Abstract
Romance fraud, where an offender uses the guise of a genuine relationship for monetary gain, affects millions globally. Further to financial losses, evidence suggests victims may also be targeted for sextortion, where the offender either has images or claims to possess indecent images of a person and attempts to extort them for money. Research exploring the association between romance fraud and sextortion is limited, with little known about the characteristics of victims and their potential for financial loss. This article addresses this gap through a quantitative analysis of those who reported romance fraud which included a threat of sextortion. It identifies those who paid in response to the sextortion threat by a variety of situational and demographic variables and locates this group in the broader context of romance fraud. The implications of this study for an understanding of online fraud victimization are explored in detail.
Introduction
While there are many benefits to the use of online technologies to establish relationships, there are also new dangers; in particular, romance fraud which uses the guise of a genuine relationship for offenders to gain a financial advantage (Cross, 2020b). Romance fraud involves “relationships constructed through websites for the purpose of deceiving unsuspecting victims to extort money from them” (Coluccia et al., 2020: 25). Victims of romance fraud recorded over US$600 million in the United States during 2020 (IC3, 2021). Those in the United Kingdom reported £68 million lost (Wakefield, 2021), while Australian reported over AUD$131 million (ACCC, 2021), which was an increase from AUD$83 million lost in 2019 (ACCC, 2020). Given the low reporting rates of fraud (Smith, 2007, 2008), and the extent of non-financial harms also experienced by victims (Button et al., 2009; Cross et al., 2016), these figures likely to represent only a small proportion of actual losses.
The growth of online relationship tools has also enabled the rise of image-based sexual abuse which includes the non-consensual creation and distribution of private sexual images (McGlynn and Rackely, 2017). These crimes may involve the creation and distribution of sexually explicit content of minors (child sexually abusive materials) or “revenge pornography”/involuntary or non-consensual pornography, where images which were shared consensually within the context of a relationship and are later disseminated without consent (Citron and Franks, 2014). A burgeoning type of image-based sexual offense is sextortion, a portmanteau of “sexual” and “extortion,” which involves the threat to distribute intimate/sexual images or videos of a victim unless they comply with specific behavioral or financial demands (Jacobs and Franks, 2017; Patchin and Hinduja, 2020; Powell and Henry, 2019; Wolak and Finkelhor, 2016). While most image-based sexual abuse often has a public element where images are shared on websites or to other users through text or email, however, what makes sextortion unique is that it is private (Patchin and Hinduja, 2020). The central component of successful sextortion is silence; offenders use embarrassment, shame, and intimidation to extort their victims and to discourage them from reporting the crime (Citron, 2019).
Sextortion is a unique crime with distinct motivations. It can occur in cases involving any type of victim/offender relationship. In addition, the victims of sextortion differ from those of other image-based sexual abuse, in that adult men are frequently targeted. Despite the focus on minor victims, most often contacted for sexually abusive materials and images, and cisgender women, targeted by previous romantic or sexual partners to manipulate behavior, adult men are most likely to be contacted through transnational schemes for financial gain (O’Malley and Holt, 2020).
There is also some evidence to suggest that it is used by romance fraud offenders in an effort to extract larger amounts of money from victims (Whitty, 2013). Although research has explored these offenses separately, few have considered the extent to which sextortion may occur in the context of romance fraud.
Thus, this study attempted to investigate whether offenders engaged in romance fraud also engaged in sextortion schemes with their victims. This exploratory analysis utilized a sample of romance fraud reports made to Scamwatch, an Australian online reporting portal for fraud, between July 2018 and July 2019. A binary logistic regression model was estimated to explore the situational, demographic, and vulnerability indicators of those who reported sextortion in the broader sample of romance fraud reports. A second binary logistic regression model was estimated to explore the factors associated with financial losses among those who reported sextortion victimization. The findings demonstrated distinct situational and personal factors associated with reporting sextortion, though characteristics were not associated with reporting financial losses. The implications of this analysis for an understanding of online fraud and victim reporting were explored in detail.
Understanding romance fraud
Romance fraud can be understood as “instances where a person is defrauded or scammed by an offender through an internet-enabled medium such as an online dating website or social networking site, in what the victim perceives to be a genuine relationship” (Offei et al., 2020: 3). The evolution of the Internet has allowed offenders to reach potential victims globally with increased ease and effectiveness. Offenders have traditionally used a range of online dating websites and apps to connect with victims but have increasingly turned their attention to broader social media platforms (Eseadi et al., 2021: 66), including Facebook and games such as Words with Friends (ACCC, 2020).
The goal of the offender in all fraud offenses is financial reward, and the use of intimate relationships to achieve this is a particularly effectively, though harmful tactic. It explicitly seeks to exploit the personal connection between the victim and the offender, with “the portrayed end goal for the victim . . . typically that they will be in a committed relationship rather than merely in receipt of large amounts of money” (Barnor et al., 2020: 2). The victim’s focus is, however, on the relationship and ensuring it is maintained.
Offenders use a range of grooming techniques to establish a connection with a potential victim (Whitty, 2013). Once fraudsters develop an initial sense of trust and rapport with the victim, they “will casually report events related to another invited story which will be suitable for building a plausible frame for a subsequent request for money” (Kopp et al., 2017: 208). These events encompass a variety of scenarios including health emergencies, family needs, criminal justice problems and business concerns (Cross and Holt, 2021; Holt and Graves, 2007). If the victim complies, these requests will usually persist and escalate in the amount requested (Cross et al., 2018; Drew and Cross, 2013).
The impacts of romance fraud can be life changing, as victims experience both financial harm as well as the loss of their emotional relationship to their fraudster (Whitty and Buchanan, 2012). For some victims, the loss of the relationship has a greater negative impact compared to the losing of money (Cross, 2020b). The consequences of romance fraud affect both financial and non-financial aspects of a victim’s life, including a decline in physical health, deterioration of psychological and emotional wellbeing, relationship breakdown and dysfunction, unemployment, homelessness, and in extreme cases, suicide and/or suicide ideation (Button and Cross, 2017; Button et al., 2009, 2014; Cross et al., 2016).
Understanding sextortion and its consequences
Image-based sexual abuse can also intersect with romance fraud. In particular, sextortion uses coercion, intimidation, and threats to achieve various goals, such as victim compliance in intimate relationships, the production and sharing of child sexually abusive materials, or monetary gains (Acar, 2016; Bates, 2017; Draucker and Martsolf, 2010; National Crime Agency, 2018; O’Malley and Holt, 2020; Wolak and Finkelhor, 2016). The offense involves sexual exploitation where the offender uses the victim’s fear and torment as a weapon to manipulate their behavior (Wittes et al., 2016).
Sextortion typically takes one of two forms: (1) an offender threatens to share the victim’s explicit images or videos to extort them, or (2) the victim is coerced to send images of themselves to the offender using threats of exposure or harm (Wittes et al., 2016). Images or videos may be obtained by the offender in several ways, including “catfishing” or using a fake identity through social media accounts to develop a “relationship” with the victim (Carlton, 2020). Others employ hacking victims’ device directly or using remote devices to hack into webcams (Carlton, 2020).
Sextortion is unique in that perpetrators may not actually possess victims’ sensitive materials but use the perception that they have the materials in order to threaten and intimidate victims into complying with requests (O’Malley and Holt, 2020). For instance, some offenders utilize email-based phishing scams to deceive the victim into believing they possess their sexually explicit materials. The number of sextortion incidents reported to law enforcement has increased exponentially. In the United States, the Federal Bureau of Investigation’s Internet Crime Complaint Center (IC3) reported that by summer of 2021, they had received over 16,000 complaints with financial losses over US$8 billion. The IC3 detailed that approximately half of sextortion victims were between the ages of 20–39, victims over the age of 60 were the most likely to report their victimization, and victims below age 20 were less likely to report the crime (FBI, 2021).
The relationship between romance fraud and sextortion
While there are established bodies of research exploring romance fraud (see Cross, 2020b for a summary) and sextortion (see O’Malley and Holt, 2020), there is limited scholarship exploring the association (if any) between these two types of offenses (Cross et al., 2022). Whitty (2013) indicates that sexual abuse is a potential stage that some individuals experience as part of their romance fraud victimization. This is reiterated by Anesa (2020) who asserts that they “can be part of the same fraudulent attempt, and may of course coexist and overlap, and the former [romance fraud] can in some cases, lead to the latter [sextortion]” (p. 2).
The use of sextortion as a potential tool to gain financial reward from a victim is consistent with the overall financial motivation of fraud offenders. Sextortion, in this sense, can be viewed as a technique designed to continue to control victims and maintain compliance for monetary requests. Sextortion may also occur as an escalation in offender methods if a previous request for money was unsuccessful. Threatening to expose an intimate image and/or recording of an individual taken in the context of a personal relationship may be an effective tool to obtain further money transfers. Using the threat of sextortion outside, the context of an established relationship is also likely to achieve success on the part of the offender in gaining financial payments from some victims who are desperate to protect themselves.
Thus, it is important to explore the situational and personal characteristics of victims who reported sextortion in the context of romance fraud, and the degree to which these factors are associated with financial losses for victims of sextortion generally. This study was guided by the following research questions:
Among those reporting romance fraud, who is also targeted by sextortion?
Is this group different to the broader category of romance fraud victims?
What factors (if any) differentiate the decision between these two groups to send money in response to the threat of sextortion?
To answer these questions, two binary logistic regression models were estimated. The first explored who reported sextortion victimization among all those who reported romance fraud generally. A second model was estimated using only those who reported sextortion to identify the unique characteristics associated with reporting financial losses to the offender.
Method
Data
This article utilized romance fraud data provided by the Australian Consumer and Competition Commission (ACCC) to one of the authors (Cross; for other publications related to this dataset, and further details on the methodology, see Cross et al., 2022; Cross and Holt, 2021; Cross and Layt, 2021; Cross and Lee, 2022). Upon request, the ACCC provided a copy of romance fraud reports lodged by complainants on the Scamwatch portal (online reporting portal for fraud in Australia) during the period July 2018 to July 2019 (inclusive). An ethics exemption for this dataset was received from the Queensland University of Technology Human Research Ethics Committee (HREC; #1900000738).
During the selected timeframe, Scamwatch received 4354 reports in the romance fraud category. Of those, 3463 (80%) complainants ticked a box that indicated their consent to share their reports for research purposes. As a result, the ACCC were able to provide a (de-identified) excel spreadsheet containing these 3463 reports. Individual reports included the following information: demographic details of the complainant (gender, age, and jurisdiction both within Australia and overseas), details about the fraud (how the approach was received, the location of the alleged offender), and any losses incurred (amount, payment methods, sensitive details lost). Vulnerability indicators of the complainant were also included, particularly around age (young and elderly), disability, sickness, financial hardship, and location (rural/remote). The de-identified free text field where each complainant described in their own words what occurred was also made available.
Upon review of the data, 204 duplicate entries were removed, leaving a final total of 3259 distinct reports available for analysis. There was some degree of missing information across these remaining reports since respondents may not have provided responses to all demographic questions or excluded details from their narrative. Due to missing data across various measures, the final sample for analysis included 2686 total cases of romance fraud reported.
Of those cases, 253 were reported as involving sextortion. This was determined through a manual coding process of reading through the free text narrative to determine if sextortion was evident in the incident. Of the cases where sextortion was involved, 43 had missing data in their report, leading to a final sample of 210 reporters (see Table 1 for comparison of sextortion complainants to the full sample). With respect to sextortion complaints, it should be noted that the free text variable field was mandatory, and simply asked complainants to “briefly describe the scam.” Complainants were given up to 1500 characters in which to do this, with some choosing to provide a few words compared to others who wrote long-detailed paragraphs. It is likely that the presence of sextortion is under-represented in the current dataset given that the ability to determine the existence of sextortion in each complaint was ascertained through a reading of this variable, rather than a specific question in and of itself.
Comparative descriptive statistics for sextortion victims relative to romance fraud victims.
Limitations
It should also be noted that while inherently valuable to an understanding of online fraud victimization, the data are not generalizable to all victims. Specifically, the Scamwatch portal was an online reporting mechanism that could be accessed by anyone across the world. Furthermore, there was no screening or human interaction associated with the lodging of a report. This is similar to other online reporting portals for fraud, such as the Internet Crime Complaint Center (IC3; the United States), ActionFraud (the United Kingdom), and the Canadian Anti-Fraud Centre (Canada). This is a limitation as there is no ability to check the quality and quantity of the data inputted by complainants (Cross, 2020a). Also as previously noted, not all fields were mandatory, and this resulted in several incomplete reports, some of which were removed for the analysis. Along these lines, these data focused solely on those reporting victimization experiences, which means the results may not be generalizable to the broader population of victims who do not report their experiences to law enforcement agencies or related bodies.
Third, all details within each report could not be independently validated. Thus, the data contain the details as remembered and framed by each complainant. The level of detail and focus of detail vary by each individual. The ACCC do not routinely verify information provided by complainants. Therefore, it was impossible to ascertain the accuracy of the data provided.
Regardless, the dataset provides unique and valuable insights into the experiences of romance fraud as described by the victim, particularly as it relates to the associated offense of sextortion. Furthermore, the nature of ACCC data allows for researchers to assess the relationships between victimization and factors associated with individuals who self-identified with a number of potential vulnerability factors (related to age, disability, health, financial hardship, language, and geographical location) as well as Indigenous identity. This covers a range of populations which have been largely excluded or are invisible in prior romance fraud and sextortion research, making these data extremely valuable to better understand the degree to which diverse populations are affected by sextortion (as it relates to being targeted by romance fraud).
Analysis
Dependent variable
This analysis focused on two key binary dependent variables. The first measure captured whether the individual reported their experience as sextortion (0 = no, 1 = yes). This analysis employed the full reporting sample so as to identify any significant factors associated with filing a complaint related to sextortion (see Tables 1 and 2). Then, a model was estimated using only those who reported sextortion to assess any significant factors associated with financial loss (0 = no, 1 = yes). This variable reflects those complainants who either noted in a checkbox that they suffered a financial loss or indicated in the free text section of the report that they had sent money to an offender(s) (see Table 2).
Descriptive statistics.
ESL: English as a second language.
Reading the free text section was essential to determine monetary loss, as well as gain a more comprehensive understanding of who sent money as a result of the sextortion threat. As there was limited verification by the ACCC on all financial losses, a binary variable was used in lieu of the reported dollar figure to better capture whether individuals sustained a financial loss. In addition, this allowed for an assessment of factors associated with monetary loss without being affected by the complainant over or under-reporting or over-reporting of a specific dollar value.
Independent variables
When individuals filed a complaint, they were also presented with various drop-down menus and options related to both their personal demographic characteristics and the nature of the offense. For instance, complainants could identify the way in which they were initially contacted by the offender, including, (1) email, (2) fax, (3) Internet, (4) in-person, (5) mail, (6) mobile apps, (7) phone (voice), (8) social networking/online forums, or (9) text message. Only one category could be selected by a complainant, and the majority identified being contacted through social networking sites or forums. Thus, a binary measure was created to reflect contact through social networks.
Respondents were further asked to identify what sorts of information they lost in the course of the offense. The reported loss of personal details was included to assess any connection between the loss of sensitive information and the sextortion request. There was no additional information provided to complainants so that they could better understand what exactly the term personal details included, so it is possible that each may have interpreted this differently. Therefore, the self-report nature of this measure may have been affected.
Complainants were asked whether they resided in Australia or an international jurisdiction (0 = Australia, 1 = international). Demographic variables were captured in reports to better understand the extent to which victims may fall into protected or vulnerable populations. Specifically, complainants were presented with a series of checkboxes to indicate their (1) disability status, whether English is a second language (ESL); if they are living in financial hardship; if they reside in a remote community; have a chronic/serious illness; and identify as Indigenous. Again, this information was not verified by the ACCC, and there was no additional information was provided to respondents to clarify these terms or verify their responses. Thus, it is unknown whether the complainant correctly identified or indicated that they fall into one of these categories. There is potential that they may have excluded information or perhaps selected options in error. As a result, these limitations must be considered.
Two additional control variables were included in the analyses. First, a categorical variable for complainant age was included (1 = 18–24, 2 = 25–34, 3 = 35–44, 4 = 45–54, 5 = 55–64, 6 = 65 and above, which reflected the age categories provided by the ACCC). Second, a binary variable was created to reflect complainant the gender options provided to respondents (0 = male, 1 = female). Complainants were also given the opportunity to not report a gender, but those cases were excluded from the quantitative analyses presented below for the sake of parity in the analysis.
Findings
The correlation matrix (see Table 3) demonstrated that reporting sextortion experiences were correlated with an individual being contacted through a social network, experiencing no financial loss, and losing their personal details. In addition, reporting was correlated with those who reported English as a second language, not reporting financial hardship or chronic illness. Finally, being young and being a male were correlated with sextortion reporting.
Correlation matrix (n = 2686).
ESL: English as a second language.
p < .05; **p < .01.
Given the univariate relationships observed, there was sufficient support for a multivariate statistical analysis. A binary logistic regression model was estimated to assess any factors associated with reporting sextortion victimization among those reporting romance fraud generally. There were no issues observed with respect to multicollinearity as no variance inflation factor (VIF) was higher than 1.099, and no tolerance was lower than .905. The findings indicated that those who reported sextortion victimization were more likely to be contacted through social networking sites (Exp(B) = 1.723, p < .001), lost their personal details (Exp(B) = .244, p < .001), and were less likely to have experienced financial loss (Exp(B) = 2.969, p < .001; see Table 4). In addition, they were more likely to be young (Exp(B) = .217, p < .001) and male (Exp(B) = .217, p < .001). No other personal characteristics were significant, suggesting few factors differentiate sextortion victims among those reporting romance fraud.
Binary logistic regression model estimating sextortion reporting (n = 2686).
ESL: English as a second language; SE: standard error.
–2LL = 1066.940; chi-squared = 406.650***; Nagelkerke R2 = .333.
p < .05; **p < .01; ***p < .001.
A binary logistic regression model was then estimated to assess any factors associated with reporting financial losses as a consequence of their sextortion experience (see Table 5). The findings demonstrated that the point of offender contact was not significantly associated with the likelihood of paying a sextortion offender. Those who did not lose their personal details (Exp(B) = .261, p < .001) were more likely to experience financial losses. In addition, those who reported living in financial hardship (Exp(B) = 6.306, p < .01) and having a chronic illness (Exp(B) = 41.136, p < .05) were more likely to pay the offender. The language skills of the victim, their living in remote communities, living in Australia, age, and gender were all non-significant.
Binary logistic regression model estimating financial losses (n = 210).
ESL: English as a second language.
–2LL = 150.585; chi-squared = 28.678**; Nagelkerke R2 = .222.
p < .05; **p < .01; ***p < .001.
Discussion and conclusions
This analysis examined the behavioral and demographic factors associated with reporting both sextortion victimization and reporting financial losses from this form of crime. The findings indicated that individuals who reported sextortion victimization were more likely to be contacted through social networking sites and have lost their personal details. They were less likely to have experienced financial loss and were more likely to be young and male. This is consistent with the literature on sextortion, as most young sextortion victims are contacted through social media in sextortion scams, and in these cases, the goal is not financial, but to procure images (O’Malley and Holt, 2020; Wittes et al., 2016). While males in this sample were more likely to report, the best estimates indicate that only half of young men report their sextortion victimization, and most do not disclose to law enforcement or reporting websites (Wolak et al., 2018). Thus, the number of young men who experience sextortion victimization is likely much higher than estimated through official reports or survey data.
In addition, for those who lost personal details, there may be a greater fear of being “exposed” and of images being distributed with identifying information. Some offenders report that the use of personal details makes the threats more effective (United States v. Adam Paul Savader, 2013). These victims may have perceived that there was a likelihood of harm, which may have increased their willingness to report the crime.
Those who reported living in financial hardship and had a chronic illness were more likely to pay the offender. The relationship may be due to the potential that these individuals may be more vulnerable to fraud targeting, as there is some evidence individuals with chronic illnesses report greater time spent online, particularly searching for health information (Madrigal and Escoffery, 2019). There is also some evidence that individuals living in economically disadvantaged situations spend the same or more time online relative to those in higher income levels (Hutt, 2016). Additional research is needed to assess the extent to which these individual characteristics are consistent predictors of sextortion victimization with larger samples both within Australia and in a global context.
It should also be noted that the results of this analysis differ from what is generally known regarding romance fraud victims. There are few consistent, significant demographic factors associated with romance fraud victims, as some evidence suggests they may come from any background generally (ACCC, 2019; Button and Cross, 2017; Whitty, 2018). There are also inconsistent relationships between socio-economic status and romance fraud victimization (Button and Cross, 2017), which is different from what is known regarding sextortion victimization. Further study is needed to better disentangle the ways that sextortion and romance fraud victims differ from one another.
Among sextortion, there are gendered patterns—women are more likely to be targeted by those with whom they were romantically involved for behavioral demands (e.g. continuing the relationship) and men are more often losing money to transnational sextortion schemes (O’Malley and Holt, 2020). The findings of this study suggest that perpetrating sextortion can also occur in romance fraud schemes, which may warrant its own category of sextortion offending (see Cross et al., 2022, for further discussion on this).
The results of this analysis may also be a function on the data used. While these data were reported to the Scamwatch portal and classified under the category of romance fraud, as was noted earlier, this is a self-reporting mechanism that does not have any human intervention. It is well known that when individuals experience fraud and other similar incidents, they face barriers and challenges to reporting (Button and Cross, 2017; Cross, 2020a; Cross et al., 2016). It is therefore plausible that not all complainant reports fit within what is understood as romance fraud, in that there is no pre-existing relationship prior to the requests for money. In this way, these results highlight the need to better differentiate romance fraud from sextortion where needed, as well as understand how it is used deliberately as a tool of manipulation and coercion for romance fraud offenders (see Cross et al., 2022, for a more nuanced and comprehensive discussion of this).
The consequences of sextortion for the victims are often devastating, both financially and emotionally. In some cases, victims may engage in self-harm or suicide attempts as a result of their experiences (Wittes et al., 2016). The factors associated with victimization in this study highlight the need for prevention and education efforts tailored to specific populations. For instance, social media companies could provide more robust information and awareness campaigns to their user base regarding the risk of victimization (Wittes et al., 2016). Victim testimonials could also serve an important role in de-stigmatizing sextortion victimization for others who may be experiencing this crime or for those who may be at risk. Providing a point of connection to specific demographic groups could also be of value, such as including male victims in any campaign so as to ensure they recognize their risks.
There are several future areas to be considered based on the limitations to these results. First, given this sample population primarily reflected individuals living in Australia, it is important to consider this as a comparative population to many other Western and European nations. Future research is needed with a comprehensive sample population to better understand the nature of sextortion victimization in various geographic contexts.
In addition, the data did not provide distinct insights into the reasons individual victims responded to any sextortionist’s schemes. There was only one free text variable and the type of detail provided by respondents carried significantly as noted. In this way, future research should ask victims of sextortion about their decision-making processes and what factors led to filing official reports, including their motivations and expectations behind reporting. Directly engaging victims about their reporting can help to inform prevention efforts, policy, and practice. In turn, researchers can identify any potential barriers in reporting, as well as specific points of intervention to reduce future victimization. It can also seek to better address any help-seeking behaviors evident behind the reporting of sextortion. Overall, the results of this analysis provide an important foundation for further work to explore the nuances highlighted and seek to both reduce the success of these approaches as well as better support those who are targeted.
Footnotes
Acknowledgements
The authors would like to thank the Australian Competition and Consumer Commission (ACCC) for their provision of data and their ongoing support of research in this area. The views expressed in this article are those of the authors alone, and do not necessarily represent those of the Australian Government. All errors and omissions are the sole responsibility of the authors.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
