Very Satisfied, Somewhat Satisfied, Not Too Satisfied, or Not at all satisfied?

1 VERY SATISFIED

2 SOMEWHAT SATISFIED

3 NOT TOO SATISFIED

4 NOT AT ALL SATISFIED 

5 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 26 May 20, 2003 (12:05pm)

(ASK SAMPLE B)

71. Now if you learned there was a federal government web site or a toll free number that provides

consumers with information on how to recognize and avoid fraudulent or deceptive offers and

how to avoid becoming a victim of identity theft...How likely would you be to visit this web site

or call the toll free number? Would you be...(ROTATE TOP TO BOTTOM, BOTTOM TO

TOP)

1 VERY LIKELY 

2 SOMEWHAT LIKELY 

 3 NOT TOO LIKELY

4 NOT LIKELY AT ALL

...to visit this website or call the toll free number?

5 DONT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 27 May 20, 2003 (12:05pm)

Changing Topics and thinking some more about you...

72. Do you ever go online to access the Internet or World Wide Web or to send and receive e-mail?

1 YES

2 NO

3 DONT KNOW/REFUSED (DO NOT READ)

(IF Q72:1, ASK)

73. How many hours EACH WEEK in total would you say you spend on the Internet either at work

OR at home ?

RECORD EXACT NUMBER OF HOURS, ENTER 999 FOR DK/REF

And for statistical purposes only...

74. In what year were you born?

_____ _____ _____ _____ (9999 = DK/REFUSED)

75. Are you married, widowed, separated, divorced or have you never been married?

1 MARRIED

2 WIDOWED

3 SEPARATED

4 DIVORCED

5 NEVER BEEN MARRIED

6 NOT SURE/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 28 May 20, 2003 (12:05pm)

76. And what was the last grade you completed in school? (DO NOT READ CATEGORIES)

1 SOME GRADE SCHOOL (1-8)

2 SOME HIGH SCHOOL (9-11)

3 GRADUATED HIGH SCHOOL (completed 9-12)

4 TECHNICAL OR VOCATIONAL SCHOOL (12)

5 SOME COLLEGE (13-15)

6 GRADUATED COLLEGE (16)

7 GRADUATE/PROFESSIONAL SCHOOL (16+)

8 REFUSED (DO NOT READ)

77. Have you or anyone in your household served or are you or a household member currently

serving in the United States military? (DO NOT READ LIST, ACCEPT MULTIPLE

PUNCHES)

1 YES SELF CURRENTLY

2 YES HH MEMBER CURRENTLY

3 YES SELF PAST

4 YES HH MEMBER PAST

5 NO

6 DONT KNOW

7 REFUSED

78. Other than English, what other languages, if any, are spoken in your home? (DO NOT READ)

1 SPANISH

2 CHINESE/MANDARIN

3 JAPANESE

4 FRENCH

5 HINDI

6 OTHER (SPECIFY) _____________

7 DO NOT KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 29 May 20, 2003 (12:05pm)

79. And for statistical purposes only...is your total annual HOUSEHOLD income greater or less than

$60,000 dollars?

(IF LESS THAN $60,000, ASK:) Is it...

(ROTATE FROM TOP TO BOTTOM/BOTTOM TO TOP)

1 UNDER $20,000

2 BETWEEN $20,000 - $40,000

3 OVER $40,000

(IF GREATER THAN $60,000, ASK:) Is it...

(ROTATE FROM TOP TO BOTTOM/BOTTOM TO TOP)

4 UNDER $80,000

5 BETWEEN $80,000 - $100,000

6 OVER $100,000

7 REFUSED (DO NOT READ)

80. Thinking ahead to three years from now, how do you think your income will compare to your

income today? Do you think it will be (ROTATE TOP TO BOTTOM, BOTTOM TO

TOP)...?

1 MUCH LOWER

2 SLIGHTLY LOWER

3 ABOUT THE SAME

4 SLIGHTLY HIGHER

5 MUCH HIGHER

6 DON'T KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey 

FTC Qux FinalDraft4c.wpd 30 May 20, 2003 (12:05pm)

81. And thinking for a moment about your personal debt on which you currently make interest

payments. I am talking about your debts you partially pay-off each month for things like

mortgages, credit cards, personal loans or car loans. Would you say the amount of debt you

currently have is...(DO NOT ROTATE)

1 More than you can handle financially

2 About as much as you can handle financially

...or...

3 You could handle more debt than you currently have

4 Do not have any personal debt (DO NOT READ)

5 DONT KNOW/REFUSED (DO NOT READ)

82. Do you personally or jointly own any stock market investments, such as stocks, bonds, mutual

funds, or have a retirement account, such as a 401K (FOUR-O-ONE-K) or other pension plan?

1 YES

2 NO

3 DON'T KNOW/REFUSED (DO NOT READ)

83. What would be your estimate of the total value of your household's savings and investments. By

savings and investments I mean things such as savings and money market accounts, stocks,

bonds, mutual funds, government securities, CDs, bank accounts, IRAs, Keoghs, (KEY OHS)

401Ks (FOUR-O-ONE KS) and 403bs (FOUR-O-THREE-BEES). Please do NOT include in

your answer any real estate investments or company-sponsored pension plans that are fully

funded by your employer. Would you say that your total investments are...(READ LIST)

1 Zero

2 Less than $5,000

3 Between $5,000 and $25,000

4 Between $25,000 and $50,000

5 Between $50,000 and $100,000

...OR...

6 More than $100,000

7 REFUSED (DO NOT READ)

83b. Do you rent or own the home where you currently live?

1 RENT 

2 OWN

3 DON'T KNOW/REFUSED (DO NOT READ)
Appendix A: The Survey Instrument

FTC Qux FinalDraft4c.wpd 31 May 20, 2003 (12:05pm)

84. Are you of Hispanic or Latino origin

1 YES

2 NO

3 DONT KNOW/REFUSED

85. I am going to read a list of racial categories. Please choose one or more categories that best

indicates your race. Are you?

1 WHITE

2 BLACK OR AFRICAN AMERICAN

3 AMERICAN INDIAN OR ALASKA NATIVE

4 ASIAN

5 NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER

6 OTHER (DO NOT READ)

7 DONT KNOW/REFUSED (DO NOT READ)
Consumer Fraud in the United States: An FTC Survey

FTC Qux FinalDraft4c.wpd 32 May 20, 2003 (12:05pm)

86. Gender (BY OBSERVATION, BUT ASK EVERYONE) Are you employed outside of the

home, are you a homemaker, or are you retired?

(IF EMPLOYED OUTSIDE THE HOME, ASK:) And, are you paid on an hourly basis or do

you draw a yearly salary?

1 MALE/EMPLOYED/HOURLY

2 MALE/EMPLOYED/SALARY

3 MALE/HOMEMAKER

4 MALE/RETIRED

5 MALE/NOT IN LABOR FORCE

6 FEMALE/EMPLOYED/HOURLY

7 FEMALE/EMPLOYED/SALARY

8 FEMALE/HOMEMAKER

9 FEMALE/RETIRED

10 FEMALE/NOT IN LABOR FORCE

11 MALE REFUSED (DO NOT READ)

12 FEMALE REFUSED (DO NOT READ)

This survey was sponsored by the Federal Trade Commission (FTC). The FTC works for the consumer to

prevent fraudulent, deceptive and unfair business practices in the marketplace and to provide information

to help consumers spot, stop and avoid them. You can file a complaint or get free information on

consumer issues  including telemarketing, identity theft or Internet fraud -- from the FTC by visiting

WWW-DOT-FTC-DOT-GOV or calling toll-free, 1-877-FTC-HELP.

(IF Q79:7 OR Q83:7 SAY) 

Now that you know the sponsor of this survey, would you NOW be willing to answer a question or two

that you initially did not answer? (IF YES ASK Q79 OR Q83 AGAIN)

FRAUD DEFINITION

(IF Q13:1-5, Q14:1-5, Q15:1-5, Q16:1-5, Q19:1-5, Q20:1-5, Q21:1-5, Q22:1-5, Q28:1, (Q33:1 OR

Q35:2 OR Q36:2), Q38:2, (Q43:2 OR Q44:2), Q48:2, Q53:2, ASK:)