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126 Identity Theft Essay Topic Ideas & Examples

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Identity theft is a serious crime that can have devastating consequences for victims. From financial loss to damage to reputation, the effects of identity theft can be long-lasting and difficult to overcome. As such, it is important for individuals to be aware of the risks and take steps to protect themselves from becoming victims.

One way to raise awareness about identity theft is through writing essays on the topic. To help get you started, here are 126 identity theft essay topic ideas and examples that you can use as inspiration for your own writing:

• The growing problem of identity theft in the digital age
• The different types of identity theft and how they can impact victims
• The role of social media in identity theft
• Common red flags of identity theft
• How to protect yourself from identity theft online
• The importance of monitoring your credit report for signs of identity theft
• The impact of identity theft on victims' mental health
• Identity theft and its connection to cybercrime
• The legal consequences of committing identity theft
• The role of law enforcement in combating identity theft
• Identity theft and the elderly population
• The impact of identity theft on children and teens
• The relationship between identity theft and data breaches
• The role of technology in preventing identity theft
• The financial implications of identity theft
• The psychological effects of identity theft on victims
• Identity theft and its impact on small businesses
• The role of identity theft in organized crime
• The importance of reporting identity theft to the authorities
• Best practices for protecting your identity online
• The connection between identity theft and identity fraud
• Identity theft and its impact on credit scores
• The role of identity theft in identity cloning
• The impact of identity theft on victims' relationships
• The role of phishing scams in identity theft
• Identity theft and its connection to identity authentication
• The impact of identity theft on victims' employment prospects
• The importance of educating the public about identity theft
• Identity theft and its impact on victims' financial futures
• The relationship between identity theft and identity theft insurance
• Identity theft and its connection to identity protection services
• The impact of identity theft on victims' sense of security
• Identity theft and its connection to identity restoration services
• The role of credit freezes in preventing identity theft
• Identity theft and its impact on victims' ability to obtain credit
• The connection between identity theft and identity monitoring services
• The role of identity theft in identity theft prevention
• The impact of identity theft on victims' ability to obtain loans
• Identity theft and its connection to identity theft protection
• The importance of identity theft awareness campaigns
• Identity theft and its impact on victims' ability to obtain mortgages
• The role of identity theft in identity theft detection
• The impact of identity theft on victims' ability to obtain insurance
• Identity theft and its connection to identity theft recovery
• The role of identity theft in identity theft investigation
• Identity theft and its impact on victims' ability to obtain jobs
• The connection between identity theft and identity theft prevention strategies
• The impact of identity theft on victims' ability to obtain housing
• Identity theft and its connection to identity theft protection measures
• The role of identity theft in identity theft prevention measures
• Identity theft and its impact on victims' ability to obtain healthcare
• The importance of identity theft detection services
• Identity theft and its connection to identity theft prevention programs
• The impact of identity theft on victims' ability to obtain government benefits
• Identity theft and its connection to identity theft protection programs
• The role of identity theft in identity theft prevention efforts
• Identity theft and its impact on victims' ability to obtain financial aid
• The connection between identity theft and identity theft protection plans
• The impact of identity theft on victims' ability to obtain credit cards
• Identity theft and its connection to identity theft protection services
• The role of identity theft in identity theft prevention strategies
• Identity theft and its impact on victims' ability to obtain car loans
• The importance of identity theft protection services
• Identity theft and its connection to identity theft prevention measures
• The impact of identity theft on victims' ability to obtain business loans
• Identity theft and its impact on victims' ability to obtain auto loans
• The impact of identity theft on victims' ability to obtain apartment rentals
• Identity theft and its impact on victims' ability to obtain student loans
• The importance of identity theft prevention measures
• The impact of identity theft on victims' ability to obtain personal loans
• Identity theft and its connection to identity theft protection plans
• Identity theft and its impact on victims' ability to obtain payday loans
• The connection between identity theft and identity theft protection services
• The impact of identity theft on victims' ability to obtain mortgage loans
• Identity theft and its impact on victims' ability to obtain credit union loans
• The impact of identity theft on victims' ability to obtain car title loans
• Identity theft and its impact on victims' ability to obtain business credit cards
• The impact of identity theft on victims' ability to obtain auto title loans
• Identity theft and its impact on victims' ability to obtain personal credit cards
• The impact of identity theft on victims' ability to obtain prepaid debit cards
• Identity theft and its impact on victims' ability to obtain online loans
• The impact of identity theft on victims' ability to obtain money orders
• Identity theft and its impact on victims' ability to obtain installment loans
• The impact of identity theft on victims' ability to obtain installment loans

By writing essays on these topics, you can help raise awareness about the dangers of identity theft and educate others on how to protect themselves from becoming victims. Remember, knowledge is power when it comes to preventing identity theft, so take the time to learn more about this important issue and share your knowledge with others.

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Identity Theft

Lynne M. Vieraitis is Professor of Criminology at the University of Texas at Dallas.

The University of Texas at Dallas

• Published: 06 January 2015
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Often cited as one of the fastest-growing crimes in the United States and abroad, identity theft continues to be of great concern to the public. It is a crime that is difficult to control and has become increasingly complex as offenders adapt to target hardening by consumers and businesses and identify new sources of data containing personally identifying information. The purpose of this essay is to provide readers with an overview of identity theft, including what is currently known about the trends and patterns of identity theft, information on offenders and victims, as well as the methods used by identity thieves to steal and convert personally identifying information for financial gain.

Often cited as one of the fastest-growing crimes in the United States and abroad, identity theft continues to be of great concern to the public. According to the 2013 Unisys Security Index , 57 percent of Americans surveyed reported that they are seriously concerned about identity theft ( Unisys 2014 ). 1 It is a crime that is difficult to control and has become increasingly complex as offenders adapt to target hardening by consumers and businesses and identify new sources of data containing personally identifying information. Because identity theft includes multiple forms of fraud, it is difficult to illustrate with singular examples; however, the following cases help to illuminate the complexity of identity theft, as well as the range of people who engage in this crime. In May 2014, 25 people were charged in a conspiracy that involved identity theft, as well as street-level drug selling, a prescription pill operation, and counterfeit check schemes in New York and New Jersey. One member of the group stole personal identifying information, including names and birth dates from his place of employment, and then passed the information on to another member who used it to fill out stolen or forged prescriptions for oxycodone. Other members then had the prescriptions filled at pharmacies and passed the product to yet another individual, who then sold the pills on the streets. The group also included an employee at a check-cashing store who provided members with personal and account information of small businesses, churches, and charitable organizations. The stolen information was then used to manufacture counterfeit checks and create false identification cards. Ring members recruited individuals to go inside banks with the false IDs, deposit counterfeit checks, and withdraw money from the bank accounts of individuals whose identities they had stolen ( Jacobs 2014 ). In a case that illustrates the global reach of identity theft, three men were charged with buying cars in San Diego using stolen identities and credit cards and then shipping them to Ghana to be resold for financial gain. The men allegedly purchased stolen credit cards and drivers’ licenses in bulk from a “carder” website in Singapore. 2 Using the victims’ information, the ringleader assumed their identities to negotiate the purchase of vehicles, email drivers’ license numbers and card information to the dealerships, and pay for the cars’ transport to New Jersey where they would be shipped to Africa and resold by a criminal organization ( Vigil 2014 ). Although the aforementioned cases resulted in victims’ losses of an estimated $80,000 and $500,000, respectively, the financial gain from identity theft can be much more extensive, reaching into the millions of dollars. For example, over a three-year period from 2010 to 2013, a group of 10 women filed over 7,000 false tax returns, resulting in nearly $20 million in refunds. The women set up sham tax businesses and filed false tax returns using identities stolen from their places of employment, which included a hospital, various state agencies, and call centers ( Gibson 2014 ). Last, while some identity thieves work in small groups, others work alone. In a recent incident, a community college student stole the personal identifying information and credit card numbers of clients from her former place of employment (a medical billing company). She used the information to pay tuition at the school and purchase items such as clothing, jewelry, and airline tickets. During her employment, she had access to thousands of clients’ personal and financial information, and at the time of her arrest was in possession of more than 400 identity profiles and 200 credit card numbers ( CBS Los Angeles 2014 ).

As illustrated by the aforementioned cases, identity theft schemes range from the simple to the complex, are committed by offenders working alone and in groups, and are committed by an array of offenders, including employees of legitimate businesses to common street offenders. Current data suggest that identity theft affects millions of people each year at a loss of billions of dollars to individuals and businesses. It was the number-one most reported fraud to the Federal Trade Commission’s (FTC) Consumer Sentinel Network in 2013 and has held this position fairly consistently over the past decade ( FTC 2014 ).

The purpose of this essay is to provide an overview of identity theft, including what is currently known about the trends and patterns of identity theft, information on offenders and victims, as well as the methods of carrying out identity theft from the available data on offenders. In the next section, we present data from various agencies and organizations tasked with collecting information on identity thefts that occur in the United States and other countries. This section is followed by an overview of offenders that engage in identity theft as well as those who are victimized. We conclude with a discussion of the techniques employed by identity thieves to steal personally identifying information and convert it to cash or goods for financial gain.

I. Measuring Identity Theft

The Identity Theft Assumption and Deterrence Act (ITADA), passed in 1998, states that identity theft occurs when a person “knowingly transfers, possesses or uses, without lawful authority, a means of identification of another person with the intent to commit, or to aid or abet, or in connection with, any unlawful activity that constitutes a violation of Federal law, or that constitutes a felony under any applicable State or local law.” The term “means of identification” is defined as “any name or number that may be used, alone or in conjunction with any other information, to identify a specific individual.” Yet, despite the federal statute, “there is no one universally accepted definition of [it] as the term describes a variety of illegal acts involving theft or misuse of personal information” ( Bureau of Justice Statistics [BJS] 2006 ).

The definitional problem makes it difficult to consistently measure identity theft, and often, the organizations and agencies collecting data employ different measures of this crime. The main issue centers on whether to include credit card fraud under the term “identity theft.” For example, if an offender steals a credit card, makes a purchase, and then discards the card, has the victim’s identity been stolen? Does the use of a financial account identifier constitute identity theft? Or does identity theft occur only when an offender uses personally identifying data? An offender can use a credit card number (financial account identifier) to make unauthorized purchases or use a social security number (personally identifying data) to open a new credit card account and make purchases ( Copes and Vieraitis 2012 ). Some researchers (e.g., Allison, Schuck, and Michelle Lersch 2005 , Copes and Vieraitis, 2007 , 2009a , c , 2012 ) exclude credit card fraud while others include it (e.g., BJS, 2013 ; FTC, 2014 ).

Others raise a second issue regarding the definition and measurement of identity theft, arguing that the crime involves two separate elements, theft and fraud, and that they should be defined and measured accordingly. In this case, “identity theft” occurs when an offender steals a victim’s personal identifying information, such as a social security number, birth certificate, or driver’s license, whereas “identity fraud” occurs when an offender uses the stolen information to open credit card accounts, obtain bank loans, or deposit counterfeit checks and make withdrawals from the victim’s bank account ( Koops and Leenes 2006 ). Although identity fraud cannot occur without identity theft, identity theft is not always followed by identity fraud, and the two components may be committed by separate offenders. Thus, it is important to be cognizant of the definition of identity theft employed by agencies and organizations when measuring the extent and patterning of this crime.

As with most crimes, understanding the true nature and extent of crime is problematic as much criminal victimization goes underreported. Identity theft is no exception. It is estimated that 40 percent of all crime victims do not report their victimization to law enforcement, but the rate of reporting varies by type of victimization with more serious crimes showing a greater level, in general, of reporting than less serious crimes. For a variety of reasons, some “unknown” number of identity theft victims do not report their crimes to law enforcement authorities. According to the 2012 Identity Theft Supplement (ITS) to the National Crime Victimization Survey (NCVS), fewer than 1 in 10—or 9 percent—of identity theft victims reported the incident to police ( BJS 2013 ). Studies from Canada provide similar rates of underreporting, with only 13 percent of Canadian victims reporting their victimization to a law enforcement agency (Office of the Privacy Commissioner of Canada 2013). However, the ITS also showed that whether someone reported the incident to law enforcement varied substantially by the type of identity theft victimization suffered by the victim. Victims of personal information fraud were the most likely to report the incident (40 percent) while the lowest rates were for victims of existing credit card fraud (4 percent; BJS 2013 ). Of victims who did not report the theft (91 percent), most “handled it another way,” including reporting the incident to another organization such as a credit card company. Identity theft victims may see no reason to report their victimization if they do not suffer much financial harm, as when a credit card company quickly dismisses the unauthorized charges made on the victim’s credit card. Nearly 30 percent of victims in the ITS indicated that they did not report their victimization because they had suffered no monetary loss ( BJS 2013 ). Other victims may be reluctant to report their victimization if they know the offender for fear of retaliation or of getting the offender in trouble with law enforcement, especially if the offender is a family member. Some victims may not know the appropriate agency with which to file a report, and the issue of jurisdiction is particularly murky when offenders and victims reside in different cities, states, or even countries. Moreover, when the “victim” is a financial institution or business the incident may not be reported as some businesses are unwilling to admit their security systems are not working ( Pontell 2002 ), some fear the potential loss of customers, and others may calculate that the tax write-off makes better business sense ( Hoofnagle 2007 ).

Understanding the true nature of identity theft, particularly regarding offenders, is also complicated by low clearance rates. An analysis of data from a Florida police department found that identity theft cases averaged a clearance rate of 11 percent ( Allison et al. 2005 ). Research studies conducted by Owens (2004) and Gayer (2003) report similar rates of 10 percent and 11 percent, respectively. Despite these limitations, a number of government and nongovernmental organizations that collect data on identity theft can provide some insight into this crime.

The first systematic survey of the prevalence and costs of identity theft victimization was conducted by the FTC in 2003. The results of a telephone survey of a random sample of US adults age 18 and older suggested that 27.3 million Americans had been victims of identity theft in the previous five years (1998–2002), including 9.9 million people in 2002 alone. The financial costs to businesses, financial institutions, and consumers were estimated at over $50 billion ( Synovate 2003 ). A follow-up survey was conducted three years later in 2006. Although not directly comparable due to changes in the methodology, the 2006 survey suggested that approximately 8.3 million US adults were victims of identity theft in 2005 ( Synovate 2007 ). In addition to the FTC surveys, other organizations have conducted surveys on identity theft, including the Javelin Strategy and Research group (Javelin), the American Association of Retired Persons, and the BJS.

Data on identity theft victimization are also collected by the FTC’s Identity Theft Data Clearinghouse, the National White Collar Crime Center, and the FBI’s Internet Crime Complaint Center. The data from these agencies, as well as state law enforcement organizations, other federal agencies, and nongovernmental organizations such as the Council of Better Business Bureaus are compiled in an online database maintained by the Consumer Sentinel Network and published each year in the Consumer Sentinel Network Data Book . Although a common source of information on identity theft victimization, as well as other consumer frauds, these data are based on victim-generated reports rather than nationally representative surveys of consumers. With these limitations in mind, the most reliable data on the extent and patterning of identity theft in the United States come from the NCVS and Javelin.

II. Trends and Patterns in Identity Theft

The most comprehensive and reliable data come from the BJS and Javelin. Both groups survey nationally representative samples of the US population and have been doing so since 2004 and 2005, respectively. It is interesting to note that the BJS employs the term “identity theft” while Javelin uses “identity fraud” in its survey of consumers, although the measures (defined later) are similar.

To address the need for data on identity theft victimization, BJS developed questions to measure identity theft trends and added them to the NCVS survey in 2004. Since this initial survey, the BJS has expanded its data collection efforts to include the ITS, first conducted in 2008, to collect more detailed information from individual victims age 16 and older. In 2012 major changes were made to the survey instrument, thus comparisons across years are not suggested ( BJS 2013 ). In its most recent report, the BJS measures identity theft victimization for persons age 16 or older who experienced one or more of the following incidents ( BJS 2013 : 1–2):

Unauthorized use or attempted use of an existing account such as credit or debit card, checking, savings, telephone, online, or insurance account (fraud or misuse of an existing account)

unauthorized use or attempted use of personal information to open a new account, such as a credit or debit card, telephone, checking, savings, loan, or mortgage account (fraud or misuse of a new account)

misuse of personal information for a fraudulent purpose, such as getting medical care, a job, or government benefits; renting an apartment or house; or providing false information to law enforcement when charged with a crime or traffic violation (fraud or misuse of personal information).

Results suggest that nearly 17 million persons, or 7 percent of all US residents age 16 or older, were victims of identity theft in 2012, with 22 percent of victims experiencing more than one incident. The fraudulent use of existing account information, such as credit card or bank account information, was the most commonly reported type of theft—85 percent of reported cases. The direct and indirect losses from this crime total nearly $25 billion, although about half of the victims suffered out-of-pocket losses of $100 or less ( BJS 2013 ).

Although not directly comparable to the BJS findings, Javelin also provides information about identity theft victimization in the United States. Since the survey methodology has remained relatively consistent since the initial survey in 2005, it allows for comparisons across time periods. Using the three categories originally defined by the FTC in 2003 and for persons age 18 and older, the survey measures identity theft (fraud) as: (a) existing card accounts—involving account numbers and/or the actual cards for existing credit and card-linked debit accounts; (b) existing non-card accounts—including existing checking and savings accounts and existing loans and insurance, telephone, and utilities accounts; and (c) new accounts and other frauds—new accounts or loans for committing theft, fraud, or other crimes using the victim’s personal information ( Javelin 2014 : 4).

According to the report, in 2013 13.1 million consumers suffered identity theft—the second highest number since Javelin began collecting data in 2005—at an estimated $18 billion in losses to consumers and businesses. The trends indicated by the data show that in 2006 there were 10.6 million victims of identity theft; this number dipped slightly in 2007 but rose to 13.9 million victims in 2009, the second highest year on record. Victimization decreased again in 2010 before rising to 13.1 million in 2013. Thus, from 2006 to 2013, identity theft victimization reported by US consumers rose nearly 24 percent ( Javelin 2014 ). 3 Existing card fraud was the most common type of victimization. The incidence of existing card fraud increased by 36 percent, affecting 5 percent of the population, to its highest level since the first survey was administered in 2006. Results also showed that the incidence of existing non-card fraud increased by a factor of 3. Although the number of fraud victims has risen since 2010, the total financial losses have declined. Total losses were $29 billion in the first year of the survey, peaking in 2009 at $32 billion before declining to $18 billion in 2013. Thus while the number of incidents of existing account fraud has risen, creating more victims, this form of identity fraud is less costly in monetary terms than nonexisting account fraud ( Javelin 2014 ).

Data from outside the United States suggests that citizens of other countries also suffer high rates of identity theft victimization. Duffin, Keats, and Gill (2006) reported that one in four British residents is or knows a victim of identity fraud. CIFAS, the UK’s fraud prevention service, reports that over 100,000 victims of identity crime have been recorded by their organization each year since 2009 ( CIFAS 2014 ). As of 2014, these data contained 460,000 records of confirmed frauds perpetrated or attempted against participating organizations, the majority (65 percent) of which are identity-related crimes. The data also show that existing account fraud against loans and credit cards increased significantly from 2012 to 2013 while fraud against bank accounts decreased ( CIFAS 2013 ). A nationwide public opinion survey of Canadians found that 6.5 percent of participants reported that they had been victims of identity fraud, the majority of whom had experienced credit card fraud ( Sproule and Archer 2010 ). The estimated out-of-pocket costs to Canadian consumers totaled over $150 million. The Canadian Anti-Fraud Centre, which collects data from victim reports, stated there were over 19,000 victims of identity fraud in 2013, up from 17,000 in 2011. Despite the increase in the number of victims, the monetary losses declined from $16 million in 2012 to 11 million in 2013 ( Canadian Anti-Fraud Centre 2013 ).

III. Correlates of Offending

As discussed previously, the clearance rates for identity theft are low, meaning that offenders are rarely identified, arrested, or prosecuted. Several obstacles make the investigation of identity theft cases and the likelihood of arrests difficult. Specifically, identity theft cases can be highly complex, and the offender may have committed the theft in a different jurisdiction than where the victim resides, making it difficult not only to identify an offender but to secure an arrest warrant. In addition, limited departmental resources may be directed toward the investigation of violent and drug-related offenses rather than identity thefts ( Vieraitis, Copes, and Birch 2014 ). Creating the profile of the typical identity thief is also complicated by the lack of information from victims. According to the ITS, in most cases the victim simply does not know anything about the identity of the offender ( BJS 2013 ). Victims whose personal information was used to open a new account or for other fraudulent purposes were more likely than victims of existing account misuse to know something about the offender, but the overall percentage of victims who knew anything about the person responsible was less than 9 percent ( BJS 2013 ). Another potential source of information on offenders is from offenders themselves. However, to date, few have sought to gather such data (for exceptions see Copes and Vieraitis 2012 ; Duffin, Keats, and Gill 2006 ; Gill, 2007 ). The lack of information from victims (individuals and businesses), low reporting rates, and low clearance rates combined with the paucity of data from offenders contribute to the difficulty in understanding identity theft, particularly those who engage in it.

Information on the demographic characteristics of identity theft offenders is presented in the results of the analyses conducted by Allison et al., (2005) , Gordon, Rebovich, Choo, and Gordon (2007) , and Copes and Vieraitis (2012) . Allison et al. and Gordon et al are based on law enforcement data while Copes and Vieraitis’ study is based on interviews with offenders. Gordon et al. examined closed US Secret Service cases with an identity theft component from 2000 to 2006. They found that most offenders (42.5 percent) were between the ages of 25 and 34 when the case was opened and another one-third were between 35 and 49 years of age. Similarly, Allison et al. found that offenders ranged in age from 28 to 49 with a mean age of 32. Both law enforcement based studies found similar patterns about race. Gordon et al. found that the majority of the offenders were black (54 percent), with whites and Hispanics accounting for 38 percent and 5 percent of offenders, respectively. Allison et al. found that the distribution of offenders was 69 percent black, 27 percent white, and less than 1 percent Hispanic or Asian. The two studies differed in terms of the gender of offenders. Gordon et al. found that nearly two-thirds of the offenders were male, whereas Allison et al. found that 63 percent of offenders were female.

Copes and Vieraitis’s (2012) sample of 59 identity thieves included 23 men and 36 women, which is consistent with the findings of Allison et al. (2005) ; however, this may be attributed to Copes and Vieraitis’ sampling strategy and the higher response rate from female participants. The racial makeup of their sample was 44 percent white, 53 percent black, and 3 percent other. 4 Offenders in the sample ranged in age from 23 to 60 years with a mean age of 38 years. The majority of offenders were ages 25 to 34 (34 percent) or 35 to 44 (32 percent). Only 7 percent were ages 18 to 24 years, and 5 percent were older than 55 years. The age distribution matches closely with the larger sampling pool and that found by Gordon et al. (2007) and Allison, et al.

Both Copes and Vieraitis (2012) and Allison et al. (2005) included information on the offenders’ employment status. Most of the offenders in Copes and Vieraitis’s study had been employed at some point during their lifetimes. The diversity of jobs included day laborers, store clerks, nurses, and attorneys. At the time of their crimes, 52.5 percent were employed, and a total of 35.5 percent of the sample reported that their employment facilitated the identity thefts. The majority of those who used their jobs to carry out their crimes committed mortgage fraud. The results from Allison et al. indicated that 47 percent were employed.

Little is known about the degree to which identity thieves specialize in their offenses. Prior arrest patterns indicated that a large portion of the offenders interviewed by Copes and Vieraitis (2012) had engaged in various types of offenses, including drug, property, and violent crimes. Yet the majority of them claimed that they committed only identity thefts or comparable frauds (e.g., check fraud). In total, 63 percent of the offenders reported prior arrests, and most were arrested for financial fraud or identity theft (44 percent), but drug use/sales (19 percent) and property crimes (22 percent) were also relatively common. This finding is consistent with that of Gordon et al. (2007) , who found that while the majority of defendants had no prior arrests, those who did have criminal histories tended to commit fraud and theft related offenses.

Copes and Vieraitis’ (2012) interviews with identity thieves yielded information that helps provide a richer and more detailed profile of the persons who commit this crime. Through interviews with offenders, they show that identity thieves are a heterogeneous group. Their family backgrounds, educational attainments, work histories, and criminal histories run the gamut from poverty to wealth, less than a high school education to graduate degrees, and no prior arrests to incarcerations for everything from fraud to drugs. Some are embedded in “street life” and resemble the profile of a typical street offender, while others live lives similar to those of the conventional middle-class citizen and share characteristics in common with middle-class fraudsters or white-collar offenders. Copes and Vieraitis suggest that it is difficult to create a profile of identity thieves because the crime may be more “democratic” than most other types of crimes ( Copes and Vieraitis 2012 ). This claim is also supported by recent research from the National Gang Intelligence Center (2013) , which found that gangs are increasingly engaging in more sophisticated criminal operations that include identity theft and related frauds such as credit card fraud, mortgage fraud, counterfeiting, and bank fraud.

IV. Correlates of Victimization

The data on identity theft victims is more substantial than the data available for offenders, yet difficulties still emerge when trying to establish the correlates of victimization. First, patterns emerging from victimization data are affected by the operational definition of identity theft employed by researchers. For example, including existing credit card fraud as a type of identity theft increases not only the victimization rate but some research suggests that it alters the demographic profile of victims (e.g., Copes, Kerley, Kane, and Huff 2010 ). However, recent findings from the NCVS show that across all types of identity theft, prevalence rates did not vary significantly by sex ( BJS 2013 ). Second, victimization patterns are also difficult to establish if certain cases are less likely than others to be reported. Victimization surveys suggest that certain types of frauds (e.g., nonexisting account frauds) are more likely to be reported to law enforcement than others (e.g., existing account frauds), thus caution in drawing conclusions is warranted (e.g., BJS 2013 ).

Several studies examine the correlates of victimization including demographic and behavioral characteristics ( Allison et al. 2005 ; Anderson 2006 ; BJS 2010 , 2013 ; Kresse et al. 2007 ; Copes et al. 2010 ; Pontell, Brown, and Tosouni 2008 ; Holt and Bossler 2009 ). Overall, the results of several of studies indicate that a similar percentage of men and women are victims of identity theft each year; the lowest rate of victimization is among persons age 65 or older, while the majority of victims are in their mid-20s to mid-50s; and those with incomes greater than $75,000 are at higher risk than households in lower income brackets ( Allison et al. 2005 ; Anderson 2006 ; BJS 2010 , 2013 ; Kresse, Watland, and Lucki 2007 ). The most comprehensive and reliable picture of identity theft victims is provided by recent data from the ITS that show that persons age 16 to 17 have the lowest rates of victimization followed by persons ages 18 to 24 and 65 or older. The highest rates of victimization were found among persons age 35 to 49 ( BJS 2013 ). Data on race/ethnicity and identity theft victimization show that households headed by white non-Hispanics and those reporting “two or more races” experienced higher rates of victimization than black non-Hispanics and Hispanics ( BJS 2013 ).

In addition to demographic profiles, studies have suggested that people who engage in risky behaviors such as remote purchasing or Internet usage are more likely to be victims of identity theft ( Holt and Bossler 2009 ; Copes et al. 2010 ). Although respondents in Copes et al.’s study reported that they rarely gave out personal information in response to a solicitation, victims of existing account fraud and new credit card fraud were more likely to do so than victims of existing credit card fraud. Despite cautions from law enforcement and consumer groups, victims of existing account fraud and new credit card fraud were less likely to check the backgrounds of people they do business with than were victims of existing credit card fraud ( Copes et al. 2010 ).

Data limitations prohibit us from knowing the true extent of identity theft victimization, and this may be particularly acute for certain types of victims. For example, child identity theft, which occurs when an offender uses the identifying information of a person under the age of 18 for personal gain, may be severely underreported. Available data suggests that this form of identity theft is relatively rare. Data from the FTC indicate that 6 percent of all cases reported to the agency involved victims who were 19 years old or younger ( FTC 2014 ), however, it is impossible to know the extent since it may take years (e.g., until the child turns 16 and applies for a driver’s license) to discover the theft. Some research suggests that the perpetrator of child identity theft is typically a family member who has easy access to personal information. According to Pontell, Brown, and Tosouni (2008) , over three-quarters of those who stole the identities of victims under the age of 18 were their parents. Similarly, Identity Theft Resource Center survey data indicated that in child identity theft cases, 69 percent of the offenders were one or both parents or a stepparent and 54 percent of these cases began when the victim was younger than the age of five ( Identity Theft Resource Center 2007 ).

Other research has examined the geographic distribution of identity theft victimization ( Lane and Sui 2010 ). In an analysis of FTC data from 2002 to 2006, Lane and Sui found regional trends for identity theft demonstrating that higher reporting rates were found in the southwestern states, with lower rates in New England and the northern plains states. The researchers note that these regional patterns mirror the trends for traditional larceny and theft crimes. They also found that following hurricane Katrina there was an eastern shift of identity theft in the form of government document and benefits fraud ( Lane and Sui 2010 ). In addition, specific types of identity theft were more prevalent in some regions that others. For example, employment fraud, government document fraud, and loan fraud were concentrated in states with higher Hispanic populations.

V. Methods of Identity Theft

Identity thieves have developed a number of techniques and strategies using low-tech (offline) and high-tech (online) methods to steal victims’ personally identifying information and convert the information to cash or goods ( Copes and Vieraitis 2012 ). Offenders obtain this information from wallets, purses, homes, cars, offices, and businesses or institutions that maintain customer, employee, patient, or student records. Social security numbers provide instant access to a person’s personal information and are widely used for identification and account numbers by insurance companies, universities, cable television companies, military identification, and banks. The thief may steal a wallet or purse; work at a job that affords him or her access to credit records; purchase the information from someone (e.g., employees who have access to credit reporting databases commonly available in auto dealerships, realtor’s offices, banks, and other businesses that approve loans); or find victims by stealing mail, sorting through the trash, or searching the Internet. Some offenders create elaborate schemes to dupe victims into revealing their personal information both on- and offline. Offenders may hack into businesses that maintain information legitimately or through the use of phishing, which involves spam email campaigns that solicit information from would-be victims. Underground websites and forums operate that sell stolen information (e.g., credit card and bank account numbers) for relatively cheap prices ( Holt and Lampke 2010 ). Other technology-based approaches include pharming (hackers install malicious code to redirect victims to fraudulent websites) and smishing (thieves use text messages to lure consumers to websites or phone numbers).

The focus here is on the low-tech methods used by thieves, as our review relies on the research findings of offender-based studies, and the information on criminals who use online methods is extremely limited. Information on methods used by offenders also comes from victimization surveys, (FTC, NCVS, and others), but the caveats discussed previously apply. Nonetheless, we give a brief overview of the findings based on these data before turning to the findings of qualitative research based on interviews with offenders. 5

A. Findings from Research Utilizing Official Data

The FTC (2009) data provide some information on the strategies used by offenders to steal victims’ information. Based on data from the 43 percent who knew how their information was stolen, the report suggests that offenders obtain information from people they know personally (16 percent), during a financial transaction (7 percent), from a stolen wallet or purse (5 percent), from a company that maintained their information (5 percent), or through stolen mail (2 percent). Of respondents to the 2012 ITS, only 32 percent of victims knew how their information was obtained. Victims who experienced more than one type of identity theft during a single incident were most likely to know how this was accomplished (46.5 percent), whereas victims of existing credit card fraud were least likely to know this information (24 percent). Of the victims who knew how the theft occurred, most (43 percent) indicated that their information was stolen during a purchase or other transaction ( BJS 2013 ). Early reports from the NCVS provide a more detailed breakdown of the methods identified by victims ( BJS 2010 ). In 2009, 39 percent of respondents knew how their personal information was obtained. Of these respondents, nearly 30 percent reported that their identity was stolen during a purchase or other transaction, 20 percent said the information was lost or stolen from a wallet or checkbook, and 14 percent indicated the information was stolen from personnel or other files at an office. High-tech methods were less likely to be reported, with 4 percent of respondents indicating their computers were hacked, that they responded to spam email or phone call, or that their data were exposed on the Internet.

Offenders can use information to acquire or produce additional identity-related documents, such as driver’s licenses or state identification cards, in an attempt to gain cash or other goods. Offenders apply for credit cards in the victims’ names (including major credit cards and department store credit cards), open new bank accounts and deposit counterfeit checks, withdraw money from existing bank accounts, apply for loans, open utility or phone accounts, and apply for public assistance programs.

According to the FTC, the most common type of identity theft in 2006 was credit card fraud (25 percent), followed by “other” identity theft (24 percent), phone or utilities fraud (16 percent), bank fraud (16 percent), employment-related fraud (14 percent), government documents or benefits fraud (10 percent), and loan fraud (5 percent; Synovate 2007 ). 6 Data from the 2012 ITS indicate the most common type was the unauthorized misuse or attempted misuse of an existing account. Eighty-five percent of victims experienced this type of theft; more specifically, 40 percent involved existing credit card accounts, 37 percent bank accounts, and 7 percent other accounts such as existing, telephone, online, or insurance accounts ( BJS 2013 ). While much of the official data (i.e., FTC and BJS) suggest that existing credit card fraud is the most common method of identity theft perpetrated by offenders, little detail is given on the specific methods employed. We now turn to offender-based data to provide a more detailed picture of the methods used to convert information.

B. Findings from Offender-Based Research

Research on identity thieves provides more details on the specific techniques that offenders use to steal and convert personal information ( Copes and Vieraitis 2012 ). 7 Participants in Copes and Vieraitis’ study revealed techniques used by organized rings in which a person is planted as an employee in a mortgage lender’s office, doctor’s office, or human resources department to access information more easily. Similarly, these groups will simply bribe insiders such as employees of banks, car dealerships, government agencies, and hospitals to gain access to identifying information. Offenders report buying information from other offenders such as prostitutes, burglars, drug addicts, and other street hustlers. Some offenders engage in sophisticated ploys to induce victims to reveal personal information such as setting up fake employment sites or convincing a friend or relative to help the offender out of a difficult financial situation.

Most offenders use the information to order new credit cards, but they also use it to induce the credit card agency to issue a duplicate card on an existing account. They use credit cards to buy merchandise for their own personal use, to resell the merchandise to friends and/or acquaintances, or to return the merchandise for cash. Offenders also use the checks that are routinely sent to credit card holders to deposit in the victim’s account and then withdraw cash or open new accounts. Offenders have been known to apply for credit cards at department and home improvement stores. Other common strategies for converting information into cash and/or goods includes producing counterfeit checks, which offenders use to obtain cash at grocery stores, purchase merchandise and pay bills, open new bank accounts in order to deposit checks or withdraw money from an existing account, and apply for and receive loans ( Copes and Vieraitis 2012 ).

Identity thieves rely on a number of methods to carry out their crimes. In addition, as the profiles at the beginning of this essay indicate, some thieves do so by working alone, while others are involved in teams both small and large. The participants in Copes and Vieraitis’ (2012) study reported that they relied on a number of organizational schemes to carry out their acquisition of personal information and the conversion of that information into cash and/or goods. Three primary organization schemes emerged from their interviews with offenders, including loners, street level identity theft (SLIT) rings, and occupational teams.

Loners reported typically using the personal information of others to open credit card accounts or secure bank loans. Many of these offenders claimed that they tried to make payments on the accounts to prevent victims from discovering the fraud, but eventually repayment became impossible. In some cases they used information available to them for their place of work, and in some cases they used the information of family members, including their own children, or friends. In one case, a woman employed at a mortgage company used client information to obtain personal bank loans. In another, the offender used the personal information of deceased family members to open bank accounts, get credit cards, and apply for a HUD loan. One thief used the personal information of her children and mother to take out bank loans. Other thieves used more sophisticated and elaborate schemes to dupe strangers into revealing their information. For example, one set up fake employment sites with applicants willingly supplying all their personal information, and another used obituaries to access information and file fraudulent Medicare claims.

The majority of the identity thieves interviewed by Copes and Vieraitis (2012) operated in teams characterized by an elaborate division of labor in which members performed different roles depending on their knowledge and skills. There was considerable diversity among this group that necessitated the division of teams into two types: SLIT rings and occupational teams. SLIT rings and occupational teams share many similarities, but they differ noticeably in the methods they use to steal and convert information.

SLIT rings used numerous methods to acquire and convert information. Some rings relied on an individual employed by a company that possessed legitimate access to names and personally identifying information of clients to obtain information. Others targeted residential and commercial mailboxes to steal checkbooks, bank statements, or medical bills. For most SLIT rings in Copes and Vieraitis’ (2012) sample, the person supplying the information was a street-level criminal—typically engaged in drug sales, robbery, burglary, or other street crimes—who sold the information to the ringleader. This information included drivers’ licenses and social security cards. Some rings obtained information from willing acquaintances, friends, and family members in exchange for a fee. The “victim” would then wait a while before reporting the “theft.” In one case involving a well-known gang, the ringleader paid someone to purchase birth certificates from drug-addicted mothers. The birth certificates of US children were used to gain passports so the children of gang members and their associates could enter the country “legally.”

After obtaining victims’ information, offenders applied for credit cards in the victims’ names, opened new bank accounts and deposited counterfeit checks, withdrew money from existing bank accounts, applied for loans, or opened utility or telephone accounts. Because such transactions all require some form of official identification, teams recruited employees of state or federal agencies with access to social security cards or birth certificates, which could then be used to order identification cards. While thieves could use fraudulent information to obtain identification cards through conventional channels, it also was possible to manufacture false cards using rogue employees of state departments of motor vehicles or through street hustlers, who had managed to obtain the necessary equipment. For SLIT rings, the most common strategy for converting information into cash was by applying for credit cards, both from major card issuers and individual retailers. Offenders could use a stolen identity to order new credit cards or to issue a duplicate card on an existing account. With these cards in hand, they could buy merchandise for their own personal use, for resale to friends and acquaintances, or to return for cash. Another common strategy for converting information into cash or goods involved producing counterfeit checks. Offenders typically used such checks to open new bank accounts or deposited them in the victim’s existing account before withdrawing cash. Counterfeit checks also could be cashed at grocery stores or be used to purchase merchandise and pay bills.

Members of occupational teams used their legitimate place of employment to steal information and convert it to goods or cash, acting almost exclusively with fellow employees to commit their crimes. In mortgage fraud schemes, the majority of players were employed at the same company or at companies that worked together to process home loans. In cases involving workers at a state department of motor vehicles, an outside source provided information to employees, who then issued state identification cards or driver’s licenses that were subsequently used to carry out identity thefts. The thefts committed by occupational teams typically involved theft on a larger scale, characterized by numerous victims and higher dollar losses than those committed by SLIT rings or loners.

VI. Conclusions and Future Research

It is clear that identity theft affects a sizable portion of the population, is costly in both time and money, and is difficult to detect and prosecute. To understand the crime of identity theft and thus increase the likelihood that policymakers and law enforcement officials are effective in reducing it, there is a need for continued research. The first step is to address the problem of data collection. Currently, information on identity theft is collected and housed in multiple databases, including both private and government agencies. One incident may be reported to local, state, and federal law enforcement agencies, credit reporting agencies, credit card companies, financial institutions, telecommunication companies, and others. This makes the collection and sharing of information among agencies difficult. It also creates significant barriers to developing reliable estimates of the extent of identity theft, patterns in victimization and offending, and the true costs associated with this crime. There is also little data on the processing of identity thieves including clearance rates, conviction rates, and sentencing. We need more systematic data collection from agencies responsible for personal information; agencies that use personal information in legitimate business practices; law enforcement agencies at local, state, and federal levels; victims; and those who know most about how and why identity theft occurs—the identity thieves themselves. Although the focus here has been on offender-based research, we do not deny the critical roles that individuals, businesses, and government agencies play in the development of prevention strategies. Increasing the effort and risk associated with stealing identifying information and converting it into cash or goods requires diligence on the part of individuals as well as businesses. Moreover, understanding how individuals and businesses protect and regulate the use of personally identifying information can improve efforts to control identity theft and fraud. Gaining information on who these offenders are and how they perpetrate their crimes can also help inform policies designed to decrease identity theft. As Collins (2006 : 181) notes, “[C]omputers do not steal identities… people do.”

Allison, Stuart F. H. , Amie M. Schuck , and Kim Michelle Lersch . 2005 . “ Exploring the Crime of Identity Theft: Prevalence, Clearance Rates, and Victim/Offender Characteristics. ” Journal of Criminal Justice , 33: 19–29.

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Canadian Anti-Fraud Centre Criminal Intelligence Analytical Unit. 2013. Annual Statistical Report 2013. https://www.antifraudcentre-centreantifraude.ca/english/documents/Annual2013CAFC.pdf

CBS Los Angeles. 2014. “LA Community College Student Pleads Not Guilty to Identity Theft Charges.” March 10. http://losangeles.cbslocal.com

CIFAS. 2013 . “ CIFAS Report Examines Fraud in 2012. ” Fraudscape , March 5. London. http://www.cifas.org.uk/fraudscape_twentythirteen

Collins, Judith M.   2006 . Investigating Identity Theft: A Guide for Businesses, Law Enforcement, and Victims . Hoboken, NJ: Wiley.

Copes, Heith , and Lynne Vieraitis . 2009 a. “ Bounded Rationality of Identity Thieves: Using Offender-Based Research to Inform Policy. ” Criminology and Public Policy , 8: 237–262.

Copes, Heith , and Lynne Vieraitis . 2009 b. “Identity Theft.” In M. Tonry (Ed.), Oxford Handbook on Crime and Public Policy . Oxford: Oxford University Press.

Copes, Heith , and Lynne Vieraitis . 2009 c. Understanding Identity Theft: Offenders’ Accounts of their Lives and Crimes.   Criminal Justice Review , 34: 329–349.

Copes, Heith , Kent R. Kerley , John Kane , and Rodney Huff . 2010 . “ Differentiating Identity Theft: An Exploratory Study of Victims Using a National Victimization Survey. ” Journal of Criminal Justice , 38: 1045–1052.

Copes, Heith , and Lynne Vieraitis . 2012 . Identity Thieves: Motives and Methods . Boston: Northeastern University Press.

Copes, Heith , Lynne Vieraitis , and Jennifer Jochum . 2007 . “ Bridging the Gap Between Research and Practice: How Neutralization Theory Can Inform Reid Interrogations of Identity Thieves. ” Journal of Criminal Justice Education , 18: 444–459.

Credit Industry Fraud Avoidance System. 2014. “Identity Fraud.” http://www.cifas.org.uk/identity_fraud

Duffin, Michelle , Gemma Keats, and Martin Gill . 2006 . Identity Theft in the UK: The Offender and Victim Perspective . Leicester, UK: Perpetuity Research and Consultancy International.

Federal Trade Commission. 2009. Consumer Sentinel Network Data Book, January–December 2008 . http://www.ftc.gov/sentinel/reports/sentinel-annual-reports/sentinel-cy2008.pdf

Federal Trade Commission. 2014. Consumer Sentinel Network Data Book, January–December 2013.   http://www.ftc.gov/system/files/documents/reports/consumer-sentinel-network-data-book-january-december-2013/sentinel-cy2013.pdf

Gayer, Jenette . 2003 . Policing Privacy: Law Enforcement’s Response to Identity Theft . Los Angeles: California Public Interest Research Group.

Gibson, David . 2014 . “ 10 Accused of $20 Million in Identity Theft Fraud. ” Atlanta Journal Constitution, May 22. http://www.ajc.com/news/news/local/10-accused-of-20-million-in-identity-theft-fraud/nf5f7/

Gill, Martin . 2007 . Learning from Fraudsters: Reinforcing the Message . Leicester, UK: Perpetuity Research & Consulting.

Gordon, Gary R. , Donald Rebovich , Kyung-Seok Choo , and Judith B. Gordon . 2007 . Identity Fraud Trends and Patterns: Building a Data-Based Foundation for Proactive Enforcement. Utica, NY: Center for Identity Management and Information Protection.

Holt, Thomas J. , and Adam M. Bossler . 2009 . “ Examining the Applicability of Lifestyle-Routine Activities Theory for Cybercrime Victimization. ” Deviant Behavior , 30: 1–25.

Holt, Thomas J. , and E. Lampke . 2010 . “ Exploring Stolen Data Markets On-line: Products and Market Forces. ” Criminal Justice Studies , 23: 33–50.

Hoofnagle, Chris J.   2007 . “ Identity Theft: Making the Known Unknowns Known. ” Harvard Journal of Law and Technology, 21(1): 98–122.

Identity Theft Resource Center. 2007. “Identity Theft: The Aftermath, 2006.” http://www.idtheftcenter.org/images/surveys_studies/Aftermath2006.pdf

Identity Theft Resource Center. 2014. “2013 Data Breach Stats.” http://www.idtheftcenter.org/images/breach/2013/UpdatedITRCBreachStatsReport.pdf

Jacobs, Shayna . 2014 . “ Exclusive: Wannabe Rapper Busted as Part of 25-Member Identity Theft Ring. ” New York Daily News, May 29. http://www.nydailynews.com/news/crime/exclusive-rapper-busted-identity-theft-ring-article-1.1809371

Javelin Strategy and Research. 2011 . 2011 Identity Fraud Survey Report: Consumer Version . Pleasanton, CA: Javelin Strategy and Research Group.

Javelin Strategy and Research. 2014 . 2014 Identity Fraud Survey Report: Consumer Version. Pleasanton, CA: Javelin Strategy and Research Group.

Koops, Bert-Jaap, and Ronald Leenes . 2006 . “ Identity Theft, Identity Fraud and/or Identity-Related Crime. ” Datenschutz und Datensicherheit , 30: 553–556.

Kresse, William , Kathleen Watland , and John Lucki . 2007. “Identity Theft: Findings and Public Policy Recommendations.” Final Report to the Institute for Fraud Prevention. Chicago: Saint Xavier University. http://www.theifp.org/research-grants/ID%20Theft%20in%20Chgo%20-%20%20Final%20Report_press.pdf

Lane, Gina W. , and Daniel Z. Sui . 2010 . “ Geographics of Identity Theft in the U.S.: Understanding Spatial and Demographic Patterns, 2002–2006. ” GeoJournal 75: 43–55.

National Gang Intelligence Center. 2013 . “ 2013 National Gang Report. ” Washington: DC.

Owens, Megan . 2004 . Policing Privacy: Michigan Law Enforcement Officers on the Challenges of Tracking Identity Theft . Ann Arbor: Michigan Public Interest Research Group.

Pontell, Henry . 2002 . “‘ Pleased to Meet You … Won’t You Guess my Name?’ Identity Theft, Cyber Crime, and White Collar Delinquency. ” Adelaide Law Review , 23(2): 305–328.

Pontell, Henry N. , Gregory C. Brown , and Anastasia Tosouni . 2008 . “Stolen Identities: A Victim Survey.” In Megan M. McNally and Graeme Newman (Eds.), Perspectives on Identity Theft (pp. 57–86). New York: Criminal Justice Press.

Sproule, Susan , and Norm Archer . 2010 . “ Measuring Identity Theft and Identity Fraud. ” International Journal of Business Governance and Ethics , 5(112): 51–63.

Synovate. 2003. “Federal Trade Commission: 2003 Identity Theft Survey Report.” http://www.ftc.gov/sites/default/files/documents/reports/federal-trade-commission-identity-theft-program/synovatereport.pdf

Synovate. 2007. “Federal Trade Commission: 2006 Identity Theft Survey Report.” www.ftc.gov/os/2007/11/SynovateFinalReportIDTheft2006.pdf

Unisys. 2014. “Unisys Security Index 2014.” http://www.unisys.com

Vieraitis, Lynne , Heith Copes , and Ivan Birch . 2014 . “Identity Theft.” In Gerben Bruinsma and David Weisburd (Eds.), Encyclopedia of Criminology and Criminal Justice . New York: Springer.

Vigil, Jennifer . 2014 . “ 3 Men Charged in Theft Ring that Stretches from San Diego to Ghana. ” Times of San Diego , May 23. http://timesofsandiego.com/crime/2014/05/23/3-men-charged-in-theft-ring-that-stretches-from-san-diego-to-ghana/

Although identity theft is ranked second on the list of top security concerns, the highest ranked issue is related to identity theft. Fifty-nine percent of US respondents surveyed are seriously concerned (“extremely” or “very concerned”) about other people obtaining and using their credit or debit card details.

Carders are people who buy, sell, and trade credit card data taken from phishing websites or large store data breaches.

Javelin reports the total number of victims rather than the rates of victimization per population. When computed as a rate per 100,000 population ages 18 years and older, identity theft victimization increases 15 percent from 2006 to 2013.

The makeup for the full list of located inmates from which the Copes and Vieraitis (2012) sample was drawn was 50 percent white, 46 percent black, and 4 percent other. This is a higher percentage of white offenders than found by either Gordon et al. (2007) or Allison et al. (2005) .

Duffin et al. (2006) and Gill (2007) are based on extremely small samples of identity thieves (five and two, respectively). We should also note that despite research that suggests online identity theft is rare in comparison to offline methods, the number of victims in one incident can be substantial. The Identity Theft Resource Center (2014) reports that in 2013 there were 614 breaches of information in which an individual’s name plus social security number, driver’s license number, medical record, or financial record/credit card/debit card was put at risk in electronic or paper format. The number of records exposed totaled nearly 92 million. The extent of frauds perpetrated after such attacks, however, is yet unknown although recent figures suggest that one in four data breach notification recipients become victims of fraud ( Javelin 2011 ).

According to the most recent Consumer Sentinel report (2014), victims’ information was misused for government documents or benefits fraud in 34 percent of reported cases, followed by “other” (24 percent) and credit card fraud in 17 percent of cases; however, the data are based on victim-initiated reports.

The limitations regarding data also apply to the offender-based studies reviewed here. For example, Copes and Vieraitis’ data are drawn from interviews with federally convicted identity thieves and are not necessarily representative of the typical identity thief. Briefly, they may be responsible for unusually high monetary losses or have clear evidence against them making prosecution easier. Moreover, some have suggested that convicted offenders may be considered unsuccessful or unskilled offenders, which is why they were caught. For a more detailed discussion of this issue see Copes and Vieraitis (2009a , b , 2012 ).

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Digital Commons @ USF > Office of Graduate Studies > USF Graduate Theses and Dissertations > USF Tampa Theses and Dissertations > 1322

USF Tampa Graduate Theses and Dissertations

A case study of identity theft.

Stuart F. H Allison , University of South Florida

Graduation Year

Document type, degree granting department.

Criminology

Major Professor

Michael J. Lynch, Ph.D.

Co-Major Professor

Schuck, Amie

Committee Member

Amie Schuck, Ph.D.

Kim M. Lersch, Ph.D

Fraud, Economic Crime, Trend Analysis

This thesis is an investigation of identity theft, although not a new crime it has recently attracted public concern. This concern has led to both federal and state governments to establish new laws to provide increased protection. Government agencies and the media have warned the public that an individual's social security number and other personal information are the tools that unscrupulous criminals can use to gain access to an identity. Once your identity is assumed criminals can use that new identity to obtain goods and services freely available in this world of instant credit lines.

The purpose of this study is to examine the magnitude and characteristics of identity theft. The objective is to determine if government official's claims and the media's portrayal of the substantial rise in identity theft incidents are supported empirically.

The data for this study comes from police records located in one southern-metropolitan city; from this two separate data sets were drawn. A case study methodology was selected for this project.

The results indicate that the identity theft trend is different than the trends for other theft related offenses -- credit card fraud, check fraud, robbery and motor vehicle theft. The data suggest that identity theft is increasing more rapidly than the other theft orientated offenses. However, future research should be conducted to help determine if the trend found in this study is a more a reflection of criminal behavior then of changes in reporting. Additionally, the available literature on identity theft suggested that attaining an arrest for identity theft is especially difficult. The empirical evidence found in this study is mixed on this point. Finally, the demographic characteristics of identity thieves in the area of study do not conform to other economically motivated offenders. African American female offenders make up a significantly large proportion of offenders. Determining the cause of these patterns would at this point be premature, but the existence of patterns warrants further research.

In conclusion, this study finds support for the expressed belief by media, private organizations, and government officials that there is greater reporting and recoding of identity theft.

Scholar Commons Citation

Allison, Stuart F. H, "A Case Study of Identity Theft" (2003). USF Tampa Graduate Theses and Dissertations. https://digitalcommons.usf.edu/etd/1322

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English Composition 1

Introductions.

An introduction does not need to be long (and should not be), but it is an important part of an essay. A weak introduction can cause readers to lose interest in your essay from the start, whereas a strong introduction will engage your readers and make them want to continue reading. Of course, the introduction is the first part of your essay that your audience will read, and it's important to make a good first impression. This page provides suggestions to help you write strong introductions.

Introductions: An Overview

In general, an introduction needs to do three things:

• to spark the interest of readers,
• to move readers gracefully toward the thesis statement, and
• to present the thesis statement of the essay.

The order of items above is the best order to present each part of the introduction: get the reader's attention, move toward the thesis statement, and then present the thesis statement. The thesis statement usually is most effective as just one sentence at the end of the introduction, so you should avoid presenting the thesis statement as the first sentence of the introduction and should avoid presenting the thesis statement in more than one sentence. (Information about thesis statements is presented on The Thesis Statement Web page.)

Just about any kind of introduction could work well in the hands of a skillful writer, but below are examples of a few approaches to writing introductions that often are effective, followed by some additional suggestions for introductions.

Approaches to Writing Introductions

Each of the introductions below presents the same thesis statement: "Identity theft is a serious problem that claims millions of innocent victims, and the government must implement better regulations to help put an end to this crime." While the thesis statement is the same for all of the introductions, notice how the various introductions set different tones for the essay and establish slightly different expectations for what will follow in the body of the essay.

1. Begin with Background or Historical Information

2. begin with a quotation, 3. begin with an interesting or surprising fact, 4. begin with a definition of an important term, 5. begin with a short narrative, 6. begin with a question, introductions to avoid.

Some approaches to introductions almost always fail to be interesting or engaging. Below are a few approaches to introduction that should be avoided. They are just about guaranteed to give an essay a weak beginning.

• Avoid Beginning with Overly Vague and General Statements or Broad Generalizations Example: Crimes are committed every day by different people, and there are many different kinds of crime. Some crimes are more serious than others. One serious crime today is identity theft. (Can you hear the readers already starting to snooze? The first two sentences to this introduction are far too vague and general to get anyone interested in what the writer is going to say in the paper.)
• Avoid Beginning with Dictionary Definitions Obvious to Readers
• Avoiding Beginning with a Direct Statement of What You, as the Writer, are Doing Example: In this essay, identity theft will be explained. I will discuss why it is such a big problem and what the government should do about it. (Such an introduction might be appropriate for a writer in junior high school, but mature writers use much more effective rhetorical strategies to begin their essays.)

Introductions: A Few Tips

• Write the introduction after you have written the body of your essay. Writers often sit down to an empty computer screen and struggle to write an introduction, and understandably so: they do not yet know what exactly it is that they are introducing. You should have a thesis statement in mind as you write an essay, but there is no reason to have to write the introduction before you begin writing the body paragraphs. It is often much easier to write an introduction when you can actually see what you are introducing.  
• Avoid long introductions. Introductions generally are not long, certainly not longer than body paragraphs. Avoid going into depth developing ideas in the introduction. That's for the body paragraphs of an essay, not for the introduction. The primary purpose of an introduction is just to introduce your essay.  
• Experiment with more than one type of introduction for the same essay. As the examples above illustrate, different introductions can give an essay quite a different tone. You might try writing a few different introductions, using the approaches above, and you could then choose the introduction that you think best fits your paper.  
• Avoid the approach to introductions sometimes taught to young students. Some young students are taught to begin an introduction with a thesis statement, followed by separate sentences that indicate the topics for the body paragraphs of the essay. Avoid this approach. It helps young writers organize an essay and stay focused, but it is rhetorically weak.  

Copyright Randy Rambo , 2019.

Identity Theft Crimes in the United States Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Unlawful identity theft happens when a pretender steals another individual’s name and private data. The data may include the date of birth, social security number or name. The thief may show to the police force a fake license comprising another individual’s information (Barnard-Wills, 2011). Often, but not at all times, the pretender falsely attained a driver’s license or ID in the object’s name and offered that documentation to the police. Or the thief, without presenting any photograph credentials, misuses the name of a colleague or acquaintance. Therefore, an identity theft is a crime, and the criminals should be punished even in the case when they do not cause any monetary damage. In numerous examples, the thief is penalized for a traffic violation or an offense and is out from the confinement. The thief signs the documents and pledges to show up in court. If the pretender fails to appear in the law court, the judge may issue a warrant, but it will be under the theft object’s credentials and legal name.

Even though the law agencies recognize the commonness of identity theft, these crimes are evidencing bizarrely problematic to avert, and they are happening with growing occurrence (Whiting, 2013). The total size of the data traded on the internet daily produces breaches for hackers and other technologically knowledgeable offenders to steal information without being exposed. Correspondingly, once these online crimes are revealed, the police are repeatedly incapable of finding and arresting the persons in charge. This may be due, to some extent, to the circumstance that a great part of the identity stealers is supposed to be living out of the country.

The identity theft target may not realize there is a chance of being arrested because of the imposter. The victim may be stopped, detained, and taken to the penitentiary without preceding announcement due to the unresolved warrant ( Identity Theft , n.d.). It may as well happen that the thief will show up in court for the road traffic or malfeasance and negotiate without the theft victim being conscious of this incident. Some identity stealing targets, unconscious of the prior illegal activity by the pretender, may find out that there was a case of the impersonation when the individual is deprived of service or fired. In these examples, the company conducted a circumstantial examination and had counted on the felonious past found under the person’s data. It is also important that the company is officially obliged to notify the victim of the motive for the denunciation of employment. Regrettably, all the responsibility lies on the victim’s name, so the target of theft has to act rapidly and forcefully to diminish the harm. Nonetheless, the accountability to edit the inaccurate information in the numerous law enforcement databases and structures is to the officers occupied within the system. There are no conventional measures for editing an individual’s incorrect criminal record.

Regarding the state identity theft statutes, any of the subsequent evidence is well thought-out to be particularly classifying data in Illinois: an individual’s name, living address, cell phone number, workplace information, savings account or credit card number, individual or electronic ID number, various credentials, and any other records or data which can be used to log into or exploit an individual’s monetary possessions, or to detect a certain person, or his or her activities, incoming and outgoing messages and calls, or other actions or communications ( Identity Theft State’s Statutory Information , n.d.). A personal ID comprises any documentation created or distributed by a legislative unit that is projected for the determination of proving the identity of a person, or any such file that misleadingly signifies to have been made in the best interests of or delivered to another individual.

In Illinois, an individual is an identity thief when he or she perceptively uses any private identifying data or personal proof of identity of another individual to dishonestly acquire recognition, money, private property, or services ( Identity Theft State’s Statutory Information , n.d.). An individual is also considered a thief in case if he or she exploits any private material or the ID of another person with the intention of committing any offense not mentioned above. The person is guilty of identity theft if he or she operates, transmits, or owns paper-production gear to create false IDs or false papers realizing that they will be exploited by the individual or another person to commit any crime. Identity theft regularly goes before other kinds of scam and monetary criminalities ( Identity Theft State’s Statutory Information , n.d.).

Along with the elementary identity theft, Illinois similarly proscribes the intensified type of the crime, which arises when an individual steals identity from a person aged 60 or older, an individual with ill health, or in the maintenance of the actions of an organized mob. Regarding to the elementary and intensified types of identity theft, the law states that the defending individual’s knowledge will be evaluated in a form of an assessment of all conditions of his or her use of the other individual’s private materials or evidence. Identity theft arrests in Illinois include almost the full range of lawbreaking offenses.

The notion of identity theft is closely related to the 14 th Amendment of the United States Constitution. The 14 th amendment was central in returning the Confederacy into the US subsequent to the Civil War. The US took charge of the retirement funds for the armed forces that took part in the conflict and rejected to take on the unpaid sums of the Confederate, while as well averting past Confederate frontrunners from holding voted agency or public positions ( 14th Amendment , n.d.). The 14 th Amendment correspondingly guaranteed that debts were not permitted owing to the liberation of slaves. The Due Process section defends the 1 st Amendment civil rights of the individuals and prevents those privileges from being annulled by any administration without “due process.” Due process is a probation by judges for all the individuals accused of a crime.

The 14 th Amendment particularly imposes the Bill of Rights on the government, to verify that it can never bound the constitutional rights of Americans without justice ( What Is the Fourteenth Amendment and What Does It Mean, n.d.). The 14 th Amendment should be looked upon in the case of an identity theft as every accused individual has the same rights as any other individual until proved guilty. The Equal Protection part of the 14 th Amendment pledges that the accused will not face any discernment by the law. The national administration imposes this fortification on the States, certifying that they do not. The Equal Protection section protracted this defense to the state administrations.

Identity theft crimes are an important area of the US legal system and should be taken very seriously. Despite the fact that these wrongdoings are punishable, and there have been numerous cases of identity theft, all the US citizens have their civil rights, and both the victim and identity thief can rely on the 14 th Amendment. It should be noted that the number of identity theft crimes grows due to the inability to arrest or at least locate the criminals, but the victims can count of the fair judgment and impartiality in the court.

14th Amendment . (n.d.). Web.

Barnard-Wills, D. (2011). Surveillance and Identity: Discourse, Subjectivity and the State . Surrey: Ashgate Publishing Group.

Identity Theft State’s Statutory Information . (n.d.). Web.

Identity Theft . (n.d.). Web.

What Is the Fourteenth Amendment and What Does It Mean (n.d.). Web.

Whiting, J. (2013). Identity Theft . San Diego, CA: ReferencePoint Press.

• Drug Control, Gun Policies, and Sex Offender Laws
• Cybercrime Impact on Global Criminal Justice System
• Provisions of the Constitution of the United States and the State of Illinois
• The Black Confederate Soldier in the Civil War
• Crimes Against Property in Illinois
• Media Influence on Criminal Justice and Community
• Police Issues and Practices Discussion
• Cybercrime, International Laws and Regulation
• Criminal Justice: Discipline, Liability and Labor Relations
• American Prison Overcrowding and Its Future
• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2020, August 19). Identity Theft Crimes in the United States. https://ivypanda.com/essays/identity-theft-crimes-in-the-united-states/

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• v.17; 2020 Mar

Risk and protective factors of identity theft victimization in the United States

David burnes.

a University of Toronto, Factor-Inwentash Faculty of Social Work, 246 Bloor Street West, Toronto, Ontario, M5S1V4, Canada

Marguerite DeLiema

b University of Minnesota, Twin Cities, School of Social Work, 105 Peters Hall, 1404 Gortner Ave., St. Paul, MN, 55108, USA

Lynn Langton

c RTI International, Division for Applied Justice Research, 701 13th Street NW, Washington DC, 20005, USA

Associated Data

• • Identity theft is a pervasive problem and a public health issue.
• • Frequent online purchasing behaviors result in greater risk of identity theft.
• • Corporate and government data breaches put consumers at risk for identity theft.
• • Risk factors vary by identity theft subtype.
• • Routine individual preventative behaviors can mitigate identity theft risk.

Identity theft victimization is associated with serious physical and mental health morbidities. The problem is expanding as society becomes increasingly reliant on technology to store and transfer personally identifying information. Guided by lifestyle-routine activity theory, this study sought to identify risk and protective factors associated with identity theft victimization and determine whether individual-level behaviors, including frequency of online purchasing and data protection practices, are determinative of victimization. Data from sequential administrations of the U.S. National Crime Victimization Survey–Identity Theft Supplement (ITS) in 2012 and 2014 were combined (N = 128,419). Using multivariable logistic regression, risk and protective factors were examined for three subtypes: 1) unauthorized use of existing credit card/bank accounts, and unauthorized use of personal information to 2) open new accounts, or 3) engage in instrumental activities (e.g., applying for government benefits, receiving medical care, filing false tax returns). Existing credit card/bank accounts and new accounts identity theft victimization were associated with higher levels of online purchasing activity and prior identity theft victimization. All identity theft subtypes were associated with government/corporate data breaches and other crime victimization experiences. Routine individual-level preventive behaviors such as changing online passwords and shredding/destroying documents were protective. Identity theft subtypes showed divergent socio-demographic risk/protective profiles, with those of higher socioeconomic status more likely to be victims of existing credit card/bank account identity theft. Identity theft is a pervasive, growing problem with serious health and psychosocial consequences, yet individuals can engage in specific protective behaviors to mitigate victimization risk.

1. Introduction

Identity theft – defined as the intentional, unauthorized use of a person’s identifying information for unlawful purposes ( Federal Trade Commission, 1998 , Koops and Leenes, 2006 ) – is a growing public health problem. While identity theft is not a new crime, the magnitude of the problem has increased with society’s growing reliance on the electronic transfer and storage of personal information across all forms of commerce and services. Approximately 10% of U.S. adults experienced identity theft in 2016, up from 7% in 2012 ( Harrell, 2019 ), and consumer agencies have seen recorded complaints about identity theft increase almost five-fold since 2001 ( Federal Trade Commission, 2017 ). Even routine, mandatory interactions with government (e.g., filing taxes) and healthcare systems (e.g., health records) involve the online transfer and storage of highly identifiable information, such as social security and medical ID numbers, expanding opportunities for identity thieves to illegally obtain personal information ( Myers et al., 2008 ).

In addition to the rising incidence of identity theft, there is growing recognition of the negative emotional and physical health consequences of financial crimes. One in 10 identity theft victims, roughly 2.6 million people, reported experiencing severe emotional distress following victimization ( Harrell, 2019 ). A quarter of identity theft victims experienced sleep problems, anxiety, and irritation six months after the crime ( Sharp et al., 2004 ), with older adults and minorities experiencing more severe emotional consequences including depression, anger, worry, and sense of vulnerability ( Golladay and Holtfreter, 2017 ). While not specific to identity theft, Ganzini and colleagues ( 1990 ) found significantly higher rates of depression and anxiety among financial crime victims compared to demographically-matched controls. Financial crimes have also been associated with increased rates of hospitalization ( Dong and Simon, 2013 ) and all-cause mortality ( Burnett et al., 2016 ). Identity theft also diminishes public confidence in government and corporate entities, prompting increasingly restrictive access to government databases designed to promote public health research ( Wartenberg and Thompson, 2010 ).

The large number of high-profile data breaches in the 21st century (e.g., Equifax, Yahoo, Anthem, U.S. Office of Personnel Management) introduce the question of whether individual-level characteristics and behaviors affect the risk of identity theft victimization, or whether victimization risk is entirely contingent on corporate and government-level data security practices. Combining 2012 and 2014 data from the Bureau of Justice Statistics’ (BJS) nationally representative National Crime Victimization Survey – Identity Theft Supplement (NCVS-ITS), the current study provides a comprehensive examination of identity theft victimization risk and protective factors across three major identity theft subtypes: 1) Unauthorized use of existing credit card(s) and/or bank account(s) and; Unauthorized use of personal information to 2) open new account(s); or 3) engage in instrumental activities. Although the BJS provides basic descriptive and bivariate statistics from the NCVS-ITS with a focus on socio-demographic variables, a multivariable analysis is necessary to identify whether individual-level online routines and lifestyle behaviors affect the probability of victimization above and beyond risk factors that are largely outside of an individual’s control, such as corporate/government-level data breaches. Only through this more comprehensive analysis that isolates the impact of individual behaviors after controlling for other factors can we begin to understand where to effectively allocate security resources to help reduce the frequency and consequences of identity theft. In contrast to BJS reports that combine both “attempted” and “actual” cases of identity theft in analysis, the current study focuses on identity theft victimization and, therefore, includes only cases of actual identity theft (excluding attempted cases).

2. Theoretical framework

The current paper draws on lifestyle-routine activity theory (L-RAT; Cohen and Felson, 1979 , Hindelang et al., 1978 ) which proposes that individual lifestyles and routine activities influence the risk of crime victimization to the extent that they bring a potential target into contact with offenders or affect the availability of protective measures to prevent the crime ( Cohen et al., 1981 , Miethe and Meier, 1990 , Hindelang et al., 1978 ). L-RAT originally described crimes involving direct victim-perpetrator contact, such as assault and robbery, yet the theory has been modified for application to internet-based crimes in which the victim and perpetrator do not physically or necessarily instantaneously converge, including financial fraud ( Pratt et al., 2010 ) and identity theft ( Reyns, 2013 , Reyns and Henson, 2016 ).

According to L-RAT, individuals with greater visibility to offenders in unguarded/un-protected settings are more likely to be victimized ( Cohen et al., 1981 ). In the context of cyber crimes, online activity could expose a person’s identifying information to offenders if the device is infected with malware, hacked, or personal data is entered into an unsecure website. Identity theft research has generally supported the hypothesis that engagement in routine online commercial activities, such as banking, shopping, emailing/instant messaging, selling goods, downloading media, or higher overall levels of internet usage, is associated with victimization ( Holtfreter et al., 2014 , Reyns, 2013 , Reyns and Henson, 2016 , Williams, 2016 ). Yet beyond individual online activities, data breaches targeting retailers, healthcare insurers/providers, and government entities that store and transfer personal information may also increase risk of identity theft.

Previous studies examining L-RAT and criminal behavior have found that routine activities account for a substantial portion of the association between crime and socio-demographic characteristics ( Osgood et al., 1996 ). It is unknown whether identity theft victimization is correlated with demographic and socioeconomic characteristics—age, income, education, race, residential setting—given that personal information is often obtained through online channels with no direct victim-perpetrator contact. Yet these characteristics influence socio-cultural lifestyles and patterns of consumption that affect how often individuals use their identifying information and for what purposes. Previous researchers have found a positive relationship between income, educational attainment, and identity theft victimization ( Anderson, 2006 , Reyns, 2013 , Reyns and Henson, 2016 , Williams, 2016 ).

Prior studies have inconsistently found that both females ( Anderson, 2006 ) and males ( Holtfreter et al., 2014 , Reyns, 2013 ) are at greater risk of identity theft victimization. Similarly, different studies have shown that younger adults ( Williams, 2016 ), middle-aged adults ( Harrell, 2015 ), and older adults ( Reyns, 2013 ) are at increased risk of victimization. Rather than considering age as a continuous variable or according to arbitrary cut-offs, the current study examined age according to generational cohorts, which may be more indicative of age-cohort-related lifestyles and routine activity trends. The study also examined age and gender risk profiles separately for each identity theft subtype, as differences in how information is obtained and misused could explain previous mixed findings.

According to L-RAT, people with greater measures of protection or security, including social, physical, or safety measures are at lower risk of victimization ( Cohen et al., 1981 , McNeeley, 2015 , Wilcox et al., 2007 ). In the context of identity theft, behaviors such as installing antivirus software, shredding documents, and routinely changing passwords theoretically reduce opportunities for identity thieves to access personal information. This has received mixed results in the identity theft literature. Reyns and Henson (2016) found that protective computer/internet-based behaviors, such as use of antivirus software, deleting emails from unknown senders, and regularly changing passwords, were not related to identity theft victimization. Williams ( 2016 ) found that some security measures (using only one computer, filtering spam email, installing antivirus software and secure browsing) were associated with lower identity theft victimization, while other measures (changing security settings and passwords) were associated with greater victimization. However, existing identity theft research is limited by study designs that have been unable to determine whether reported protective behaviors were enacted as a general precautionary measure (prior to) or in response to (following) identity theft victimization. The current study only considered protective behaviors reported as general preventive measures and excludes protective behaviors enacted in reaction to a victimization experience.

This study combined cross-sectional data (n = 128,419) from a rotating panel design of consecutive, directly comparable 2012 (n = 64,132) and 2014 (n = 64,287) administrations of the NCVS-ITS ( U.S. Department of Justice, 2012 , U.S. Department of Justice, 2014 ). The broader NCVS study used a two-stage, stratified cluster sample design, representing all U.S. residents age 12 years or older living in housing units or group quarters. The ITS surveys were administered to eligible respondents age 16 or older at the end of their NCVS interviews using computer-assisted personal or telephone interviewing. While the ITS survey collected only data about respondent experiences with identity theft, respondents’ demographic data and their experiences with other types of crime victimization were collected through the broader NCVS survey. The overall NCVS-ITS unit response rates for NCVS households, NCVS persons, and ITS persons in 2012 and 2014 were 68.2% and 66.1%, respectively. Selection bias analysis found little or no bias to ITS estimates due to non-response ( Inter-University Consortium for Political and Social Research, 2012 , Inter-University Consortium for Political and Social Research, 2014 ). Data were weighted to be nationally representative but adjusted back to reflect the original sample size and avoid inflated p-values. Further details on NCVS-ITS methods can be found at www.bjs.gov ( Bureau of Justice Statistics, 2014 ).

3.2. Dependent variables

Consistent with empirically derived recommendations to maximize sensitivity and reduce respondent under-reporting in financial exploitation prevalence research ( Burnes et al., 2017 ), the NCVS-ITS measured identity theft victimization using a series of contextually oriented questions describing specific sub-categories, rather than a single, general self-report assessment question. Dependent identity theft variables include the unauthorized use of: 1) existing credit card and/or bank accounts; 2) personal information to open new accounts (e.g., financial, investment, utilities); and 3) personal information for instrumental purposes (e.g. filing false tax returns, obtaining medical services, applying for a job or government benefits). Because the mechanisms of identity exposure and the purposes of identity misuse differ across these three categories, risk and protective factors were assessed separately in the analysis. Victimization status was limited to respondents reporting identity theft within the previous year (1 = yes, 0 = No).

3.3. Independent variables

3.3.1. risk factors.

Potential risk factors for identity theft included: 1) frequency of online purchasing behavior in the past year (none, up to once per month, up to once per week, up to once per day, more than once per day); 2) prior year breach of personal information stored by a company or government (no = 0, yes [but social security number not exposed] = 1, yes [social security number exposed] = 2); 3) number of other forms of victimization experienced in the past year, such as theft and assault (continuous); and 4) whether the respondent experienced prior identity theft victimization during lifetime (yes = 1, no = 0).

3.3.2. Protective factors

Respondents were asked a series of seven questions (no = 0/yes = 1) designed to capture identity theft-related preventive/protective practices within the previous 12 months. The questions asked about the following behaviors: checked credit report; changed passwords on financial accounts; purchased credit monitoring services or identity theft insurance; shredded or destroyed documents containing personally identifying information; checked bank or credit card statements for unfamiliar charges; used computer security software; or purchased identity theft protection services. An affirmative response to each question triggered a follow-up question asking whether the behavior was enacted in response to a misuse of personal information. To address issues of temporal ordering as it relates to routine protective behaviors, respondents who indicated that a behavior was enacted in response to a victimization event in the past 12 months were coded as a “no” for the preventive behavior. To understand whether the seven binary protective practice items loaded onto one or more dimensional factors, a multiple correspondence analysis (MCA) was conducted, which analyzed the underlying structure of the binary/categorical data ( Greenacre & Blasius, 2006 ). As illustrated in the discrimination measures plot ( Appendix A ), two factors emerged based on whether the protective item was purchased or reflected a routine protective behavior. The purchased factor contained two items—credit monitoring services/identity theft insurance and identity theft protection services. The routine protective behavior factor had five items—checked credit report, changed passwords, shredded/destroyed documents, checked bank/credit card statements, used computer security software. These purchase and routine protective behavior variables (continuous) were entered separately into the models.

3.3.3. Controls

Age was operationalized according to generational cohorts to reflect age-related lifestyles that could impact exposure to identity theft: millennials (born 1981–1998), Generation X (born 1965–1980), baby boomers (born 1946–1964), and Silent/Greatest (born before 1945) ( Pew Research Center, 2016 ). Additional socio-demographic characteristics included gender (male/female), marital status (married/partnered vs. not married/partnered), education (high school or less, some college, college degree, advanced degree), annual household income ($0–24,999, $25,000–49,999, $50,000–74,999, $75,000 or more), and race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, non-Hispanic Asian American/Pacific Islander/American Indian/Alaska Native [AAPI/AIAN], other). Other control variables included residential setting (urban, rural) and survey administration mode (in-person, telephone).

3.4. Analytic plan

Risk and protective variables and controls were regressed on each subtype of identity theft using multivariable logistic regression. Model fit was tested using the Omnibus Test of Model Coefficients and the Hosmer-Lemeshow Test. Tolerance and variance inflation factor statistics were used to test for multicollinearity in regression models. The existing credit card/ bank account analysis was limited to respondents who reported having a credit card or bank account. Missing data were managed with a fully conditional specification multiple imputation method using five pooled data sets. Analyses were performed using IBM SPSS version 25. Due to the large sample size, a p-value of less than 0.001 was considered statistically significant.

Table 1 provides a description of the weighted sample of victims across identity theft subtypes. Across identity theft subtypes, victims were proportionally more female, Caucasian, belonged to the Baby Boomer generation, and lived in urban settings. Whereas victims of existing credit card/bank account identity theft tended to belong to higher income households, victims of new accounts and instrumental purposes identity theft tended to belong to lower-income households.

Descriptive characteristics of weighted (sample-size-adjusted) victim samples across identity theft victimization subtypes.

Table 2 presents the prevalence of identity theft victimization overall and by subtype. The prevalence of overall identity theft victimization (any type) was 6.2% in the combined 2012/2014 sample (95%CI = 6.0%–6.3%). The most common form of victimization was existing credit card or bank account identity theft, with a prevalence of 5.6% (95%CI = 5.5%–5.8%).

Identity theft victimization frequencies.

4.1. Risk factors

Table 3 presents results from the multivariable analysis of risk and protective factors of identity theft victimization for each subtype. Higher levels of online purchasing behavior were significantly associated with increasing odds of existing credit card/bank account and new accounts identity theft victimization; those engaging in daily online shopping were more than five times as likely to be victims of existing credit card/bank account identity theft as those not engaging in online purchasing (OR = 5.74, 95%CI = 4.31–7.64). Persons reporting breached personal information from a company or government were significantly more likely to experience identity theft, particularly if social security information was exposed (instrumental purposes: OR = 8.05, 95%CI = 5.66–11.46; new accounts: OR = 3.83, 95%CI = 2.67–5.51; existing credit/bank account: OR = 1.46, 95%CI = 1.26–1.68). Those reporting other NCVS victimizations were between 29% (existing credit/bank account: OR = 1.29, 95%CI = 1.23–1.35) and 46% (new accounts: OR = 1.46, 95%CI = 1.32–1.62) more likely to be victims of identity theft with each successive crime. Individuals with a history of identity theft victimization were 28% more likely to be victimized by existing credit/bank account identity theft in the past year than those with no prior history (OR = 1.28, 95%CI = 1.19–1.37).

Multivariable logistic regression models predicting identity theft victimization.

Note: All multivariable logistic regression models, except the New Accounts model, satisfied the Omnibus Test of Model Coefficients (p < 0.01). All multivariable logistic regression models satisfied the Hosmer-Lemeshow Test (p > 0.05). Across models, independent variables had tolerance of 0.70 or above and variance inflation factor of 1.43 or below, indicating no concern of multicollinearity.

CI = Confidence interval; OR: Odds ratio; SSN: Social Security Number; AAPI/AIAN = Asian American/Pacific Islander/American Indian/Alaskan Native. ***p < 0.001, (two-tailed tests).

4.2. Protective factors

Individuals engaging in a higher number of proactive, routine protective behaviors, such as shredding documents and updating passwords, were between 25% (existing credit/bank account: OR = 0.76, 95%CI = 0.75–0.78) and 35% (new accounts: OR = 0.66, 95%CI = 0.61–0.71) less likely to experience identity theft victimization with each additional protective behavior. Purchasing credit monitoring services and identity theft insurance, however, was associated with significantly higher odds of new accounts (OR = 1.62, 95%CI = 1.28–2.06) identity theft.

4.3. Socio-Demographic controls

Across all identity theft subtypes, baby boomers were most likely to be victims (existing credit/bank account: OR = 1.38, 95%CI = 1.29–1.48; new accounts: OR = 1.70, 95%CI = 1.32–2.20; instrumental: OR = 1.79, 95%CI = 1.32–2.42). Unmarried/un-partnered persons were 63% (OR = 1.63, 95%CI = 1.28–2.09) more likely to experience instrumental forms of identity theft. Higher levels of education were associated with increasingly higher odds of both existing credit card/bank account and new accounts forms of identity theft. Compared to non-Hispanic whites, existing credit/bank account victimization was less likely among Hispanic (OR = 0.85, 95%CI = 0.78–0.93), Black (OR = 0.78, 95%CI = 0.71–0.86), and AAPI/AIAN (OR = 0.78, 95%CI = 0.70–0.87) persons. Persons living in households in the highest income bracket were most likely to experience existing credit/bank account identity theft (OR = 1.38, 95%CI = 1.25–1.52) compared to those in the lowest income households. As a methodological finding, respondents who participated in a telephone rather than in-person interview were significantly less likely to report identity theft victimization.

5. Discussion

Approximately 1 out of every 15 adults aged sixteen years or older in the U.S. – over 16 million people – experience some form of identity theft each year. In addition to direct losses, consequences may include damaged credit, legal fees, loss of trust, and health outcomes such as stress, anxiety, and depression ( Harrell, 2015 , Golladay and Holtfreter, 2017 ). Among victims who experienced the misuse of personal information for instrumental purposes, approximately 56% suffered moderate to severe distress, a similar percentage as seen among victims of violence ( Harrell, 2015 ).

As large-scale data breaches have become an unfortunate part of our growing tech-based marketplace, this analysis examined whether online purchasing behavior and personal data security practices affect the risk of identity theft victimization, or whether becoming a victim is largely contingent on corporate and government-level data breaches. Findings provide support for the L-RAT model of victimization which suggests that individual lifestyle routines and degree of protective measures/guardianship influence the likelihood of victimization.

Respondents who stated that their information was part of a large data breach were significantly more likely to report all forms of identity theft, particularly when their social security numbers were exposed. Victims of identity theft for instrumental purposes were eight times as likely to say their social security numbers were exposed in a data breach compared to non-victims, likely because that form of identity theft requires social security numbers to access government benefits and other services. Although it is not possible to assess whether data breaches directly caused identity theft incidents, data breaches were significantly correlated with the misuse of identity information.

L-RAT proposes that routine lifestyle behaviors contribute to crime victimization risk. In the present study, individual risk and protective behaviors were consistent and strong (magnitude) predictors. Similar to findings using a Canadian sample ( Reyns & Henson, 2016 ), increasing levels of online purchasing activity were associated with incrementally higher odds of financial account and new account identity theft. Participating in commercial activities online reflects a major societal innovation and lifestyle shift that has allowed consumers to purchase products conveniently and globally, but entering personal data online entrusts vendors to safely store and manage this data. For example, Holtfreter et al. (2015) found that individuals who placed an order with a company they had never done business with before were significantly more likely to be victims of identity theft. While the NCVS ITS does not ask respondents what online retailers they have made purchases from, it is likely that as the frequency of online shopping increases, the odds of using an unsecured payment portal or having information exposed in a retail data breach increases. Further innovations in online security and payment systems are required to protect users’ information, and future research should explore precisely how online purchasing activities expose personal information.

In support of the guardianship principle of L-RAT, proactive individual behaviors, like shredding personal documents and routinely changing account passwords, significantly reduced the likelihood of identity theft. Unfortunately, the Pew Research Center ( Olmstead & Smith, 2017 ) found that half of U.S. respondents were not educated about everyday security practices. Given that routine safety behaviors reduce risk of identity theft, consumer protection efforts need to focus on educating consumers on the basics of online security. Purchasing external credit monitoring and identity theft protection services did not reduce risk and was related to greater likelihood of new accounts identity theft victimization. Perhaps respondents who purchased these services had some knowledge that their identity may be misused. Another explanation is that some criminal entities have reached a level of sophistication to evolve techniques ahead of current industry protection standards ( Moore et al., 2009 ).

This study found that exposure to other types of crime, as well as prior experiences with identity theft, were associated with a greater risk of identity theft victimization. Personal information may be stolen during the course of other crimes directly (e.g., theft of wallets, bank statements) or indirectly through theft of devices that contain personal information. This result is consistent with financial fraud research—prior fraud victimization increases the odds of re-victimization ( Titus et al., 1995 ). An underground system exists for identity theft where specified pieces of stolen identifying information are bundled and sold to other criminals, thereby increasing the odds that it is used for various identity crimes over time ( Moore et al., 2009 ). Services for identity theft victims should include help contacting the major credit bureaus to place a temporary freeze or fraud alert on credit reports to prevent criminals from opening new accounts with victims’ stolen credentials.

The socioeconomic and demographic risk patterns found in this study were roughly consistent with the predictions of L-RAT. In general, members of Generation X and the baby boomers, now between the ages of 39 and 73, were at the highest risk of most types of identity theft. This likely reflects the socioeconomic capacity and consumption patterns among Generation X and baby boomers relative to millennials. Together, these older generations constitute the bulk of the U.S. workforce and, therefore, have the economic means to engage in consumer activities where identities may be exposed. Longitudinal data is needed to determine whether the association between middle to late adulthood and increased risk of identity theft is indeed due to lifestyles or whether age has an independent effect.

Compared to Hispanic, Black, and Asian respondents, White respondents and those with higher educational attainment experienced significantly higher risk of existing credit card/bank account identity theft. Individuals with higher socioeconomic status have more purchasing power ( Charron-Chénier et al., 2017 ), have more access to credit ( Haushofer & Fehr, 2014 ), own more internet-enabled devices that store and transfer personal information, and are more likely to use credit cards ( Greene & Stavins, 2016 ). In support of L-RAT, this suggests that the association between existing credit card/bank account identity theft and demographic/socioeconomic profiles is related to lifestyle factors where there is greater reliance on these financial instruments, and thus more opportunities for criminals to intercept account information.

5.1. Limitations

While the NCVS Identity Theft Supplement is one of the most comprehensive sources of data on identity theft, the survey likely underestimates the true extent of the problem. First, the NCVS excluded adult sub-populations who may be particularly vulnerable, such as those living with cognitive impairment and/or in institutional settings. Second, the literature on financial fraud victimization finds that people tend to under-report victimization in survey research ( Beals et al., 2015 ), and this self-report error likely extends to the issue of identity theft. Finally, the nonresponse group is likely disproportionately represented by victims who are reluctant to provide personal information in response to a survey. Another limitation of the study was that data on other potentially important behavioral variables, such as the extent of online downloading, online financial account management, types of websites visited, and presence of malware, hacking or phishing events, were unavailable. To better understand risk of identity theft victimization within the L-RAT paradigm, measures are needed to account for system-level security practices among corporate and government entities, but this is beyond the scope of the NCVS.

5.2. Health implications

Identity theft victimization affects tens of millions of Americans each year. Financial exploitation, in general, is associated with major health-related consequences such as increased rates of hospitalization and all-cause mortality. Victims of identity theft experience severe mental/emotional distress, particularly among minority and older adult populations ( Harrell, 2019 , Golladay and Holtfreter, 2017 ). Given the increasing scope of this problem, the development of effective primary prevention strategies is critically needed and should focus on promoting relatively unintrusive and feasible everyday practices such as routinely changing financial account passwords, shredding documents, and checking credit reports and financial statements. The prevalence of this problem indicates that healthcare professionals will encounter patients who are victimized by identity theft on a regular basis. Healthcare settings represent an important place to both recognize vulnerable adults and provide victims with preventive education to mitigate the risk of identity exposure.

6. Conclusion

This study comprehensively examined the risk of different forms of identity theft victimization in the U.S. Although other research indicates that Americans have inadequate knowledge of cybersecurity practices ( Olmstead & Smith, 2017 ), findings from the current study demonstrated the importance of this knowledge in keeping personal information safe. Yet individual actions alone are not enough. As investment in cybersecurity grows, criminals respond with increasingly sophisticated and evolving techniques such as hacking, malware, and skimming to overcome these controls ( Pontell, 2009 ). Reducing the incidence of identity theft requires greater public/private investment in robust, dynamic data security systems and encryption tools, and more collaboration between criminal justice and law enforcement agencies to investigate and prosecute identity theft crimes.

CRediT authorship contribution statement

David Burnes: Conceptualization, Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Marguerite DeLiema: Conceptualization, Writing - original draft, Writing - review & editing. Lynn Langton: Conceptualization, Methodology, Writing - original draft, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix B Supplementary data to this article can be found online at https://doi.org/10.1016/j.pmedr.2020.101058 .

Appendix A. 

Multiple Correspondence Analysis Discrimination Measures Plot.

Appendix B. Supplementary data

The following are the Supplementary data to this article:

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• Economic Sociology
• Identity theft

Cybercrime -Identity Theft

• December 2020

• Swinburne University of Technology

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• Systematic review
• Open access
• Published: 10 February 2024

Identity fraud victimization: a critical review of the literature of the past two decades

• Yasemin Irvin-Erickson   ORCID: orcid.org/0000-0002-1467-5960 1  

Crime Science volume  13 , Article number:  3 ( 2024 ) Cite this article

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This study aims to provide an understanding of the nature, extent, and quality of the research evidence on identity fraud victimization in the US. Specifically, this article reviews, summarizes, and comments on the state of empirical research of identity fraud victimization in the US based on a narrative review of 52 published empirical studies. Studies included in this review suggest that the prevalence of identity fraud in the US has increased over the years and existing account frauds is the most prevalent type of identity fraud. There is a pressing need for more research on the prevalence of identity fraud victimization among minors, institutionalized individuals, and individuals from minority groups; long-term prevalence of identity fraud victimization; and emerging forms of identity fraud such as synthetic identity fraud victimization. Studies included in this review further suggest that identity fraud risk factors vary based on the fraud type considered. Identity fraud victims can experience a variety of harms. Longitudinal studies following identity fraud victims are essential for reliably estimating the risk factors for identity fraud victimization and the impact of identity fraud victimization on individual victims. The research on services for identity fraud victims is limited and suggests the positive impact of trauma-informed services for serious identity fraud victims. The overwhelming lack of research on the impact of programs and services for identity fraud victims necessitates more attention from scholars to study the impact of programs, interventions, and services for identity fraud victims on reporting of victimization, prevention of victimization, experiences of victims, and victim-centered cost benefit analysis of services. Policy and practice implications of these findings are discussed.

Identity theft and associated frauds have increasingly attracted public attention in the United States (US) with highly publicized data breaches and millions becoming victims of this crime every year. Efforts to educate the public about identity theft have raised attention to the risks of identity theft and fraud, however, an in-depth exploration of identity fraud victimization is needed to further the field’s and the public’s understanding of this crime.

Despite the comparatively scant evidence on identity theft in the field of criminology, the research on identity theft in the US has started picking up speed in the past decade with the availability of nationally representative data on this topic through the Bureau of Justice Statistics’(BJS) National Crime Victimization Survey Identity Theft Supplement (NCVS-ITS). The NCVS is the US’s primary data source on victimization since 1972. The NCVS is administered to non-institutionalized individuals who are 12 years old or older from a nationally representative sample of households in the US. The ITS is a supplemental survey to the NCVS which is administered to the respondents to the NCVS survey who are 16 years old or older. The ITS was first implemented in 2008 and gets fielded approximately every two years. This leading national level data source on identity theft victimization asks respondents if they had been victims of different forms of identity theft in the past 12 months and beyond the past year and the characteristics and consequences of victimization and help-seeking behavior if respondents indicate they had been victims of identity theft.

There has been a few review studies on the state of the US literature on identity theft through funding by the Department of Justice offices. For instance, the first literature on identity theft by Newman and McNally ( 2005 ) funded by the National Institute of Justice explored what is known about identity theft and the knowledge gaps based on their review of publications of different organizations, complaint data, less than 10 surveys conducted by different organizations, and a handful of research studies published at the time of that review. Another review study by Irvin-Erickson and Ricks ( 2019 ) funded by the Office for Victims of Crime examined the state of the literature on fraud victimization based on research evidence from academic and non-academic sources and practice evidence sources (such as fact sheets, podcasts, and other sources that are not traditionally considered in reviews) published between 2000 and 2018. This study expands upon the aforementioned reviews by considering not only the scope of the literature on identity theft victimization published in the past two decades but also the quality of conduct of these studies to provide a broad yet nuanced understanding of the state of the literature on this topic and the knowledge gaps. Although the aforementioned reviews provided invaluable information about the opportunity structure, risks, and consequences of identity theft victimization and the needs of identity theft victims, similar to other traditional narrative reviews of the literature in the grey literature, these reviews did not include risk of bias and quality assessments of the sources of evidence included in these reviews. The current study fills this critical knowledge gap in our understanding of the state of the literature on identity fraud victimization through consideration of the risk of bias and the quality of each study included in this review.

Despite the increase in the number of studies on the topic of identity theft victimization over the past decade, the evidence base on identity theft victimization is still limited. Accordingly, this review did not follow the format of a systematic review and instead followed steps similar to a scoping review to gain an understanding of the nature, extent, and quality of the research evidence on identity fraud victimization. Specifically, this review aimed to answer the following questions to present the size, scope, and quality of the emerging evidence base on identity fraud victimization:

What are the trends in the US literature on identity fraud victimization?

What do we know from the US literature on identity fraud victimization?

What are the topics most and least commonly studied in the literature on identity fraud victimization?

What are the risks of bias associated with existing studies?

What do studies with lower risk of bias and/or higher quality demonstrate about key concepts studied by these studies?

What are the knowledge gaps in the US literature on identity fraud victimization?

By answering these questions, this review primarily aims to provide suggestions for future research on identity fraud victimization including potential research questions for future systematic reviews as the evidence base on this topic becomes denser at which point researchers can conduct larger knowledge syntheses. Accordingly, although risk of bias and quality of studies are assessed for each study included in this review, a meta-analysis or statistical pooling of studies has not been performed.

Definitional issues regarding identity theft

There is an increased interest in the field to differentiate between the terms of identity theft and identity fraud because not all identity theft incidents involve a fraudulent act at the time of theft of personal information. Javelin Strategy and Research (2021) defines identity theft as “unauthorized access of personal information” and identity fraud as identity theft incidents in which there is an element of financial gain. The Federal Trade Commission (FTC) and the BJS define identity theft as “fraud that is committed or attempted using a person’s identifying information without authority” (FTC, 2004 ; Harrell, 2019 , p. 18). The acts considered by the BJS under this definition include unauthorized use or attempted use of an existing account, unauthorized use or attempted use of personal information to open a new account, and misuse or attempted misuse of personal information for a fraudulent purpose (Harrell, 2019 ).

Researchers differentiated between three stages of identity theft: acquisition of personal information, use of personal information for illegal financial or other gain, and discovery of identity theft (Newman & McNally, 2007 ). Personal information can be acquired through different means ranging from simple physical theft to more complex and even legal ways such as scams, cyber, or mechanical means and purchasing the information from data brokers. The acquired personal information is used for financial gain or other criminal purposes (Newman & McNally, 2007 ). However, fraudulent use of information might not happen at the time of acquiring of information and once personal information is exposed, a person can become an identity theft victim multiple times.

Another important stage of identity theft is the discovery of theft of personal information and associated frauds because the longer the discovery period is the less likely it is for victims to contact law enforcement (Randa & Reyns, 2020 ) and the more likely it is for them to experience aggravated consequences (Synovate, 2007 ). Police reports are critical for victims to pursue an identity theft case (OVC, 2010 ). For victims of certain forms of identity theft, the discovery of victimization can take as long as 6 months or more (Synovate, 2003 , 2007 ). In cases where personal information is exposed due to data breaches, victims might have greatly varying experiences of when and what they learn about this exposure (if at all) and the services available to them. Currently, all 50 states, the District of Columbia, Guam, Puerto Rico, and the Virgin Islands have laws requiring businesses, and in most states, government organizations to notify individuals of security breaches involving personal information (National Conference of State Legislatures, 2022 ). However, the decisions of organizations on whom to notify (such as the victims, the FTC, or law enforcement), when to notify, and how to notify can drastically vary from one geography to another based on laws. Two groups can become targets of identity fraud: individuals whose personal information is stolen and organizations which are in care of the stolen personal information or which become targets of fraud. Law enforcement might be more likely to put emphasis on organizations as visible and collective targets of identity theft (Newman & McNally, 2005 ).

In recognition of the stages and targets of identity theft, there has been an interest in the field to differentiate between the terms of identity theft and identity fraud. In popular knowledge, the terms “identity theft” and “identity fraud” have been used interchangeably considering the interrelated nature of acts considered under these terms. However, it is acknowledged that these terms legally refer to different things (Newman & McNally, 2005 ).

In statute, identity theft was legally defined at the federal level with the Federal Identity Theft and Assumption Deterrence Act (ITADA) of 1998 (Newman & McNally, 2005 ). ITADA made it a federal offense to “knowingly transfer or use, without lawful authority, a means of identification of another person with the intent to commit, or to aid or abet, any unlawful activity that constitutes a violation of Federal law, or that constitutes a felony under any applicable State or local law” (the Identity Theft Act; U.S. Public Law 105-318). Prior to this legal definition of identity theft in the US, the terms “identity theft” and “identity fraud” were used to primarily distinguish between the individual victims and collective victims with the former being referred to as victims of identity theft and the latter as victims of identity fraud (McNally & Newman, 2008 ). In later years, these terms have been used to differentiate between the act of unlawful acquisition of identity information and the fraudulent use of personal information.

Over the years, different research and practice sources have generally considered the following acts under identity theft and identity fraud: criminal identity theft in which individuals use others’ personal information during interactions with law enforcement or for committing other crimes (Button et al., 2014 ); existing account frauds where an individual makes unauthorized charges to existing accounts such as bank, credit card, and other existing accounts; medical/insurance identity theft in which an individual fraudulently uses somebody else’s personal information to receive medical care; new account frauds in which an individual’s personal information is used unlawfully to open a new account; social security number (SSN) related frauds in which an individual uses the victim’s SSN to file for a tax return, for employment, or to receive government benefits; and synthetic identity theft in which different pieces of real and fake identity information are combined together to create an identity and to commit frauds (Dixon & Barrett, 2013 ; FTC, 2017 , 2018 ; GAO, 2017 ; Pierce, 2009 ).

The opportunity structure for identity theft

Earlier research on perpetrators of identity theft, using a conceptual framework informed by Cornish and Clarke’s ( 1986 ) Rational Choice Theory and the methodology of crime script analysis, has focused on the motivations and methods of committing identity frauds (see Copes & Vieraitis, 2009 , 2012 ) and the impact of experiences of perpetrators’ on their criminal involvement and criminal event decisions (Vieraitis et al., 2015 ). Regarding the organizational level of identity frauds, research has shown that perpetrators of identity theft and fraud might range from individuals to street-level and more advanced criminal organizations (Copes & Vieraitis, 2009 , 2012 ; Newman & McNally, 2007 ). Although earlier research has shown that perpetrators of identity theft used low-technology methods (Copes & Vieraitis, 2009 , 2012 ), perpetrators of identity theft have started using more complex schemes and relying more heavily on the internet to acquire identity information over the years (Pascual et al., 2018 ).

The number of identity fraud victims who know the perpetrators has decreased over the years. For instance, in 2008, about 40% of identity fraud victims knew how the incident happened, and from those, about 30% believed that their information was stolen during a purchase or other interaction and 20% believed that their personal information was stolen from their wallet, 14% believed the information was stolen from files at an office, and another 8% believed that the information was stolen by friends or family (Langton & Planty, 2010 ). In 2012, about 32% of identity victims in the US knew how their personal information was stolen and 9% knew the identity of the perpetrator (Harrell & Langton, 2013 ). Comparatively, in 2018, 25% of identity fraud victims knew how the offender obtained the information and 6% of victims knew something about the perpetrator (Harrell, 2021 ). This unknown status of how the information is obtained or who the perpetrator is sometimes interpreted as the technology-facilitated nature of the acquisition of information (Newman & McNally, 2005 ). However, victims of instrumental identity theft in which an individual’s information is stolen to commit other frauds and crimes, and individuals who have been victims of multiple types of identity theft in the recent past, are more likely to know how their information was stolen and the perpetrator (Harrell, 2019 ). New research examining the impact of the pandemic on identity fraud further suggest an increase in identity fraud scams and loan fraud in which perpetrators directly target consumers and a significant portion of victims of identity fraud scams and loan fraud (about 3 in every 4 victims) knowing their perpetrators (Buzzard & Kitten, 2021 ).

The most frequent way identity theft victims become known to authorities in the US is complaints to financial institutions (Harrell, 2021 ). The other ways victims report their victimization include complaints to federal institutions [such as the FTC and the Internet Crimes Complaint Center (IC3)] and non-governmental organizations [such as the Identity Theft Resource Center (ITRC) and the National Consumers League (NCL)] and crime reports to law enforcement.

In the past decade, federal and non-profit organizations increased their efforts to educate consumers on risks and reporting of identity theft and how to deal with the ramifications of fraud victimization. Several federal and other organizations provide information for services victims can receive such as reporting and assistance hotlines, civil and criminal legal services, and trauma informed counseling. Other available responses to identity theft include credit and identity theft monitoring, identity theft insurance, and identity theft restoration; however, these responses are typically provided by for-profit companies. Depending on who the victim contacts, victims might not be uniformly informed about all options available to them. Many victim service providers working in organizations funded by the Victims of Crime Act do not have the resources to recognize and respond to fraud’s harms (OVC, 2010 ). Furthermore, even when services are available, there might be significant barriers against victims’ access to these resources including financial barriers. Currently, majority of services available to identity theft victims are geared towards handling out-of-pocket expenses.

At the time of this review, there was a fast evolving opportunity structure for identity theft and identity fraud due to the hardships inflicted on individuals by the economic and health crises. Direct stimulus payments, increased loan applications, and the overall increase in online activities during the pandemic have provided increased opportunities for identity frauds such as account takeovers (Tedder & Buzzard, 2020 ) and identity frauds in relation to scams (Buzzard & Kitten, 2021 ). Furthermore, low-income individuals, older individuals, individuals who depend on others for their care, and individuals who might not have control over their finances can experience aggravated harms as a result of identity fraud victimization. Furthermore, some victims might experience a significant damage to their reputations (Button et al., 2014 ). All of these conditions necessitate more scientific inquiry and a better understanding of existing research evidence base on identity fraud.

Scope of review

This review focuses only on identity fraud victimization and excludes studies that focus on theft of personal information but not the fraud aspect of identity theft. As an example, although skimming, intentional data breaches, and mail theft are acts of identity theft, if a research study focused solely on these acts but not the fraud aspect, that study was excluded from the review. The review further excluded research on identity frauds targeting organizations and governments, harms of identity fraud to businesses and institutions, and research studies focusing on victims in countries other than the US. The review also excluded sources in which no data collection and analysis was attempted, paid research content, and research summaries with limited or no information about methodology.

The current review included empirical research studies that focus on identity fraud victimization in the US which were published in English and between January 2000 and November 2021. The resources that were reviewed included journal articles, PhD dissertations, government reports, and other reports found in major social science research databases and on websites of organizations focusing on identity theft. This review adopted a broad definition of “empirical” research focusing on studies using both quantitative and qualitative data analysis methods including descriptive analysis.

In this review, a comprehensive search strategy was used to search the literature for relevant studies. The search strategy was consisted of (1) a formal search of academic databases using search strings based on Boolean operators Footnote 1 and (2) an informal search of grey literature using keyword searches and searches on the websites of organizations focusing on identity fraud. Searches were conducted in the following academic databases: Proquest Social Sciences Collection, Web of Science Social Sciences Citation Index, Wiley Online, JSTOR, Criminal Justice Abstracts, SocIndex Full text, and Violence and Abuse Abstracts. Additional searches were completed on the websites of the BJS, the Internet Crime Complaint Center (IC3), the FTC, the ITRC, Javelin, the National White Collar Crime Center (NW3C), and the Ponemon Institute.

299 potential studies were identified through database searches (excluding duplicate records) and 37 publicly available empirical studies were identified from websites of leading organizations on identity fraud. Ultimately, 29 sources from these database searches and 23 sources from the aforementioned organizations met the inclusion criteria for this review (see Appendix 1 for the screening process). These included articles are denoted with an asterisk (*) in the references section.

Appraisal of quality of studies

Studies included in this review were appraised for methodological quality. Quality appraisal was conducted after deeming a study eligible for the review based on the inclusion criteria specified earlier. Appendix 2 and Appendix 3 show the two quality appraisal tools that were adapted from Hoy et al. ( 2012 ) and Mays and Pope ( 2020 ). Each quantitative study was assigned into one of three categories based on the evaluation of risk of study bias: low, moderate, or high risk of bias. Each qualitative study was assigned into one of three categories based on the evaluation of quality: low, medium, or high quality. For the only mixed-method study in this review, risk of bias and study quality were evaluated separately for qualitative and quantitative elements of the study. More information about quality rating process and quality ratings of studies can be found in Appendix 4 and notes on bias and quality assessments for included studies can be found in Appendix 5.

Trends of identity fraud victimization research

Of the 52 studies included in this review, the majority were NGO reports (n = 22) followed by journal articles (n = 18), government reports (n = 7), and PhD dissertations (n = 5). Almost all of the white papers from government organizations and NGOs (n = 28) were descriptive quantitative studies. All of the white papers included in this review (n = 29) were based on survey data. Of the 23 academic studies (i.e., journal articles and dissertations) included in the review, 19 quantitative studies used surveys and 4 qualitative studies used interviews or focus groups discussions as their data source. Among these 23 academic studies, the primary data analysis method was regression analysis (n = 15) followed by descriptive quantitative data analysis (incidence, correlation, ANOVA analyses (n = 4), narrative analysis (n = 3), and phenomenological analysis (n = 1). Only one quantitative study included in this review used a quasi-experimental design with propensity score matching, and none of the quantitative studies included in the review had random assignment. The earliest journal article included in this review was published in 2006 and half of the journal articles included in this review (n = 9) were published between 2019 and 2021 (n = 9).

The studies in this review thematically fell into one or more of the following four areas of identity fraud victimization research: (1) prevalence, incidence, and reporting, (2) risk factors, (3) harms, and (4) prevention, programs, and services. From the 52 studies included in this review, 31 focused on harms, 22 focused on prevalence, incidence, and reporting, and 15 focused on risk factors. Notably, only 3 studies included in this review focused on services for identity fraud victims and among these studies there were no experiments with random assignment focusing on the effectiveness of specific programs or interventions for identity fraud victims (see Table  1 for subtopics and citations of identity fraud studies included in this review).

Prevalence, incidence, and reporting of identity fraud victimization

A significant number of studies included in this review (n = 22) focused on the extent and reporting of identity fraud victimization, however the majority of these publications (n = 13) were evaluated to have a high risk of bias. Nine of the 22 publications in this area which were evaluated to have lower risk of bias (i.e., low or moderate risk of bias), were based on nationally representative surveys by the BJS and the FTC.

Prevalence, incidence, and types of identity fraud victimization

National estimates.

Seven lower bias studies included in this review uniformly demonstrated that the incidence and prevalence of identity fraud victimization have increased between early 2000s and 2018, and misuse or attempted misuse of an existing account has been the most common type of identity fraud victimization over the years (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ; Synovate, 2003 , 2007 ).

The FTC, the first organization that collected national survey data on identity fraud based on phone surveys of US adults aged 18 and older in 2003 and 2006 estimated that approximately 10 million, or 4% of US adults, experienced identity fraud in the year preceding data collection (Synovate, 2003 , 2007 ). As indicated earlier, BJS has been collecting individual-level data on identity fraud since 2008. The 2008 iteration of the NCVS-ITS was significantly different than the later iterations of the NCVS-ITS conducted in 2012, 2014, 2016, and 2018. Results from the 2008 NCVS-ITS are not comparable to the results from the subsequent surveys. One important limitation of the NCVS-ITS is that it does not include individuals younger than 16 and individuals living in institutional and transient settings in its sample (Harrell, 2021 ). Another limitation of the NCVS-ITS is that although it was designed to distinguish between victims of attempted identity fraud and victims of successful frauds, the 2008 NCVS survey couldn’t successfully distinguish between the two (Langton & Planty, 2010 ). Accordingly, reports based on the NCVC-ITS fielded between 2008 and 2018 do not provide disaggregated statistics on these two groups.

The 2008 NCVS-ITS, despite being different than the 2003 and 2006 surveys of the FTC with regards to its shortest prevalence and the age interval of its study participants, similarly found that 11.7 million, or 5% of all persons aged 16 or older in the US, have been victims of at least one type of identity fraud in the two years preceding the survey (Langton & Planty, 2010 ). Later iterations of the NCVS-ITS highlighted a significant increase in the share of identity theft victims among persons aged 16 and older, especially after 2015. While the 2012 and 2014 NCVS-ITS estimated that approximately 7% of all persons aged 16 or older in the US had been victims of identity fraud in the past year (Harrell, 2017 ; Harrell & Langton, 2013 ), the 2016 and 2018 iterations of the NCVS-ITS estimated that approximately 10% and 9% of persons aged 16 or older in the US had been victims of at least one form of identity fraud in the past 12 months, respectively (Harrell,  2019 , 2021 ).

In the FTC and the BJS identity theft surveys, three main subcategories of identity fraud are captured: existing account frauds, new account frauds, and use of personal information to commit other frauds. The FTC and the BJS surveys over the years have showed that existing credit card frauds are the most prevalent form of identity fraud victimization (Harrell, 2017 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ; Synovate, 2003 , 2007 ). Notably, neither the FTC nor the BJS surveys captured synthetic identity frauds.

In the FTC and the BJS surveys, more detailed forms of identity frauds are captured under the main subcategories of existing account, new account, and other frauds. The FTC reports included in this review provided estimates on identity theft victims who had been affected by these detailed identity fraud categories (see Synovate, 2003 , 2007 ). For instance, according to the 2006 FTC identity theft survey, fraudulent use of credit cards (existing account frauds), opening of new credit cards (new account frauds), and use of personal information to commit other crimes (other frauds) were the most frequently experienced detailed fraud types under the three broad subcategories of identity fraud (Synovate, 2007 ). Although the NCVS-ITS also collects data on detailed forms of frauds under these three categories, neither the BJS reports nor the academic studies in this review based on the NCVS-ITS provided disaggregated information on detailed categories of identity fraud considered under “new account” and “other fraud” categories. However, publications based on the NCVS-ITS showed that, existing credit card frauds is the most prevalent existing account fraud subcategory followed by bank account and other existing account frauds (Harrell, 2017 , 2019 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ).

Currently, surveys from the Ponemon Institute, which were classified to have high risk of bias, provide the most in-depth insights into medical identity fraud. In Ponemon surveys, medical identity fraud is defined as the use of an individual’s personal identity to fraudulently receive medical service or prescription drugs and goods, including attempts to commit fraudulent billing (Ponemon Institute, 2011 ). The number of US adult individuals who experienced medical identity fraud at some point in time increased from 1.49 million in 2011 to 2.32 million in 2014 (Ponemon Institute, 2011 , 2012 , 2013 , 2015 ). Lastly, another study with high bias risk by Navarro and Higgins ( 2017 ) found that among victims of familial identity fraud (identity frauds committed by family members), the most frequent type of identity fraud experienced was misuse of personal information for instrumental frauds such as government benefit frauds.

Although there is a recall bias associated with using cross-sectional surveys to capture distant past experiences, data from the FTC and the BJS surveys also provide important information about individuals’ exposure to multiple forms of identity theft and their repeat victimization. In 2003, the FTC estimated the 5-year prevalence rate of identity fraud victimization among US adults to be 12.7% (Synovate, 2003 ). In 2012 and 2014, the NCVS-ITS estimated that about 14% of individuals aged 16 and older experienced at least one incident of identity fraud in their lifetime (Harrell, 2017 ; Harrell & Langton, 2013 ). Analyses based on the two most recent iterations of the NCVS-ITS further show that nearly 1 in 5 persons aged 16 and older experienced identity fraud in their lifetime (Harrell, 2019 , 2021 ).

Data from the NCVS-ITS further show that number of identity fraud victims who experienced multiple types of identity fraud victimization in a single incident decreased between 2016 and 2018 and majority of multiple identity fraud victims in a given year experienced fraudulent use of a combination of existing accounts (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). According to the 2008 NCVS-ITS, about 18% identity fraud victims experienced multiple types of identity fraud during their most recent victimization in the past year. Studies based on the 2012, 2014, 2016 iterations of the NCVS-ITS estimated that approximately 8% of victims experienced multiple types of identity fraud during a single incident (Harrell, 2017 , 2019 ; Harrell & Langton, 2013 ). According to the 2018 NCVS-ITS, only 6% of the identity fraud victims experienced multiple identity victimization in the past year (Harrell, 2021 ).

Subnational estimates

Publications by the AARP included in this review, which were evaluated to have a high risk of bias due to several design issues (see Appendix 5), showed that 15% to 30% of individuals who participated in the AARP surveys in Colorado, Minnesota, Montana, Oklahoma, Washington, and West Virginia have been victims of identity fraud or knew someone who has been victim of identity fraud in the past 5 years (see Binette, 2004 ; Burton, 2008 ; Dinger, 2006 ; Sauer, 2005 , 2010 ; Silberman, 2004 ).

Discovery of identity fraud victimization

Although majority of identity fraud victims discover their victimization quickly, some victims, and especially victims of new account frauds and other frauds, might be more likely to have a long discovery period (Synovate, 2003 , 2007 ). FTC surveys estimated that for 33% to 40% of all identity fraud victims, it took less than one week to discover that their personal information was misused (Synovate, 2003 , 2007 ). The same surveys further found that the discovery period was the quickest for victims of existing account frauds; and, victims of new account and other frauds were the least likely to discover their victimization within one week (Synovate, 2003 , 2007 ). Furthermore, for 24% to 27% of new account and other fraud victims, it took them 6 months or more to discover their victimization as opposed to less than 5% for existing credit card and other existing account victims (Synovate, 2003 , 2007 ). In parallel with these findings, the 2014 Ponemon medical identity fraud study found that most victims of medical identity fraud did not learn about their victimization until 3 months after the incident (Ponemon Institute, 2015 ). Surveys by the BJS over the years have consistently shown that the most common way identity fraud victims discover their victimization was through contact from a financial institution for victims of existing account frauds and contact from a non-financial institution for other types of identity fraud (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ).

Reporting of identity fraud victimization

The studies included in this review demonstrated that there is a considerable risk of underreporting of identity fraud victimization to authorities (especially to law enforcement) and to organizations which can provide the necessary information and services to handle the aftermath of victimization.

Looking at studies from early 2000s, the 2003 and 2006 FTC surveys show that, 38% of identity fraud victims did not report their victimization to any organization. In both surveys, 43% of the victims reported their victimization to the company that issued an existing credit card/account or the company that issued the new account and close to 75% of survey participants did not report their victimization to law enforcement (Synovate, 2003 , 2007 ). According to the 2008 NCVS-ITS, the majority of victims (68%) contacted a credit bureau or a bank to report their victimization. The 2008 NCVS-ITS estimated the reporting of identity fraud victimization to law enforcement at 17% (Langton & Planty, 2010 ), which is lower than the FTC surveys’ estimates of 25% in 2003 and 2006 (Synovate, 2003 , 2007 ). The later iterations of the NCVS-ITS confirmed the findings from earlier surveys by showing that not only identity fraud is underreported to law enforcement but reporting of identity fraud to law enforcement decreased significantly after 2008 with less than 10% of victims reporting their most recent victimization to law enforcement in 2012, 2014, 2016, and 2018 (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ). However, the same NCVS-ITS surveys also showed an uptick in reporting of identity fraud to non-law enforcement agencies. According to the 2012, 2014, 2016, and 2018 NCVS-ITS surveys, about 9 in 10 identity fraud victims reported their victimization to a non-law enforcement agency (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ) with credit card companies and banks being the most frequently contacted organizations and non-law enforcement victim service organizations being the least contacted organizations by the victims.

BJS reports based on all 5 iterations of NCVS-ITS further suggest that victims of existing account frauds are less likely than victims of new account frauds and other frauds to report their victimization to law enforcement (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). The most common reason for victims to not report their victimization to law enforcement was victims handling the incident in a different way such as reporting their victimization to another non-law enforcement agency (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). Other reasons for victims to not report their victimization to law enforcement include victims not suffering any monetary loss; victims thinking law enforcement cannot help them; victims thinking their victimization is not important enough; victims not knowing they can report their identity fraud victimization to police; victims being embarrassed, afraid, or burdened to report their victimization; and perpetrator being a family member or an acquaintance (Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). The 2014 Ponemon Institute study similarly found that victims of comparatively more serious identity fraud cases are more likely to contact law enforcement. Ponemon surveys found reasons similar to those identified by the NCVS-ITS for victims not reporting their victimization to legal authorities (Ponemon Institute, 2012 , 2013 , 2015 ).

Two academic studies by Golladay ( 2017 ) and Reyns and Randa ( 2017 ), both based on the 2012 iteration of the NCVS-ITS, provide additional insight into reporting of identity frauds. According to Golladay ( 2017 ), higher income victims are more likely to report their victimization to a credit card company or financial institution whereas people of color, individuals who know the perpetrator, and individuals who did not have prior identity fraud victimization or who had a lower number of identity fraud victimization experiences in the past year were more likely to contact law enforcement. The Golladay ( 2017 ) finding on the positive relationship between knowing the offender and the likelihood of contacting organizations is surprising considering, the descriptive analysis of the NCVS-ITS suggest that individuals knowing the offender is a reason for not contacting law enforcement (Harrell & Langton, 2013 ). This discrepancy might be due to the increasingly technological nature of identity fraud cases where victims who know anything about the offender contacting the police or the omission of some variables in relation to the severity of identity fraud (such as discovery time or time spent trying to resolve issues in relation to victimization) from the regression models. According to the same study (Golladay, 2017 ), people of color (in comparison to individuals who identify as White), individuals who knew the perpetrator (in comparison to people who did not know), individuals with a higher monetary loss as a result of their victimization, and victims who experienced a higher number of identity frauds in the past year were more likely to report their victimization to a credit bureau.

Another study by Reyns and Randa ( 2017 ) compared the factors affecting reporting of victimization among victims of credit card fraud, bank fraud, any existing account fraud, and new accounts fraud. According to this study, seriousness of the offense (which the authors describe as incidents in which victims experienced more emotional distress and had more out of pocket losses and perpetrators obtained more money) appears as the only common factor affecting the decision to report victimization to law enforcement among all identity frauds considered. Other factors such as knowing how the personal information was obtained and a shorter time period between the fraud incident and the discovery of victimization were associated with increased odds of contacting law enforcement for credit card and bank fraud victims. According to the same study (Reyns & Randa, 2017 ), reporting the incident to a non-law enforcement agency was associated with increased odds of contacting law enforcement among victims of existing account frauds, however a sub-analysis of reporting patterns among bank fraud and credit card fraud victims showed that, while bank fraud victims who contacted other agencies were more likely to contact law enforcement, victims of credit card fraud who contacted other agencies were not as likely to contact law enforcement. This study further showed that income and sex were significant predictors of reporting when subcategories of identity fraud were considered. Victims of credit card fraud with higher incomes and female victims of new account frauds were less likely to report their victimization to law enforcement.

Other academic studies, which were evaluated to have a high risk of bias, provide additional insight into reporting behavior of identity fraud victims. A study by Gray ( 2010 ) found that individuals who knew which law enforcement agency to contact for reporting identity fraud were most likely to contact law enforcement (Gray, 2010 ). Another online survey of school counselors by Marcum et al. ( 2016 ) found that counselors who are White, who have a higher level of education, and who work in urban school settings were less likely than their counterparts to complete an incident report about identity fraud victimization reported by students.

Risk factors for identity fraud victimization

From the 52 publications included in this review, 15 focused on risk factors of identity fraud victimization. According to the evaluation of risk of bias among these 15 studies, 6 were classified to have a low risk of bias; 3 to have a moderate risk of bias and 6 to have a high risk of bias. The 9 studies with low and moderate risk of bias ratings suggest several individual-level risk factors for identity fraud victimization. Among these studies, demographic factors were the most commonly studied individual-level predictors of identity fraud victimization. The biggest takeaway from these studies is that predictors of identity fraud victimization vary significantly based on the identity fraud victimization type considered.

Among all demographic factors studied, the findings from different studies on the relationship between age, income, and identity fraud risk were in most agreement. In the broader victimology literature, victims and especially victims of violent crime have been shown to be younger (Turanovic & Pratt, 2019 ). The studies included in this review generally suggest that victims of identity fraud are older than victims of other crimes. However, as indicated in the earlier section, minors under the age of 16 who might be at increased risk of identity fraud victimization due to their clean credit histories and lack of control over their finances (FTC, 2011 ), have not been included in identity fraud data collection efforts in the studies that were reviewed. Accordingly, this exclusion should be taken into consideration in the comparison of age patterns among identity fraud victims and victims of other crimes. Although victims of existing bank account frauds tend to be slightly younger than victims of existing credit card frauds and new account frauds, overall, lower bias studies included in this review show that the victims of existing account frauds and new account frauds tend to be in older age categories (35–64 years of age) (see Anderson, 2006 ; Burnes et al., 2020 ; Copes et al., 2010 ; Harrell & Langton, 2013 ; Harrell, 2017 , 2019 , 2021 ; Langton & Planty, 2010 ). Another important finding from lower bias studies included in this review was that identity fraud victimization risk decreases after age 65 and individuals who are aged 75 and older have a lower risk of identity fraud victimization in comparison to other age groups (Anderson, 2006 ; Harrell & Langton, 2013 ).

High income was another common predictor of identity fraud among the majority of studies included in this review. Several lower bias studies not only showed that among all identity fraud victims, individuals with a household income of $75,000 or more are more likely to be an identity fraud in the general victim population (Anderson, 2006 ; Harrell, 2017 , 2019 , 2021 ; Langton & Planty, 2010 ; Reyns, 2013 ) but this pattern also holds for the subcategory of existing credit card/bank account fraud (Burnes et al., 2020 , 2017 , 2019 ). One exception to this finding was a study by Copes et al. ( 2010 ), which was evaluated to have a moderate level of bias, which showed that although the typical identity fraud victim earned $50,000 to $75,000, victims of non-credit card identity frauds were majority low-income individuals.

The relationship between racial/ethnic minority status and identity fraud victimization risk was another commonly studied topic. Based on the lower bias studies included in this review, the evidence on this relationship was mixed. Findings from the most recent studies based on the NCVS-ITS demonstrate the clear need for differentiating between credit card frauds and other types of identity frauds for exploring the nature of this relationship. A study by Anderson ( 2006 ) based on a regression analysis of data from the 2003 FTC survey showed that, when all identity fraud types are taken into consideration, individuals who identity themselves in the “Other” race/ethnicity group, which included individuals who do not identify as African American/Black, Asian, Hispanic, or non-Hispanic White, were more likely to become victims of identity fraud in comparison to individuals who identify with these racial/ethnic categories. On the other hand, later descriptive analyses based on NCVS-ITS showed that non-Hispanic White individuals were more likely to be victims of identity fraud in the general victim population and this pattern also held true for victims of existing credit card fraud (Burnes et al., 2020 ; Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). Some of the lower bias studies included in this review showed that there were no differences between different racial/ethnic categories in their risk of experiencing existing bank account frauds (Harrell, 2017 ; Harrell & Langton, 2013 ), new account frauds, and other frauds (Burnes et al., 2020 ). One notable exception to this finding was results from the Copes et al. ( 2010 ) study which showed that victims of non-credit card frauds were more likely to be Black.

Similar to the relationship between racial/ethnic identity and victimization risk, the evidence on the relationship between sex and identity fraud victimization risk was mixed. While some of the lower bias studies included in this review suggested that there was no significant relationship between an individual’s sex and their identity fraud victimization risk (even when different subcategories of identity fraud were considered; see Burnes et al., 2020 ; Harrell, 2019 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ), other studies found that females have a higher victimization risk in general (Anderson, 2006 ; Copes, 2010 ; Harrell, 2021 ) and especially for non-credit card frauds (Anderson, 2006 ; Copes, 2010 ).

Lower bias studies included in this review further showed that other less commonly studied demographic factors such as education, marital status, number of children in the household, and number of adults in the household can be related to risk of identity fraud. While earlier studies found no relationship between marital status and identity fraud risk (Anderson, 2006 ; Copes, 2010 ), a recent regression study by Burnes et al. ( 2020 ), which was based on the 2012 and 2014 iterations of the NCVS-ITS, found that married people were more likely to be victims of instrumental identity frauds. The same study (2020) further showed that individuals who have attended at least some college degree have a higher likelihood of becoming a victim of an existing or new account fraud. The study by Copes ( 2010 ) also found that individuals with more than a high school education were more likely to become identity fraud victims. Although far less commonly studied, a higher number of children in the household (three or more) and having only one adult in the household were also found to be associated with a higher identity fraud victimization risk (see Anderson, 2006 ).

Burnes et al. ( 2020 ) further showed that individuals who experience multiple instances of identity fraud in a short amount of time and individuals who chronically experience identity fraud victimization are more likely to experience identity fraud victimization later. Repeat victimization is a particularly understudied topic within the literature on identity fraud and has important implications considering stolen personally information can be used over the years and the conditions that enable victimization in the first place can predict further victimization.

Lastly, a few of the lower bias studies included in this review examined the relationship between individuals’ protective behavior, routine online activities, and self-control and their risk of identity fraud victimization. For instance, Copes et al.’s ( 2010 ) study found that victims of identity fraud did not engage in any more risky behavior than non-victims and spent about the same time online as average Americans. Other more recent studies on the other hand found a significant relationship between lifestyles, routine activities, self-control and identity fraud victimization. For instance, Holtfreter et al. ( 2015 ) conducted a phone survey with individuals aged 60 and older living in Arizona and Florida and found that individuals who have a lower level of self-control were more likely to engage in risky online purchases and subsequently more likely to become identity fraud victims. Burnes et al. ( 2020 ) further found that some protective behaviors employed by individuals such as changing online passwords and shredding and destroying documents reduced the risk of identity fraud victimization.

Other studies that were evaluated to have a higher risk of bias also provided support for the findings discussed above and provided additional insights into predictors of identity fraud victimization. However, the findings from these studies should be considered carefully considering each study’s limitations (see Appendix 5). For instance, a study by Cornelius ( 2016 ) based on an online survey found that the higher an internet user’s knowledge of phishing risks, the higher likelihood that the user was victimized by online theft. In another study, Holt and Turner ( 2012 ) administered a survey to students, faculty, and staff at a university and found that females and individuals who update their protective computer software were more resilient against identity fraud. Kpaduwa ( 2010 ) conducted a survey with university students and found no significant correlation between students’ knowledge of identity fraud and their risk of identity fraud victimization. Another study by Navarro and Higgins ( 2017 ) found that victims of familial identity theft, younger victims, and repeat victims of identity fraud were more likely to experience non-account identity frauds. Ponemon Institute ( 2011 ) provided further support for the findings from lower bias studies by showing that victims of medical identity fraud tend to be older. Lastly, in another college sample, Reyns et al. ( 2019 ) found that the time spent sending e-mailing was positively correlated with identity fraud victimization risk.

Harms and consequences of identity fraud victimization

From the 52 publications included in this review, 31 focused on harms of identity fraud victimization. Studies based on the NCVS-ITS once again provide the most robust evidence on both economic and non-economic harms of identity fraud.

Economic consequences of identity fraud victimization

The studies included in this review focused on both direct costs of identity fraud for victims, which can include out-of-pocket and reimbursed losses to the victim and indirect costs such as monetary costs associated with dealing with the aftermath of the victimization experience (such as legal costs, bounced checks, and other expenses), lost wages, difficulty finding jobs, being denied loans, and damaged credit scores. The lower bias quantitative studies included in this review based on national samples revealed the following main findings: (1) the majority of identity fraud victimizations result in direct financial loss; (2) the initial money lost does not always result in out of pocket loss; (3) certain demographic factors might predict the likelihood of experiencing out of pocket losses; (4) the indirect and direct loss amount differs by the type of identity fraud victimization; and (5) victims whose personal information is used for other fraudulent purposes are most likely to experience direct and indirect losses, credit related problems, and other financial problems (Green et al., 2020 ; Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ; Reynolds, 2020 ; Synovate, 2003 , 2007 ).

For instance, the most recent statistics based on the 2018 iteration of the NCVS-ITS show that 68% of victims experienced a direct loss of $1 or more as a result of their most recent victimization (with a median loss of $200) but from these victims only 12% experienced an out of pocket loss of $1 or more (with a median out of pocket loss of $100) (Harrell, 2021 , p. 9). According to the same survey, among all victims, only 5% experienced an indirect loss that was $1 or more (with a median loss of $30) (Harrell, 2021 , p. 10). The same survey further showed that victims of existing account frauds were least likely to experience direct and indirect costs whereas individuals whose personal information was stolen for other fraudulent purposes were most likely to experience direct and indirect costs (Harrell, 2021 ). Another important trend is that victims who have a long discovery time had more severe economic consequences. For instance, the 2006 FTC survey found that while 30% of victims who discovered that their personal information was being misused 6 months or more after the incident spent $1000 or more to handle the aftermath of their victimization, only 10% of those who found the misuse within 6 months spent $1000 or more.

A recent study by Reynolds ( 2020 ) further found a relationship between economic costs and demographics. Individuals with lower income and educational attainment and unmarried individuals are at higher risk of experiencing out of pocket losses as a result of their identity fraud victimization. Another study by DeLiema et al. ( 2021 ) based on the 2014 and 2016 iterations of the NCVS-ITS also found that, among older adults, individuals who live at or below the federal poverty level were most likely to experience out of pocket losses.

Other high bias studies included in this review provide further support for the lower bias studies included in the review. For instance, studies by the Ponemon Institute found that medical identity fraud victims can experience distinct indirect costs such as increased insurance premiums and lost medical coverage (Ponemon Institute, 2011 , 2012 , 2013 , 2015 ). ITRC surveys further showcased the aggravated economic harms experienced by victims of comparatively more serious cases of identity fraud (i.e., non-account frauds) (see ITRC, 2003 , 2005 , 2007 , 2008 , 2009 , 2010 , 2014 , 2015 , 2017 , 2018a , 2018b , 2021 ).

Non-economic consequences of identity fraud victimization

The lower bias studies included in this review which are based on national surveys showed that a significant number of identity fraud victims (estimates ranging from 80 to 90%) experience some level of distress as a result of their victimization. Victims of new account frauds and other frauds (in comparison to victims of existing account frauds), victims of multiple types of identity fraud (in comparison to victims of one type of identity fraud), and victims who spend a longer time resolving problems associated with their victimization are much more likely to experience severe distress as a consequence of their victimization (Harrell, 2017 , 2019 ; Harrell & Langton, 2013 ; Langton & Planty, 2010 ). National studies further suggest that a small group of identity fraud victims might experience physical problems, legal problems, and problems with family, friends, work, and school in relation to their identity fraud victimization (Langton & Planty, 2010 ; Harrell, 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Reyns & Randa, 2020 ).

Looking deeper into the time burden aspect of identity fraud, national studies over the years revealed that, unsurprisingly, victims who discovered their victimization later spent a longer amount of time resolving the ramifications of their victimization (Synovate, 2003 ). These surveys further estimated that between 25 and 50% of victims resolved any issues experienced as a result of their victimization within 1 day of discovering they were victims (Harrell 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Synovate, 2007 ) but for a smaller group of victims (less than 10% of the victims) resolving issues took 6 months or more (Harrell 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ). National surveys also showed that new account and other fraud victims spent a longer amount of time resolving their problems in the aftermath of their victimization in comparison to victims of existing account frauds (Harrell 2017 , 2019 , 2021 ; Harrell & Langton, 2013 ; Synovate, 2007 ). According to the 2006 FTC survey, the top 10% and 5% of victims spent more than 100 h and 1000 h respectively to resolve their problems (Synovate, 2007 ).

Other lower bias regression studies and higher quality qualitative studies included in this review support these descriptive findings from national surveys and further suggest other individual and situation-specific factors that can predict who is more likely to experience these negative outcomes (Betz, 2012 ; Golladay & Holtfreter, 2017 ; Pryor, 2009 ; Randa & Reyns, 2020 ). For instance, a qualitative study based on in-depth interviews with identity fraud victims showed that individuals who experienced identity fraud as a minor but discovered the victimization as an adult can experience negative emotional consequences and these consequences might be aggravated if the victims do not have support from law enforcement and their families (Betz, 2012 ). Another study by Golladay & Holtfreter based on the 2012 NCVS-ITS suggested that individuals who have prior victimization experiences and individuals who are not White might be more likely to experience a higher level of negative emotional consequences. Another low bias study by Randa and Reyns ( 2020 ) found that while being older, being a female, spending more time resolving the ramifications of victimization, and higher amount of net loss as a result of victimization were all correlated with higher distress level; being married and having a higher education level were correlated with less distress reporting. The authors (2020) similarly found that while the net monetary loss and the time to clear the incident were positively correlated with the level of negative physical outcomes experienced by the victims; education level and being married were negatively correlated with the level of negative physical outcomes.

Green et al. ( 2020 ) conducted qualitative analyses based on data from interviews with 16 individuals who contacted the ITRC after experiencing a serious identity fraud victimization (defined by authors as victims who experienced identity frauds other than existing credit card fraud and who contacted the ITRC). According to this study, among victims of serious identity fraud, victims of criminal identity fraud (and especially identity frauds involving government-based services) had the most complicated and time-consuming cases with the most substantial indirect economic and legal consequences and the majority of victims of serious identity frauds attempted to investigate their own cases (despite being discouraged to do so). The study further showed that victims who strictly follow the best practices to document in detail their interactions and conversations with others during the remediation process, experienced a significant time burden and had a hard time in managing their daily routines. This study suggested that the experiences of victims of serious identity frauds trying to prove their situations to legal authorities is similar to those of survivors of sexual assault (Green et al., 2020 ).

Other studies that were rated to have a high risk of bias due to issues with the sampling frame and size, nonresponse rate, and missing data nevertheless provided strong support for the findings on the negative emotional and physical outcomes, legal problems, time burden, and other problems faced by the victims in the aftermath of their victimization (see ITRC, 2005, 2007, 2008, 2009, 2010, 2014, 2015, 2017, 2018a, 2018b, 2021 ; Li et al., 2019 ; Ponemon Institute, 2011 , 2012 , 2013 , 2015 ).

Prevention, programs, and services

From the 52 studies included in this review, prevention of victimization and programs and services for victims was the least researched topic. Notably, all of the three articles included in the review under this topic were published between 2020 and 2021 and by the same group of authors.

One of these studies by Green et al. ( 2020 ), which was rated to have a moderate risk of bias, found that victims of serious identity fraud, despite the increasingly online nature of this crime, still use internet search engines as the main method to learn about remediation options. The authors further found that victims of serious identity fraud who expressed a higher level of satisfaction with services provided to them were individuals who had a representative from an organization whom they felt was a partner in their pursuit of recovery from their victimization.

Another study by Green et al. ( 2021 ), which was rated to have medium quality, explored the needs of identity fraud victims from the viewpoint of a diverse group of professionals providing services for identity fraud victims. An important finding from this study was that organizations serving identity fraud victims are not equipped to respond to the long-term needs of victims of synthetic identity fraud in which perpetrators generally combine real and fake identity information to create new identities and victims do not become aware of victimization for years. The study findings further suggested that the field need to better understand the relationship between data breaches and subsequent identity fraud victimization to better educate and provide services to individual victims based on the nature of the stolen personal information.

Another quantitative study by Gies et al. ( 2021 ) examined the effect of using services provided by the ITRC on experiences of serious identity fraud victims (defined by authors as victims of any identity fraud other than misuse of existing credit card). The authors combined data from the ITRC’s 2017 Aftermath Survey and the 2016 NCVS-ITS to compare experiences of three groups of victims of serious identity frauds that have been matched on key demographic variables: (1) respondents to the NCVS-ITS who did not report their victimization to any entity ( no report ), (2) respondents to the NCVS-ITS who reported their victimization to one or more entities and received standard services from these entities ( treatment as usual ), and (3) individuals who contacted the ITRC and received specialized services which involves receiving caring and compassionate advice from specially trained (trauma-informed) employees of the ITRC including a continuity of care upon request of the victim ( ITRC treatment ).

First, this study showed that individuals who contacted the ITRC had a longer time period between the victimization incident and the discovery of victimization and spent a longer amount of time resolving the incident. Accordingly, it is reasonable to argue that although the groups were matched on key variables, individuals in the ITRC treatment group had comparatively more serious cases of identity fraud victimization. The study found significant differences between the three groups regarding the key outcomes measured. The respondents in the ITRC treatment group reported significantly more general problems, financial problems, employment/educational problems, family/friend problems, and physical health problems and more money loss in comparison to the individuals in the no report and treatment as usual groups. This finding is not surprising considering the victims in the ITRC treatment group had a longer discovery time and spent more time dealing with the ramifications of their victimization. However, surprisingly, the victims in the ITRC treatment group reported fewer health problems as a result of their victimization experience than the individuals in the no report and treatment as usual groups. This finding provides support for the model of services provided by ITRC (i.e., the trauma-informed focus of these services and the continuity of care in the long term if requested by the victims). However, these findings should be interpreted carefully considering some limitations of this study (see Appendix 5 for a detailed description) including the cross-sectional nature of data collection on which this quasi-experimental study was based on.

For this study, 52 studies were reviewed for their results on different aspects of identity fraud victimization. So, what does this emerging literature on identity fraud tell us about identity fraud victimization and what we can do as researchers and practitioners to narrow the gaps in the existing literature and to better identify, reach, and serve victims and to prevent victimization?

Cross-sectional national data collection efforts show that the incidence and prevalence of identity fraud victimization increased over the years and the misuse of an existing account is the most common type of identity fraud victimization. However, national identity fraud surveys likely underestimate the number of victims due to underreporting, the discovery period of identity frauds, and exclusion of certain groups and from survey samples. There is a pressing need for further analysis of existing data and collection and analysis of new data to explore the following: (1) the prevalence of identity fraud victimization among minors, individuals in institutional settings, and individuals in transient living settings; (2) long-term prevalence of identity fraud victimization; (3) prevalence of victimization to detailed subcategories of new account and instrumental frauds; (4) disaggregated analysis of prevalence of attempted and successful identity frauds; (5) subnational trends in identity fraud victimization; and (6) prevalence of synthetic identity fraud victimization.

The reluctance of victims to report identity frauds in general, and to law enforcement and victim service organizations in particular, suggest a pressing need to educate the public, the law enforcement, and victim service providers about stages of identity theft, forms of identity theft, and seriousness of this crime. As discussed earlier identity theft and identity fraud are two terms that are used interchangeably although acquiring of information precedes the fraudulent acts committed with the acquired information and theft of information does not have a monetary harm (Gies et al., 2021 ). The lack of distinguishing between these two stages of identity theft and not knowing about different forms of identity theft might result in individuals not fully understanding the potential long-term harms of exposure of their personal information.

Furthermore, in addition to public’s reluctance to report identity fraud victimization to law enforcement; the often cross-jurisdictional nature of identity theft and fraud, the interrelatedness of identity theft with other crimes, the lack of knowledge about the perpetrator, and the frequent handling and investigation of financial frauds by financial agencies make it hard for law enforcement agencies to identify and record identity theft and even disincentivize them to handle identity theft cases (Newman & McNally, 2005 ). The reluctance of victims to report their victimization and the reluctance of law enforcement to respond the cases of identity theft can: reduce victims’ access to criminal justice processes, affect investigation and prosecution of these crimes, increase victims’ sense of helplessness, and reduce victims’ chances of accessing critical information and resources to prevent victimization and revictimization and recover from the aftermath of their victimization. Accordingly, there is a need for individuals, law enforcement, victim service providers, and policymakers to put as much emphasis on the acquisition of personal information as the subsequent frauds (Gies et al., 2021 ) and to better understand the nature of this crime including stages, types, victims, perpetrators, and consequences of identity theft and the evolving opportunity structure for identity theft.

The research evidence on the lower likelihood of identity fraud reporting among individuals who had negative interactions with law enforcement further suggest that there is a need for making it easier for victims to report their victimization, increasing public outreach to encourage reporting, commitment of leadership to a victim-centered approach, training of police officers on the nature of identity theft and fraud and different forms of identity fraud. However, similar to the experiences of victim service providers, budget limitations can prohibit local law enforcement from putting in place organizational inputs (such as establishing an identity theft unit, having victim advocates, and providing continuous training) to ensure these outcomes. Collaboration between federal and local law enforcement organizations in training of officers and increasing state funding for police departments to have cybercrime and identity theft units and employ identity theft analysts and investigators can lift some of these barriers. There is also a need to better educate the employees of banks and financial institutions about the nature of identity theft and to use this communication between identity theft victims and these organizations as an opportunity to direct victims to government and non-profit organizations specialized in helping identity theft and identity fraud victims.

Studies on risk factors of identity fraud victimization further show that risk factors for victimization vary by identity fraud types. Studies in this review further showed that people of color, individuals from lower socio-economic backgrounds, individuals with chronic identity fraud victimization experiences, and individuals with multiple identity fraud victimizations at a short amount of time in the near past might be more likely to experience more serious forms of identity fraud and might be at heightened risk of experiencing aggravated harms. However, these studies exclude critical groups and do not provide information about the risk factors for detailed subcategories of identity fraud such as various subcategories of instrumental frauds. The research on protective behavior of individuals against identity fraud is not conclusive and is not able to temporally differentiate the impact of protective behaviors on identity fraud victimization due to the cross-sectional design of studies. Longitudinal studies of protective behavior and more detailed data collection and analysis on risk factors for victimization can provide critical insight for public education about risk factors and targeting of this information through different means to groups at risk.

Longitudinal studies following identity fraud victims are also essential for reliably estimating the true impact of identity fraud victimization on victims and the effectiveness of services and programs offered to identity fraud victims. There is also a need to better distinguish the impacts of identity fraud victimization for detailed categories of identity fraud.

The overwhelming evidence on the differential impact of identity fraud for victims of different identity frauds and victims of different circumstances reiterate the importance of recognizing that not every identity fraud is the same and not every identity fraud victim will experience severe trauma and other negative consequences. Considering the limited funding and resources for victims of crime in general, and victims of identity frauds in particular, better identification of victims who are in need of extended services and triage of services and resources between different organizations are essential to provide holistic and long-term services to victims who are at highest risk to experience chronic victimization and aggravated harms as a result of their victimization.

The overwhelming lack of research on the impact of programs and services for identity fraud victims necessitates more attention from scholars and practitioners to study the impact of programs, interventions, and services for identity fraud victims on reporting of victimization, prevention of victimization, experiences of victims, and victim-centered cost benefit analysis of services. The empirical evidence on the more positive outcomes experienced by victims of identity fraud who have a meaningful and satisfactory experience with victim service professionals and who are receiving specialized services suggest the promising potential of trauma informed services and continuity of services for a specific group of victims experiencing more serious forms of identity frauds. However, more research is needed to identify which characteristics and components of specialized services that are more likely to produce positive outcomes for identity fraud victims.

Although phishing and vishing (i.e., voice phishing) has not been included in the scope of this review, another emerging important topic in relation to the understanding individuals’ vulnerability to identity fraud and other types of frauds is the use of artificial intelligence (AI) in fraudulent activities. Recently, the ITRC ( 2019 ) reported the first case of the use of artificial intelligence in AI-related fraud in which AI was used to impersonate the head of a German company to successfully request money from the CEO of the UK branch of the company.

Lastly, although this review focused on individual victims of identity fraud, and not organizational victims, considering the increasing number of data breaches; greater preventative efforts are required at the organizational level to secure operations, to fix vulnerabilities, and to better notify involved parties (FTC, 2022 ). Establishment of uniform data security and data breach notification standards across the US and federal enforcement of these standards can simultaneously reduce identity theft and identity fraud risk by targeting both collective and individual targets of identity theft.

The following search string was used in all databases with the exception of JSTOR: (“identity theft” OR “identity fraud” OR “social security fraud” OR “credit card fraud” OR “account fraud” OR “internet fraud” OR “cyber fraud”) AND (victim*). For JSTOR database the following truncated search string was used due to word limitations: ("identity theft" OR "identity fraud") AND (victim*). These search strings were applied to the title or abstracts of the sources included in these databases.

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Acknowledgements

I would like to thank the anonymous peer reviewers, Dr. Schumann, and Dr. Wortley for their thoughtful feedback on this manuscript. I would like to thank Alexandra Ricks for her contribution to the early stages of this project. I would like to thank Dr. David B. Wilson for sharing resources on assessments of quality of qualitative research. I would like to also thank Dr. Christopher Koper for his review of and thoughtful feedback on an earlier version of this article.

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Flow chart diagram of search results and identification of studies

Hoy et al. ( 2012 ) risk of bias tool

Note: If there is insufficient information in the article to permit a judgment for a particular item, please answer No (HIGH RISK) for that particular item.

• *All descriptive quantitative studies were evaluated based on items 1–5, 7(if necessary), and 8. Items 6, 9, and 10 were only used to assess the risk of bias within prevalence studies

Mays and Pope ( 2020 ) framework for assessing quality of qualitative studies

Quality/risk of bias evaluations and ratings for included studies

Evaluation of quantitative studies.

This review adopted criteria from Hoy et al.’s ( 2012 ) risk of bias evaluation tool (see Appendix 2) to evaluate the risk of bias within quantitative studies. Hoy et al.’s ( 2012 ) risk of study bias assessment, similar to the GRADE approach, does not include a numerical rating but rather evaluates the overall risk of bias based on assessment of risk of bias of individual risk items (Hoy et al., 2012 ). Each quantitative study in this study was assigned into one of the following three categories based on an overall evaluation of risk of study bias based on this tool: low risk of bias, moderate risk of bias, or high risk of bias (see below for individual study ratings and Appendix 5 for bias/quality notes).

Evaluation of qualitative studies

Seventeen appraisal questions from Mays and Pope ( 2020 ) were used to evaluate the quality of qualitative studies based on the reporting of findings, study design, data collection, analysis, reporting, reflexivity and neutrality, ethics, and auditability of the studies (see Appendix 3). In this review, each qualitative study was allocated into one of the following three categories based on an overall evaluation of the study quality based on these 17 indicators: low quality, medium quality, or high quality (see below for individual study ratings and Appendix 5 for bias/quality notes).

Evaluation of mixed-method studies

For the only mixed-method study included in this review (see ITRC, 2003 ), the risk of bias and the study quality were evaluated separately for qualitative and quantitative elements of the study utilizing the frameworks by Hoy et al. ( 2012 ) and Mays and Pope ( 2020 ) (see below for individual study rating and Appendix 5 for bias/quality notes).

• *Studies that analyze data quantitatively were classified into one of the following three bias ratings: low risk of bias, moderate risk of bias, or high risk of bias
• **Studies that analyze data qualitatively were classified into one of the following three quality ratings: low quality, medium quality, or high quality
• ***For the only mixed-method study included in this review, results from qualitative and quantitative analysis were evaluated separately

Bias and quality assessment summary notes for included studies

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Irvin-Erickson, Y. Identity fraud victimization: a critical review of the literature of the past two decades. Crime Sci 13 , 3 (2024). https://doi.org/10.1186/s40163-024-00202-0

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Essays on Identity Theft

Writing an identity theft essay may not be fun, but it will be a good reason for you to learn about the dangers of identity theft and how it can affect you personally. Identity theft affects millions of people every year. This issue is more pressing than ever now as we conduct most of our activities online. Active social media users have a 30% higher risk of becoming victims of identity theft because their personal information is often disclosed. Writing essays on identity theft can offer insight into this issue and help students be more aware of the dangers it can pose. Our identity theft essay samples below will allow you to cut back time on research and help pin some points you should touch upon in your essay. Students’ workload is not getting any lighter, so we offer to compose identity theft essays for those who need further help with their essays than just samples.

Everyone dreams for that time when the elections will be of integrity, free and fair. There has been a lot of debate whether the voter ID laws are the solution or not. All Americans can freely acquire the photo IDs even though some may get it easier than others depending...

Big data is the availability of data and metadata concerning virtually every object in existence in the world at the moment. When the information relates mere objects, the privacy may not be of much concern. However, with more information captured relating to individuals and organizations, the stakes-placed on the sensitivity...

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Understanding Identity Theft Every computer user should understand how identity theft takes place and which information to protect to avoid being an identity theft victim. Currently there many cases of identity theft and unless a computer user employs measures to protect his/her information, he may be at risk of identity theft....

Introduction Over the previous decade, there has been growth in threats to critical infrastructure sectors to potential disastrous dimensions. Critical infrastructure protection has turned out to be an issue of economic stability, domestic security, and public safety. To protect the nation from cyber-attacks to critical infrastructure it is imperative the United...

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The Masks We Wear in Life The paper discusses masks that I wear in life which in most cases are used to impress or please others. An individual can wear different masks such as sexuality, being non-sensitive, or gay in their entire life. Often people wear social masks to navigate the...

The Toughest Questions Facing the World on Social Media Security The current world is facing the toughest questions of all time on the security threat caused by social media platforms. The fake account is a platform facilitating identity theft since unauthorised information plays a central role in criminal activities. Countermeasures to...

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Research Question: What affect does identity theft have on the economy? Thesis Statement: While financial and health institutions are rolling out modern ways of identifying and interacting with their clients, the rate of identity theft is alarming and the economy is losing billions of dollars annually. Thus, strict policies and public...

Since the dawn of the twenty-first century, news reports of hacking incidents involving significant financial institutions, companies, governmental organizations, and any other location where hackers can acquire personal information and use it to defraud millions of people worldwide have been almost daily. Identity theft is the practice of stealing personally...

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The banking industry demands the highest level of expertise and ethical behavior. One financial organization, Wells Fargo, defied these regulations by issuing credit cards and accounts to face clients. Through this practice, bank workers were able to increase profits at the expense of unwitting and innocent customers. Customers and investors...

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Although financial and health institutions are implementing new methods of defining and communicating with their customers, the rate of identity theft is troubling, and the economy is losing billions of dollars per year. To reverse the trend, stringent legislation and public recognition must be implemented. The Center for Identity (2014)...

The introduction of the Internet signaled the beginning of a new age of how humans perform their business. Technology advancements have allowed a person in the Arctic to video chat with a colleague in the most distant region of the African continent. Furthermore, large amounts of data can be stored...

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Identity fraud is a serious crime in today's society. Identity fraud, according to Javelin Strategy and Research (2015), is the illegal use of an individual's personal information for financial gain. Identity fraud can involve anything from using a stolen credit card to running another person's bank account. Many individuals in...

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Identity Theft

Identity theft is one of the most widely used crimes which involve the use of personal data by other individuals. This essay tells about identity theft background and gives the definition of this term. It highlights the ways of how the personal information can be stolen by criminals. It indicates main types of identity theft and explains the consequences of this type of crime for victims. It also demonstrates the facts that back up the main points of the paper.

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What is identity theft?

Identity theft is a crime for which the personal data are used illegally for material gain. The information from the Social Security number, credit card number, bank account, telephone calling card number and other types of personal data can be used by other people for stealing money. In some cases, it is only necessary to know the victim’s name in order to commit the identity theft. Victims of the identity theft may lose not only the financial costs, but also struggle with the attempt to restore their reputation as a result of using their personal data by criminals. Criminals can apply the stolen personal information in order to fill in the false application for loans or credit cards or fulfill the fraudulent withdrawals from bank accounts.

Common ways to commit the identity theft

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Types of the identity theft

There are several types of the identity theft that could be identified as criminal, financial, medical, child identity theft and identity cloning. Criminal identity theft occurs when a person, who just was arrested, presents to police the fake ID or other stolen documents that identify him or her as another person. Subsequently, it could be difficult for the victims to clean the criminal record as a result of violation of their rights. Financial identity theft is the most common form of identity theft that is used in order to obtain, goods, services or credit. Usually, along with a wallet people stole credit cards and use them in order to obtain cash. At the large perspective, people steal the private financial information with the help of computer programs and conduct transactions with a victim’s money. Medical identity theft usually occurs when a theft wants to obtain prescription drugs or see a doctor while using the victim name or health insurance numbers. Very often, the payment records and credit report of the victim are affected after the mix of the victim and thief’s health information. Medical identity theft is one of the most dangerous forms of identity theft as it could be resulted into incorrect medical treatment of the victim in the future. A child identity theft occurs when a thief the Social Security number in order to apply for government benefits or other needs. Identity cloning is a type of identity theft when criminal pretends to be a different person. Instead of stealing private information, they actually can commit crimes in someone’s name.

Ways of protection

There are many ways of protection that banks and government use in order to escape the identity theft among the general population. However, people should guard their personal information on their own. Many people prefer to buy goods over online shopping. Thus, it is important to clear logins and passwords while using a public computer. It is better to pay from credit cards which have guarantees under federal law. It is important to be careful while entering personal data on different Web sites. People should monitor their credit reports, bank and credit card statements. For companies and large corporations, it is necessary to shred all sensitive documents that can provide the criminal with financial and private information.

Identity theft facts

Identity theft is a growing problem in the world electronic community. It is the fastest growing crime in the United States (Reed, 2). The Department of Justice in the U.S. indicated that that 8.6 million Americans suffered from identity in 2010. It is 2.2 million more than in 2005. A total financial loss was estimated as 13.3 billion dollars. (Tugent, 4). On average, it is necessary to spend approximately 33 hours and 500 dollars for victim in order to resolve the identity theft crime. About 19 people become the victims of the identity theft each minute. One of the main problems is that it is difficult to detect the criminals and arrest them. Only 1in 700 identity crimes end up with the arrest (Reed, 5).

Identity theft could be one of the main criminal issues in the future. The growing number of cases only proves this tendency. It is difficult for the authority to detect criminals who are going to commit the identity theft. That is why people should always be careful with their personal information.

Reed, B., (2012). “5 frightening facts about identity theft”. Retrieved from  site

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How to Write a Thesis Statement | 4 Steps & Examples

Published on January 11, 2019 by Shona McCombes . Revised on August 15, 2023 by Eoghan Ryan.

A thesis statement is a sentence that sums up the central point of your paper or essay . It usually comes near the end of your introduction .

Your thesis will look a bit different depending on the type of essay you’re writing. But the thesis statement should always clearly state the main idea you want to get across. Everything else in your essay should relate back to this idea.

You can write your thesis statement by following four simple steps:

• Start with a question
• Write your initial answer
• Develop your answer
• Refine your thesis statement

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Table of contents

What is a thesis statement, placement of the thesis statement, step 1: start with a question, step 2: write your initial answer, step 3: develop your answer, step 4: refine your thesis statement, types of thesis statements, other interesting articles, frequently asked questions about thesis statements.

A thesis statement summarizes the central points of your essay. It is a signpost telling the reader what the essay will argue and why.

The best thesis statements are:

• Concise: A good thesis statement is short and sweet—don’t use more words than necessary. State your point clearly and directly in one or two sentences.
• Contentious: Your thesis shouldn’t be a simple statement of fact that everyone already knows. A good thesis statement is a claim that requires further evidence or analysis to back it up.
• Coherent: Everything mentioned in your thesis statement must be supported and explained in the rest of your paper.

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The thesis statement generally appears at the end of your essay introduction or research paper introduction .

The spread of the internet has had a world-changing effect, not least on the world of education. The use of the internet in academic contexts and among young people more generally is hotly debated. For many who did not grow up with this technology, its effects seem alarming and potentially harmful. This concern, while understandable, is misguided. The negatives of internet use are outweighed by its many benefits for education: the internet facilitates easier access to information, exposure to different perspectives, and a flexible learning environment for both students and teachers.

You should come up with an initial thesis, sometimes called a working thesis , early in the writing process . As soon as you’ve decided on your essay topic , you need to work out what you want to say about it—a clear thesis will give your essay direction and structure.

You might already have a question in your assignment, but if not, try to come up with your own. What would you like to find out or decide about your topic?

For example, you might ask:

After some initial research, you can formulate a tentative answer to this question. At this stage it can be simple, and it should guide the research process and writing process .

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Now you need to consider why this is your answer and how you will convince your reader to agree with you. As you read more about your topic and begin writing, your answer should get more detailed.

In your essay about the internet and education, the thesis states your position and sketches out the key arguments you’ll use to support it.

The negatives of internet use are outweighed by its many benefits for education because it facilitates easier access to information.

In your essay about braille, the thesis statement summarizes the key historical development that you’ll explain.

The invention of braille in the 19th century transformed the lives of blind people, allowing them to participate more actively in public life.

A strong thesis statement should tell the reader:

• Why you hold this position
• What they’ll learn from your essay
• The key points of your argument or narrative

The final thesis statement doesn’t just state your position, but summarizes your overall argument or the entire topic you’re going to explain. To strengthen a weak thesis statement, it can help to consider the broader context of your topic.

These examples are more specific and show that you’ll explore your topic in depth.

Your thesis statement should match the goals of your essay, which vary depending on the type of essay you’re writing:

• In an argumentative essay , your thesis statement should take a strong position. Your aim in the essay is to convince your reader of this thesis based on evidence and logical reasoning.
• In an expository essay , you’ll aim to explain the facts of a topic or process. Your thesis statement doesn’t have to include a strong opinion in this case, but it should clearly state the central point you want to make, and mention the key elements you’ll explain.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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A thesis statement is a sentence that sums up the central point of your paper or essay . Everything else you write should relate to this key idea.

The thesis statement is essential in any academic essay or research paper for two main reasons:

• It gives your writing direction and focus.
• It gives the reader a concise summary of your main point.

Without a clear thesis statement, an essay can end up rambling and unfocused, leaving your reader unsure of exactly what you want to say.

Follow these four steps to come up with a thesis statement :

• Ask a question about your topic .
• Write your initial answer.
• Develop your answer by including reasons.
• Refine your answer, adding more detail and nuance.

The thesis statement should be placed at the end of your essay introduction .

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Congressman George Santos Charged With Conspiracy, Wire Fraud, False Statements, Falsification of Records, Aggravated Identity Theft, and Credit Card Fraud

CENTRAL ISLIP, NY – A 23-count superseding indictment was filed today in the United States District Court for the Eastern District of New York, charging George Anthony Devolder Santos, better known as “George Santos,” the United States Representative for the Third District of New York, with one count of conspiracy to commit offenses against the United States, two counts of wire fraud, two counts of making materially false statements to the Federal Election Commission (FEC), two counts of falsifying records submitted to obstruct the FEC, two counts of aggravated identity theft, and one count of access device fraud, in addition to the seven counts of wire fraud, three counts of money laundering, one count of theft of public funds, and two counts of making materially false statements to the United States House of Representatives that were charged in the original indictment.  Santos is due back in federal court in Central Islip on October 27, 2023.

Breon Peace, United States Attorney for the Eastern District of New York, Nicole M. Argentieri, Acting Assistant Attorney General of the Justice Department’s Criminal Division, and James Smith, Assistant Director-in-Charge, Federal Bureau of Investigation, New York Field Office (FBI), and Anne T. Donnelly, Nassau County District Attorney, announced the superseding indictment.

“As alleged, Santos is charged with stealing people’s identities and making charges on his own donors’ credit cards without their authorization, lying to the FEC and, by extension, the public about the financial state of his campaign.  Santos falsely inflated the campaign’s reported receipts with non-existent loans and contributions that were either fabricated or stolen” stated United States Attorney Peace.  “This Office will relentlessly pursue criminal charges against anyone who uses the electoral process as an opportunity to defraud the public and our government institutions.”

“Santos allegedly led multiple additional fraudulent criminal schemes, lying to the American public in the process.  The FBI is committed to upholding the laws of our electoral process.  Anyone who attempts to violate the law as part of a political campaign will face punishment in the criminal justice system,” stated FBI Assistant Director-in-Charge Smith.

“The defendant - a Congressman - allegedly stole the identities of family members and used the credit card information of political contributors to fraudulently inflate his campaign coffers,” stated District Attorney Donnelly.  “We thank our partners in the US Attorney’s Office and the FBI as we work together to root out public corruption on Long Island.”

As alleged in the superseding indictment, Santos, who was elected to Congress last November and sworn in as the U.S. Representative for New York’s Third Congressional District on January 7, 2023, engaged in two fraudulent schemes, in addition to the multiple fraudulent schemes alleged in the original indictment.

The Party Program Scheme

During the 2022 election cycle, Santos was a candidate for the United States House of Representatives in New York’s Third Congressional District.  Nancy Marks, who pleaded guilty on October 5, 2023 to related conduct, was the treasurer for his principal congressional campaign committee, Devolder-Santos for Congress.  During this election cycle, Santos and Marks conspired with one another to devise and execute a fraudulent scheme to obtain money for the campaign by submitting materially false reports to the FEC on behalf of the campaign, in which they inflated the campaign’s fundraising numbers for the purpose of misleading the FEC, a national party committee, and the public. Specifically, the purpose of the scheme was to ensure that Santos and his campaign qualified for a program administered by the national party committee, pursuant to which the national party committee would provide financial and logistical support to Santos’s campaign.  To qualify for the program, Santos had to demonstrate, among other things, that his congressional campaign had raised at least $250,000 from third-party contributors in a single quarter.

To create the public appearance that his campaign had met that financial benchmark and was otherwise financially viable, Santos and Marks agreed to falsely report to the FEC that at least 10 family members of Santos and Marks had made significant financial contributions to the campaign, when Santos and Marks both knew that these individuals had neither made the reported contributions nor given authorization for their personal information to be included in such false public reports.  In addition, understanding that the national party committee relied on FEC fundraising data to evaluate candidates’ qualification for the program, Santos and Marks agreed to falsely report to the FEC that Santos had loaned the campaign significant sums of money, when, in fact, Santos had not made the reported loans and, at the time the loans were reported, did not have the funds necessary to make such loans.  These false reported loans included a $500,000 loan, when Santos had less than $8,000 in his personal and business bank accounts. 

Through the execution of this scheme, Santos and Marks ensured that Santos met the necessary financial benchmarks to qualify for the program administered by the national party committee.  As a result of qualifying for the program, the congressional campaign received financial support.

The Credit Card Fraud Scheme

In addition, between approximately December 2021 and August 2022, Santos devised and executed a fraudulent scheme to steal the personal identity and financial information of contributors to his campaign.  He then charged contributors’ credit cards repeatedly, without their authorization.  Because of these unauthorized transactions, funds were transferred to Santos’s campaign, to the campaigns of other candidates for elected office, and to his own bank account.  To conceal the true source of these funds and to circumvent campaign contribution limits, Santos falsely represented that some of the campaign contributions were made by other persons, such as his relatives or associates, rather than the true cardholders.  Santos did not have authorization to use their names in this way.

For example, in December 2021, one contributor (the “Contributor”) texted Santos and others to make a contribution to his campaign, providing billing information for two credit cards.  In the days after he received the billing information, Santos used the credit card information to make numerous contributions to his campaign and affiliated political committees in amounts exceeding applicable contribution limits, without the Contributor’s knowledge or authorization. To mask the true source of these contributions and thereby circumvent the applicable campaign contribution limits, Santos falsely identified the contributor for one of the charges as one of his relatives.  In the following months, Santos repeatedly charged the Contributor’s credit card without the Contributor’s knowledge or authorization, attempting to make at least $44,800 in charges and repeatedly concealing the true source of funds by falsely listing the source of funds as Santos himself, his relatives and other contributors.  On one occasion, Santos charged $12,000 to the Contributor’s credit card, ultimately transferring the vast majority of that money into his personal bank account.

The charges in the superseding indictment are allegations, and the defendants are presumed innocent unless and until proven guilty beyond a reasonable doubt in a court of law.

The government’s case is being handled by the Office’s Public Integrity Section, the Long Island Criminal Division, and the Justice Department Criminal Division’s Public Integrity Section.  Assistant United States Attorneys Ryan Harris, Anthony Bagnuola, and Laura Zuckerwise, along with Trial Attorneys Jacob Steiner and John Taddei, are in charge of the prosecution with assistance from Paralegal Specialist Rachel Friedman.  Former Trial Attorney Jolee Porter of the Criminal Division’s Public Integrity Section also provided substantial contributions to the prosecution.

The Defendant :

GEORGE ANTHONY DEVOLDER SANTOS Age:  35 Washington , District of Columbia

E.D.N.Y. Docket No. 23-CR-197 (JS)

John Marzulli Danielle Blustein Hass United States Attorney's Office (718) 254-6323

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