Abstract
Fraud and scams are some of the most common crimes in the world, inflicting staggering emotional, financial, health, and psychological suffering on millions of individuals each year. Despite this widespread and extensive impact, the psychological research on what renders some individuals more susceptible to fraudulent solicitations, what mechanisms scammers use to lure potential victims, what therapeutic programs can help victims, what educational/preventive programs can reduce compliance, what can be done to increase reporting, and what policies are needed to safeguard the public is just emerging. To address this pressing social problem, this article has several goals. First, it is designed to provide readers with state-of-the-art insights into fraud research: what has been done thus far and what is urgently missing. Its second purpose is to highlight the urgency of the problem and encourage researchers to conduct relevant research in their domain of expertise. Our primary goal, however, is to reach beyond the academic sphere. To fight fraud, we must unite forces with private and not-for-profit organizations, education providers, financial institutions, government entities, grassroots organizations, international organizations, law enforcement agencies, and many more. To that end, we hope this article draws the attention of a wide range of stakeholders and encourages collaborations that produce direct action.
Keywords
On October 31, 2024, Charlotte Cowles—a journalist who at times reports on financial matters—received a phone call from a person regarding suspicious activities on her Amazon account. The person knew vital information about Cowles, including her phone number, the last four digits of her social security number, and her date of birth. After speaking to this so-called “Amazon customer representative,” Cowles was transferred to “Calvin Mitchell,” who was supposedly working for the Federal Trade Commission (FTC). Within minutes, Cowles learned that she, or someone who identified as “her,” was involved in a wide range of serious crimes, including money laundering and drug trafficking, and that warrants for her arrest existed in both Maryland and Texas. Calvin reassured her that he was there to help, and he would transfer her to the lead investigator of her case at the Central Intelligence Agency (CIA). The colleague at the CIA (“Michael”) would resolve the case and ensure that the $80,000 in her savings account was safe as long as Charlotte spoke to no one and followed their strict protocol. There was no time to waste, and any deviation from the protocol would jeopardize their ability to help her. Aside from remaining silent, the most important next step to ensure the safety of her savings was for Charlotte to withdraw $50,000 from her bank and to hand it over to one of Michael’s associates for safeguarding. Cowles did as she was instructed (see Cowles, 2024).
Cowles’s story raises two important questions, namely how someone like her could fall prey to such a scam and whether it could happen to anyone. As we show, although some individuals might be more susceptible to scam solicitations, scammers have been honing a wide range of social-engineering tools, persuasion techniques, and ways in which to exploit human psychological vulnerabilities to tailor their nefarious activities to victimize all types of people. It is no wonder that Cowles felt as if the scammer(s) “waged psychological warfare” against her. This psychological warfare, most likely, will intensify in prevalence and sophistication. Psychologists, therefore, are in an excellent position to (a) understand the mechanisms and tools scammers deploy in waging this war, (b) develop educational and prevention programs to help individuals become more resilient, (c) design support systems for victims and their social networks (i.e., family and friends), (d) collaborate with academics from different disciplines, and (e) lobby policymakers and other stakeholders (as they have done in antismoking campaigns and promoting mental-health awareness). To achieve real progress, we will need a coordinated effort from a wide range of stakeholders, one that uses a range of measures (e.g., economic and legal) and presents a unified front against fraud.
The Fraud Crisis: An Overview
Cowles’s case is far from unique. Every day, millions of people across the globe receive fraudulent letters, phone calls, texts, and, more frequently, emails or notifications on their social networking sites (SNSs). Fraud and scams (we use these two terms interchangeably because they are both commonly used in academic literature and popular media) have become so prevalent that they are one of the most common crimes across the globe. In the United Kingdom, scams account for over 40% of all reported crimes (Home Office, 2023). In the United States, according to the Global Anti-Scam Alliance (2025), 22% of American adults have lost money to scams. The 2024 Global State of Scams report revealed that roughly 50% of the world’s population encounters a scam solicitation at least once a week (Rogers, 2024). 1
Scams not only are ubiquitous but also carry an enormous financial price. Estimates from 2019 suggest that the price tag of scams for people, organizations, and governments is more than $5 trillion a year (Gee & Button, 2019), roughly equivalent to the 2024 U.S. budget, or that of Germany, France, Italy, and the United Kingdom combined. Moreover, because a substantial amount of this money is being channeled toward organized crime, terrorist organizations, and rogue states, the European Union (EU), U.K., and U.S. governments view fraud as a threat to their economic and national security (EU Agency for Law Enforcement Cooperation [Europol], 2025; Federal Bureau of Investigation [FBI], 2025; Home Office, 2023).
The price tag associated with scams is not only financial. Several reports have shown that victims experience severe emotional, health, and psychological impacts after being scammed (Consumers, Health, Agriculture and Food Executive Agency [CHAFEA], 2020; Low & Lally, 2024). Interviews with fraud victims, likewise, expose that victims are as, if not more, concerned about the psychological harm compared with their financial losses (Coluccia et al., 2020; Smith et al., 2024). Moreover, because of its nature, fraud often strains victims’ social support networks, further reducing their capacity to seek and find help, yet there are very few bespoke treatments designed to help victims deal with the psychological consequences or provide support (Sousa-Gomes et al., 2024).
Moreover, according to some data (Koning et al., 2025; Office for National Statistics, 2022), close to 90% of victims fail to report to any agency, whether law enforcement, their bank, or other related entities, for a myriad of reasons such as not knowing whom to report to, lack of trust in law enforcement agencies, and feeling embarrassed. Even when reporting to law enforcement agencies, many victims are told that not much can be done to help them or recover their money (Cross & Blackshaw, 2015). One estimate suggests that only 5% of victims manage to recoup part or all of their stolen funds (Rogers, 2024). To make things worse, investment in fighting fraud is rather limited. To date, many governments have been slow in grappling with and understanding the scope of the problem and devoting the necessary resources to address this menacing criminal activity (both in financial and policy terms). 2 According to the U.K. government’s admission, only 1% of police resources are devoted to fighting scams/fraud, despite being by far the most reported crime (Home Office, 2023). It is not surprising, then, that individuals do not believe that governments are doing enough to battle fraud (Hyde & Gibson, 2024).
If governments have failed to grasp the magnitude and rapid expansion of the problem, individuals might be in an even more precarious position to tackle fraud on their own. Scams, of course, have been part of humanity for centuries. What has fundamentally changed is the capacity of fraudsters to reach millions of people globally—and to do so almost instantly and at relatively little cost or risk of being caught. No other criminal activity was as quick to adopt and utilize technological innovations—such as the internet, FinTech, cryptocurrencies, and SNSs—that offered the capacity to reach almost any person on earth and transfer funds with ease and anonymity. Scammers can reach targets across the world from the safety of their homes or scam centers 3 and be located far away from law enforcement agencies’ capacity to intervene or apprehend them. Fraudsters are also able to gain confidential or private information about individuals from SNSs—where individuals freely share personal information—by hacking into servers or purchasing information on individuals and their households from data brokers. Scammers have also been quick to adopt and use advances in artificial intelligence (AI) and machine learning to create ever more sophisticated and realistic scams in any language they choose (Europol, 2025).
Fraud also has several characteristics that distinguish it from other types of crimes. Unlike many other crimes, fraudulent activities rely on technological innovations such as the internet and other forms of mass communication. Fraud is not bound by location in the sense that one can defraud individuals anywhere on earth, and physical proximity is of little or no importance. Moreover, in many cases, individuals might not realize that they have been defrauded or that a crime has taken place. It can take days, weeks, or even months before one fully comprehends that they have lost money; some investment and romance scams can unfold over months. Importantly, fraud or scams require the victims’ so-called cooperation at one level or another (hence Charlotte Cowles’s feeling that scammers were waging psychological warfare against her). That is, victims must engage with the fraudsters, provide them with (personal) information, click on websites, or send funds. Last, some fraud victims, being financially and often emotionally invested in the scammers’ false promises, deny or refuse to believe that a crime took place despite being confronted with clear evidence by law enforcement agencies, family members, and financial institutions (possibly helping to explain the low rate of reporting fraud). This, in turn, leads to what several scholars have termed “chronic fraud compliance”—falling victim to fraud multiple times despite intervention from concerned parties (Financial Industry Regulatory Authority [FINRA], 2021).
Two key related psychological questions emerge from these observations on fraud victimization. First, are some individuals more likely to respond to fraudulent solicitation? And second, what techniques or methods do fraudsters use to both deceive individuals and persuade them to send money? In other words, fraudsters must accomplish two separate but related tasks. They must first be able to convince individuals about a certain narrative, which might include providing false information about an investment, impersonating another person, pretending to be a legitimate company or a charity, or stating that there is a problem with one’s (Amazon, bank, etc.) account. The second step is to convince individuals to part with their money. Fraudsters thus must rely on a wide range of persuasive and psychological techniques to deceive people and convince them to send their hard-earned money. Uncovering these techniques offers the opportunity to develop interventions that address two paramount junctures: helping individuals flag possible scams at an early stage and developing interventions and mechanisms that prevent the transfer of funds (e.g., cash, cryptocurrencies, gift cards). We address these key junctures below by reviewing and analyzing techniques used by scammers, as well as offering means to tackle them on both the individual and institutional (e.g., banks) levels.
Historically, scam victimization was conceived as an older adult issue. Organizations such as ageUK and AARP have long championed awareness among their members, and much, although not all, of the early psychological research on scams and scam vulnerability was focused on older adults or noted the effect of age (e.g., Anderson, 2013; Jorna, 2016; Lee & Soberon-Ferrer, 1997). Hence, we probably know more about the link between age and scam vulnerability than any other characteristics. Yet the focus on older adults as the primary target of scammers and as the most frequent victims of scams no longer seems to accurately represent the scam landscape. A growing body of research and surveys (FTC, 2020; Hyde & Gibson, 2024; Liverpool Victoria Financial Services, 2024) from across the globe paints a far more complex and nuanced picture, suggesting that scammers target different age groups with different scams (Better Business Bureau [BBB] Institute for Marketplace Trust, 2024) and that the relationship between age and victimization is no longer linear or increases with older age. In fact, according to several studies (Social Catfish, 2025; UK Finance, n.d.), individuals under age 25 comprise the most rapidly growing group of victims.
Aside from age, researchers have explored a plethora of other demographic factors, such as income, and personality characteristics, such as risk-taking and impulsivity, that might help explain vulnerability to scams. Indeed, gaining a better understanding of why some individuals are more vulnerable is key to the development of bespoke and effective prevention programs. At the same time, given the grim statistics about the scamming industry and use of sophisticated technologies, it is essential to emphasize that everyone is at risk, and anyone can become a victim. Moreover, confidence in one’s ability to detect and handle fraudulent solicitations might prove to be overconfidence (Balakrishnan et al., 2025), leading individuals to lower their guard.
Developing intervention programs and clinical/psychological support to aid victims is essential to reduce the rate of victimhood and support existing victims. Yet this is unlikely to be enough. Tackling any complex phenomena requires interventions on multiple levels and from multiple stakeholders, and at times collaboration among international stakeholders. We believe that an approach akin to the very successful antismoking campaign could serve as an inspiration. Although psychological interventions have no doubt proven to be effective in helping reduce smoking rates (Flay, 2009), they represent only one piece of the puzzle. To reduce smoking, policymakers and other agencies have enacted laws, allocated financial resources, levied taxes, initiated public-health campaigns, reinforced advertisement bans, and taken tobacco companies to court. No single measure was sufficient on its own. Rather, it was the joint efforts that led to a decline in smoking rates from 42.6% in the 1960s to 11.6% in 2021 (American Lung Association, n.d.). To achieve a similar reduction in fraud victimization would require a coordinated effort that would bring together telecommunication providers, education providers (schools and universities), law enforcement agencies, government agencies, financial institutions, SNSs (e.g., Meta, TikTok), tech companies (e.g., Google, Microsoft), third-sector organizations, and international stakeholders (governments and law enforcement agencies). It will also require coordinated campaigns and lobbying efforts by ordinary citizens and interest groups to highlight the problem to their political representatives and private-sector entities. Although such coordinated efforts are currently not taking place, similar challenges were faced by the early antismoking campaigners.
Despite the widespread economic, political, and psychological impact that fraud inflicts on millions of people, governments, and organizations, psychological research on the topic is methodologically limited. The number of publications specifically on fraud in behavioral economics, clinical psychology, cognitive psychology, forensic psychology, health psychology, judgment and decision-making, personality psychology, and neuropsychology is rather limited. 4 Research on judgment and decision-making, for example, has had a profound impact on the literature regarding economic decisions (e.g., saving) and has offered important practical and theoretical insights that have guided and impacted academic research, consumer behavior, and policy decisions. It is enough to mention the extensive research on decision-making, time discounting, and risk-taking to see the direct link between these lines of research and the challenges that fraud poses to individuals, organizations, and societies. Likewise, there has been immense progress in neuroimaging techniques and their ability to investigate deception, decision-making, and risk-taking. Yet one would be hard-pressed to find a similar corpus of research (with nonclinical or young/middle-aged participants) on fraud. And there is an acute need for clinical investigations regarding the impact of fraud on victims’ physical health and mental and psychological well-being and to generate and test interventions and better assessment tools that can benefit victims and their social networks. Moreover, an interdisciplinary approach—combining insights and methods from computer science, criminology, economics, engineering, law, marketing, psychology, and public health (to name a few)—is urgently needed to address the complex nature of fraud.
A 2025 report by Europol warned that the impact and prevalence of fraud are likely to amplify and multiply. Echoing this sentiment, Sam Altman, the CEO of OpenAI, issued a warning that we are on the verge of a “fraud crisis” because of AI’s ability to imitate other people (Duffy, 2025). There is already enough evidence that Europol and Altman’s stark warnings are materializing. Our priority should be to prevent fraud from becoming an even worse epidemic. To provide psychologists and others with a solid starting point, we developed this article to offer a comprehensive (although not exhaustive) picture regarding the nature of scams, the characteristics and conditions associated with scam susceptibility, the “tricks” scammers use in their psychological warfare against individuals, the neuroscientific evidence about fraud, the emotional/health/psychological impact of fraud, evidence on the effectiveness of existing prevention programs, and coordinated actions needed to fight scams.
Scams and deception: definitions and differences
The terms “fraud” and “scam” can be defined in several ways. Here we draw on work from Titus et al. (1995) and view scams or fraud as “the deliberate intent to deceive with promises of goods, services, or other financial benefits that, in fact, do not exist, or that were never intended to be provided” (p. 54). On the face of it, scams share many features with deception. However, the literature on deception and scams has developed and exists mostly in parallel, with the two rarely feeding off and informing one another. 5 “Deception” is a broad term that entails misleading or lying to others, driven by a range of reasons that are not always nefarious or monetary in nature. One can deceive a partner regarding an affair, a police officer regarding an offense, or a client about why a project is late—or simply deceive others by omitting to provide information. The literature on deception and the ability to detect it is well established, with some consensus that individuals are not particularly good at detecting deception (Vrij et al., 2019).
Scams can be viewed as a special case of deception in which scammers not only intend to deceive their victims but also extract money (or information) from them. Deception is a means toward an end rather than the end in itself. Moreover, scams possess certain features that differentiate them from studies on deception. In most scams, there is little to no ability for a target to gather information aside from voice or written communication because most scams take place over the internet or phone. Nonverbal cues (e.g., facial expression) and many other cues that are often studied in the domain of deception are absent. Moreover, a class of scams (e.g., investment and romance) unfold over weeks and months, during which trust, positive emotions, positive reinforcement, and certain facts are established as a foundation for later exploitation. Most importantly, unlike studies on deception that focus solely on the ability to differentiate between true versus false statements, scams contain an important behavioral step—calling a number, sending money, clicking a link, and so on. That is, scams require not only the detection of the deception but also deciding on whether to act on it.
Susceptibility to scams: from demographic to personal characteristics
Researchers have long been interested in understanding whether certain characteristics distinguish scam victims and those who remain immune to these solicitations. In this pursuit, research has focused on both demographic characteristics, such as age and income, as well as measures of individual differences, such as risk-taking and financial literacy. Several researchers have developed conceptual frameworks to facilitate better understanding susceptibility to scams. These frameworks recognize that scam susceptibility is not driven by demographics or individual-level deficits in judgment and decision-making alone. Rather, victimization depends on a complex interplay between individual characteristics, contextual factors, and structural determinants such as the digital and financial ecosystems that connect scammers to their targets. Jones et al. (2015, 2019) argued that susceptibility to scams might be driven by three complementary but independent components. First, how persuasive is the scam message? Second, how does the receiver process the information or message (e.g., emotionally vs. rationally)? Last, what are the impacts of individual differences (Jones et al., 2015, 2019)? Jones et al.’s conceptual framework is nicely aligned with the framework developed by and described in Ebner et al. (2022, 2023), who intuited that to better understand susceptibility to fraud requires considering individual factors and how they interact with the deceptive context (for an illustration of these concepts, see Ebner et al., 2023). Building on these ideas, we first focus on individual characteristics: demographic factors and, thereafter, individual differences (e.g., risk-taking) and susceptibility to scams.
Susceptibility to scams and demographic variables
In the literature on frauds and scams, one of the most frequently assessed relationships is between age and scam susceptibility. A common assumption is that older adults are more susceptible to scams than young and middle-aged adults because of stereotypes such as greater cognitive impairment, social isolation, more trusting dispositions, and poor technological sophistication (see M. Ross et al., 2014). 6 However, data from both self-report surveys and national fraud complaint databases suggest that older adults report fewer victimization incidents than young and middle-aged adults (e.g., Anderson, 2019; Schoepfer & Piquero, 2009; van Wilsem, 2013). The Office for National Statistics (2016) indicated that adults aged 45 to 54 were the group most likely to be victims of fraud, which is similar to a 2017 population-based survey in the United States that found that self-reported victimization was highest among adults aged 35 to 54 (Anderson, 2019). Similarly, in a survey of nearly 30,000 individuals across Europe, CHAFEA (2020) found that individuals aged 35 to 54 were more likely to be fraud victims compared with other age groups. Data from a Dutch fraud-victimization survey (Koning et al., 2024) with close to 3,000 participants indicated that older adults were less likely to report being victims of purchase fraud, dating fraud, phishing, and spoofing.
Even studies that used experimental designs have found that older adults are less interested in fraudulent solicitations relative to young adults (Klapatch et al., 2023; Nolte, Hanoch, Wood, & Hengerer, 2021; Parti, 2022; Wood et al., 2018). An investigation by Mueller et al. (2020) presented young and older adults with two types of investment scams taken from research conducted by the FINRA. Their results showed that younger adults were more likely to respond favorably to one of the investment scams, and no age differences were found for the second investment scam.
The link between age and scam susceptibility might be further complicated by the nature of the scam. That is, older adults might be more likely to be targeted by phone and with bespoke scams that fit their age and interests (Button et al., 2024). The BBB Institute for Marketplace Trust (2024) concluded, in line with this idea, that although 35- to 44-year-olds were most likely to lose money from a scam overall, people in different age groups may be more likely to fall for different types of scams. For example, the BBB found that investment or cryptocurrency scams are the riskiest for people who are 45 and older. But employment scams were the riskiest for 18- to 44-year-olds.
Using fraud complaint data, DeLiema and Witt (2024) found that older adults were more likely to report victimization by tech-support scams and prize, sweepstakes, and lottery scams compared with other age groups, whereas young adults were more likely to report victimization by online shopping scams.
There are rising indications that young adults are the group seeing the largest increase in scam victimization and money lost (Australian Competition & Consumer Commission, 2020; Social Catfish, 2025; UK Finance, n.d.). According to the FTC (2024b), for example, young adults were almost twice as likely (44% vs. 24%) to report losing money to fraud compared with older people. Other surveys reveal that individuals aged 35 to 44 and 45 to 54 are exposed to scams more often and are more likely to report losing money to scams (BBB Institute for Marketplace Trust, 2024).
In comparison, studies that use perpetrator or law enforcement data have found a positive relationship between age and fraud. DeLiema et al. (2024) merged four longitudinal databases of victims’ contact information and their payments to global mail fraud enterprises. The databases were seized during federal law enforcement investigations, and victimization incidents spanned 20 years. The researchers found that as victim age increased, the odds of responding to a subsequent scam increased, even after controlling for the number of prior victimizations. In a study using law enforcement data from 23 fraud cases, Raval (2021) found that victimization rates were higher in older communities.
There are several explanations for the contradictory findings on the relationship between age and scam victimization. First, older adults may be less likely to report victimization in surveys and to government agencies compared with young adults. Admitting victimization may activate negative stereotypes and threaten an older person’s self-efficacy and financial autonomy. Acknowledging fraud also requires the victim to recognize the experience as a scam (instead of maintaining a false belief) and have the capacity to disclose the incident to authorities or in a research survey. Studies that exclude vulnerable adults, including adults with dementia, are likely to underestimate the prevalence of fraud in the older population.
Although older adults may report scams at lower rates than young and middle-aged adults, the costs of fraud are more severe. Older people have significantly more money stolen per incident when they are victimized (DeLiema & Witt, 2024; FTC, 2024b). Median reported losses based on 2024 fraud complaints to the FTC were $1,450 for those aged 80 and older compared with $450 to $500 for those aged 20 to 59 (FTC, 2024b). That being said, recent trends and reports cast further doubt over these findings as well (e.g., BBB Institute for Marketplace Trust, 2024), suggesting that young adults and middle-aged people are losing more money than older adults. It should also be noted that data from different countries might provide a different picture regarding who is being scammed more often and how much money is being lost to each age group. As scammers use more sophisticated profiling technologies, tailor and test new persuasion messages, and pay data brokers for detailed information on consumers, victim typologies will likely become more specific to each type of scam.
An examination of other variables, such as gender, presents a somewhat similar picture, in which the link between demographic factors and fraud victimization is complex and depends on the type of scam. For example, there has long been interest in the link between gender and risk of scam victimhood. Koning et al. (2024), for example, found that, overall, there were no gender differences in fraud victimization. However, the data revealed that males were less likely to report being victims of purchase fraud but more likely to report being victims of investment, prize, charity, dating, and phishing fraud. A study by Whitty (2020), which included more than 1,000 fraud victims, found that although women tended to report a higher rate of victimhood, the higher rate was contingent on the type of scam such that women were much more likely to be a victim of a consumer scam whereas men were more likely to be a victim of an investment scam (Whitty, 2020).
An earlier investigation presents a somewhat more nuanced picture. Drawing on data from the Older Consumer Behavior survey (commissioned by AARP), Lee and Soberon-Ferrer (1997) found that women who were 65 years old and over reported higher fraud vulnerabilities, whereas younger women (18–64) showed a somewhat reduced vulnerability (the data at the time did not include different types of fraud). A study by DeLiema et al. (2020), based on data from the 2016 Health and Retirement Study, found no gender differences. In another study, DeLiema, Li, and Mottola (2023) examined data from close to 1,400 Americans and Canadians who had previously reported being a fraud victim. In this study, DeLiema and colleagues did find that males were at higher risk, although gender differences were limited to opportunity-based scams. A survey among 300 Singaporean residents (Buse et al., 2024), however, found that males were significantly more likely to be victims of investment scams. Echoing these results, CHAFEA (2020) found that females were significantly less likely to be victims of fraud, and an analysis of more than 11,000 records by the Financial Conduct Authority (Graham, 2014) found that males were far more likely to be victims of investment fraud. A scoping review of romance scams reveals, in contrast, that females are at greater risk of becoming victims (Coluccia et al., 2020).
Experimental studies on scam susceptibility also provide mixed results. Nolte, Hanoch, Wood, and Hengerer (2021) presented participants with COVID-19 scams and found that males were more likely to express a willingness to respond to these solicitations. However, the authors did not find gender differences in response to sweepstakes scams. In an earlier investigation, Wood et al. (2018) found no gender differences in intentions to respond to mass marketing sweepstakes solicitations regardless of the size of the prize, the sender of the solicitation, or whether an activation fee was present. Kubilay et al. (2023) experimentally manipulated different types of scams and asked individuals to identify them. They found that females were slightly worse at detecting scams compared with males. In contrast, Kelley et al. (2023) examined participants’ ability to discriminate between real versus fraudulent websites. In a series of several studies, the authors found no gender differences in their ability to tell whether a website was real or fake.
There might be a reason to believe that fraudsters specifically target those with higher incomes because their capacity to extract more funds is higher. The Office for National Statistics (2016) found that individuals with a household income of £50,000 (about $65,000) are almost twice as likely to report being a victim of fraud compared with those who come from households with yearly incomes less than £10,000 (about $13,000), consistent with this possibility. Similar trends were also reported by CHAFEA (2020), in which individuals who self-identified as having a higher income were more likely to be victims of fraud, at least compared with individuals who self-identified as being at the bottom of the income scale. Data from more than 11,000 reports by the Financial Conduct Authority (Graham, 2014) revealed that as income increased, so did the probability of reporting being a victim of fraud. Wang et al. (2025) analyzed data from a representative sample of more than 4,200 Chinese adults. Their findings exhibited similar trends, in which higher income was associated with a significant increase in the likelihood of being a fraud victim.
Hyde and Gibson (2024) reported that individuals at the bottom (below approximately $27,000) and the top (above approximately $108,000) of the income scale experience a similar rate of victimhood (17%). Interestingly, Koning et al. (2024) found no relationship between income and susceptibility to fraud, results that also mirror work by Lee and Soberon-Ferrer (1997). An experimental study with older adults in the United States (Yu et al., 2023) found that levels of income (and education) had no relationship to individuals’ vulnerability to government impersonation scams.
DeLiema, Li, and Mottola (2023) found that financial fragility, defined as being unable to cover a $2,000 emergency expense, was significantly associated with victimization by “get-rich-quick” and other opportunity-based scams. Financial fragility was also associated with an increasing number of victimization incidents among mail fraud victims identified by law enforcement (DeLiema et al., 2024). The directionality of these effects is unknown; for example, in a representative cross-sectional survey of more than 4,000 Americans, Brenner et al. (2020) reported that fraud victimization was associated with an 8.7% decrease in individuals’ financial well-being score. There is likely a bidirectional effect of financial well-being on fraud victimization. Feeling financially insecure may increase a person’s willingness to engage in fraudulent offers; at the same time, the financial consequences of fraud victimization can cause even greater financial insecurity. Longitudinal research is needed to assess the augmentative relationship between these two factors.
There are several reasons why the association between income (and financial fragility) and susceptibility to scams might be difficult to discern. First, higher income may be related to greater financial losses and hence a stronger incentive to report falling prey to scams. Previous work, moreover, has shown that many individuals are uncertain as to who they should report the crime to, and when they do report it, they are informed that not much can be done (Rogers, 2024). There are indications that low socioeconomic status (SES) is related to lower confidence and trust in the police and other governmental institutions (Panditharatne et al., 2021; Reisig & Holtfreter, 2007), possibly reducing the probability of reporting. Data also indicate that scammers target more affluent individuals because they have more available funds (Wang et al., 2025). Individuals with low SES, however, might be at greater peril to the impact of fraud because their capacity to withstand financial losses might be lower (Hyde & Gibson, 2024).
Available data present a similar mixed picture regarding the association between education level and susceptibility to fraud. Lee and Soberon-Ferrer (1997) found that education levels had an inverse relationship to fraud susceptibility, placing individuals with lower education at higher risk of victimhood. Wood et al. (2018) and Mueller et al. (2020) also found that higher education was linked with a lower intention to respond to mass marketing solicitations.
Whitty (2019a) and Nolte, Hanoch, Wood, and Hengerer (2021), in contrast, reported that individuals with higher education were more likely to fall prey to fraud. DeLiema et al. (2020), likewise, found that being better educated was associated with higher rates of investment-type scam victimization. Low & Lally (2024) reported that individuals with higher education (and income) are at higher risk of fraud. The CHAFEA (2020) study on fraud across Europe lends further support to these findings, showing that higher education attainment was associated with a greater probability of experiencing fraud, and an experimental study focusing on detecting phishing emails (Butavicius et al., 2022) also found that less educated people were better at the task. A report examining scams in France (Global Anti-Scam Alliance, 2025) that drew on responses from 2,000 people indicated that those most likely to experience a scam had a high level of education. The findings from France are nicely aligned with Koning et al.’s (2024) conclusion that “a higher education level significantly predicted more exposure to investment fraud, prize fraud, debt fraud, friend-in-need fraud, phishing, and spoofing” (p. 454).
Others, however, have found no relationship between education and susceptibility to scams. Yu et al. (2023) reported that education had no relationship to older adults’ intention to respond to fraudulent solicitations. On the basis of data from the 1996 and 1997 EXCEL Omnibus Survey commissioned by AARP that included slightly more than 1,200 respondents aged 50 and over, Lee and Geistfeld (1999) also found that education did not impact consumers’ intention to respond to fraudulent solicitations.
Education might be considered a safeguarding factor against deleterious decisions. Possibly counterintuitively, educational levels not only do not seem to serve as a protective measure; they might even act as a risk factor. Although it is difficult to draw a precise conclusion from the literature, there is enough and growing evidence that individuals with higher educational levels are more likely to fall prey to scams. What can help explain this link? First, educational levels are typically associated with higher income, which might mediate some of the results. That is, scammers might specifically target more affluent individuals who also happen to be more educated. Second, there is evidence to suggest that education is linked to higher confidence levels in a wide range of settings. Mishra and Metilda (2015) found that overconfidence was positively associated with levels of education among investors, Martínez-Costa et al. (2023) showed that higher education was linked to greater confidence in the detection of misinformation (although not related to performance), and Scheibe et al. (2014) found that high-confidence older adults were more likely to believe persuasive but deceptive telemarketing pitches. There are also indications that overconfidence is inversely related to the ability to detect and handle fraudulent solicitations (Anderson, 2016; Pressman, 1998; Wood et al., 2023).
One additional demographic variable has been studied: ethnicity. The literature on ethnicity should first be qualified because categories of ethnic minorities differ across nations, and much of the literature on ethnicity emerged from the United States and the United Kingdom. 7 Moreover, there is a paucity of data on the link between ethnicity (or race) and fraud victimization. Data from the United States, for example, suggest that African Americans and Hispanics are more likely to report being victims of fraud. An examination of the data by Anderson (2019) showed that African Americans (19.2%) and Hispanics (17.3%) are slightly (although not significantly) more likely to report being a fraud victim compared with their non-Hispanic White (14.9%) counterparts. And although not including ethnicity per se in their analysis, Koning et al. (2024) reported that a non-Western immigrant background was significantly linked to being a victim of fraud (e.g., investment fraud, prize fraud, debt fraud, dating fraud, friend-in-need fraud, phishing, and spoofing). Poppleton et al. (2021) echoed the sentiment that limited research exists on the link between ethnicity and fraud victimization but also suggested that some ethnic minorities are at a slightly higher risk of experiencing fraud.
Experimental studies present, however, a somewhat different perspective. Han et al. (2021) presented older Black Americans and older White Americans (without dementia) with a susceptibility to scam questionnaire. White participants exhibited higher susceptibility to scams compared with their Black counterparts. Other experimental studies (Nolte, Hanoch, Wood, & Hengerer, 2021; Wood et al., 2018), however, failed to report any association between ethnicity and susceptibility to scams. This lack of relationship could stem from the low participation rate of non-White participants. Data from the Crime Survey for England and Wales (Office for National Statistics, 2022) also failed to identify ethnicity as a risk factor.
To date, the link between ethnicity and susceptibility to fraud is the least researched topic among the main demographic factors (age, education, and income), both in national and international surveys as well as in experimental studies. Moreover, unlike age, education, and income, which can be compared internationally, ethnicity is a far more difficult construct to compare across nations because of how it is defined, the methods used to collect data, and the very nature of ethnicity. To complicate matters even further, the status, size, and SES of a specific ethnicity can vary drastically across nations. That being said, it is crucial to untangle the relationship between ethnicity and fraud vulnerability, although the generalizability of such results might be confined to certain loci.
Taken together, the relationship between scam susceptibility and demographic factors turns out to be complex and dependent on a range of variables, such as the type of scam, whether the study measures susceptibility versus actual experiences of victimization, and whether one uses surveys, conducts experiments, or relies on secondary data (e.g., victimization records from the police). Moreover, scams and scammers do not remain static: Scams evolve continuously, and scam trends change constantly. That is not to say that age, income, education, gender, and ethnicity might not serve as risk factors. Each demographic variable might place individuals at risk, but the risk might differ on the basis of the context, type of scam, and rate of targeting and exposure. Older adults might be at greater risk of phone scams and health-related scams. Younger adults might be at greater risk of scams presented via SNSs (especially via TikTok and Instagram) and scams that are related to sextortion or employment opportunities. Middle-aged individuals might be more prone to receiving fraudulent solicitations via the internet, such as those that focus on investment. Thus, although we believe that demographic variables are important to study, they might also serve to give certain demographic groups (higher income and education) a false sense of security or overconfidence that they could identify and manage fraudulent solicitations. Scammers do their homework to tailor scams to specific demographic groups and further customize the message to the individual. That is, they research the person whom they are contacting and possess vital information about them (age, gender, ethnicity, and various personal identifiers). In the case of Cowles, they knew the last four digits of her social security number and that she had a 2-year-old son. Last, there is a real paucity of studies evaluating how mental health, dementia, and learning disability might impact susceptibility to fraud. These vulnerable populations might be at greater risk, although at present we do not have enough data to support or negate this possibility.
Susceptibility to scams and individual differences
Harvesting information about one’s age, gender, job (as a proxy for income), and marital status can be achieved rather easily via SNSs. Tidy (2021) revealed how one hacker, Tom Liner, sold a database containing information on 700 million LinkedIn users from across the globe for $5,000. More sensitive data can be obtained by hacking or purchasing from more secure databases. Scammers often utilize this information during the interaction to appear more legitimate. At present, however, scammers have a much harder time telling whether their target is a risk-taker/risk-averse, impulsive, or possesses internet knowledge or what their level of analytical reasoning and financial literacy might be. Moreover, there is inconsistent and patchy literature regarding the link between measures of individual differences and scam susceptibility. For example, only a few studies have investigated whether analytical reasoning—as measured by the Cognitive Reflection Test (CRT)—can serve as a protective factor against fraud (cf. Anderson, 2016; Jones et al., 2019; Kelley et al., 2023), despite substantial research linking analytical reasoning to detecting misinformation (e.g., R. M. Ross et al., 2021). Thus, it is difficult to generalize whether analytical reasoning is a protective measure across cohorts (e.g., young adults), cultures, and types of scams (e.g., investment vs. government imposter).
One measure that has attracted much attention is financial literacy. There is a large corpus of data and research showing that higher financial literacy is associated with better financial decisions, such as paying credit card bills on time and planning for retirement (Lusardi & Mitchell, 2011, 2014). If financial literacy aids in making better financial decisions, it may be reasoned that it should also help in detecting fraudulent solicitations. Looking at data from the China Household Finance Survey, Wei et al. (2021) found that financial literacy was positively related to fraud detection. The authors, however, did not report whether financial literacy was also associated with encountering fraud and, more importantly, suffering from fraud. Drawing on data from the Rush Memory and Aging Project, Gamble et al. (2013) reported that a reduction in cognitive ability was also linked to a reduction in financial literacy and that individuals were not aware of this reduction. Interestingly, their data also showed that overconfidence in one’s financial literacy was a significant factor in scam susceptibility. Experimental studies by Anderson (2016) and Roth (2024) revealed similar patterns, in which better literacy was negatively correlated with intention to respond to fraudulent offers.
Not all researchers report similar trends. Du and Chen (2023) analyzed the same data used in the study by Wei et al. (2021). In their study, rather than focusing on fraud detection, they evaluated fraud victimization. Unlike Wei et al., Du and Chen demonstrated a U-shaped relationship between financial literacy and fraud victimization. Others have reported either opposite findings or no relationship. Wood et al. (2018) failed to find a relationship between numeracy and intention to respond to a fraudulent sweepstakes solicitation. Likewise, Rey-Ares et al. (2024) analyzed data from more than 6,000 Spanish individuals and reported contradictory results to those discussed above. Individuals with higher financial literacy were exposed to more consumer financial fraud solicitations, but financial literacy offered no protection against victimization. McAlvanah et al. (2015) also reported that more numerate participants rated implausible ads as more credible. A study with more than 4,500 financial investors (Lokanan & Liu, 2021) showed that investors with lower financial literacy had lower chances of being fraud victims. Fan and Yu (2022), drawing on the China Household Finance Survey, found that higher financial literacy was a predictor of a higher rate of fraud victimization. Others (Aristei & Gallo, 2021; DeLiema et al., 2020; Drew & Cross, 2013), however, failed to find a relationship between the two constructs.
Why would financial literacy (like education) not offer the same protection against fraud as it does against other financial decisions? One possibility, identified by several authors (Aristei & Gallo, 2021; Drew & Cross, 2013), is that higher financial literacy might give individuals a false sense of confidence and security regarding their ability to identify fraudulent solicitations, especially financial ones. Thus, they will also be less guarded against fraudulent offers and may pay less attention to potential red flags. Fraudsters, moreover, use specific tactics—such as fear and time pressure—that deliberately aim at reducing individuals’ capacity to use their cognitive faculties and knowledge. Third, fraudsters are adept at creating a false sense of financial security, telling targets that they are avoiding financial loss by moving money into a “safe account” that no one else can access, that an investment has guaranteed returns, or that sending money will protect a loved one from serious harm. An individual’s numeracy and knowledge of basic financial concepts may therefore offer little protection when faced with choices that are divorced from traditional financial risk/reward contexts. In scam situations, persuasion knowledge and familiarity with how scammers exploit technology may be more predictive of victimization.
Because fraudsters often use time pressure, it is conceivable that impulsive individuals might be at greater risk of responding to these solicitations. Work by Anderson (2016) lends support to this intuition. The author found that measures of impulsiveness predict intention to respond to fraudulent solicitations (but see McAlvanah et al., 2015). An examination of two types of fraud (cyber and romance) found similar results, showing that impulsiveness served as a risk factor for fraud victimization (Whitty, 2019a, 2019b). A study by Modic and Lea (2013) evaluated susceptibility to persuasion. The authors reported that self-control was a predictor of both past and future compliance with scam solicitations. An analysis of a secondary data set of more than 11,000 internet users revealed a similar picture: Self-control served as a key predictor of being a scam victim (H. Chen et al., 2017). A survey of more than 6,000 individuals from the Netherlands (van Wilsem, 2013) exposed a positive link between self-control and fraud susceptibility. Focusing on older adults and online shopping, Reisig and Holtfreter (2013) also identified self-control as a risk factor for fraud victimization. Last, using the CRT as a proxy for self-control, Kelley et al. (2023) showed that higher scores on the CRT are associated with better discrimination of fraudulent websites.
Scammers often inject time pressure or urgency into their pitch. This is not surprising, because self-control or impulsiveness seems to be a clear factor in susceptibility to scams. Self-control or impulsiveness has been similarly linked to a host of deleterious financial behaviors, such as reduced saving (Strömbäck et al., 2017). It is little wonder that one of the most common pieces of advice given is not to respond immediately and to think carefully about the nature of the solicitation. For example, a major national antifraud campaign in the United Kingdom called Stop! Think Fraud instructs people to take a moment to stop, think, and check whenever approached.
Like impulsiveness, risk-taking tendencies have been identified as possible culprits. The link between risk-taking and susceptibility to fraud might not be surprising because a large corpus of work has shown an association between risk-taking and a wide range of behaviors, such as economic (Schoemaker, 1993), medical (Reyna et al., 2009), and driving (Iversen, 2004). Moreover, because many scam solicitations are financial by nature (e.g., investment scams), it is important to evaluate the link to individuals’ risk-taking profile (Hunt, 2016).
Building on the above logic, Anderson (2016) found a positive relationship between risk-taking and intention to purchase a fraudulent product. Yet the data from this experiment showed no relationship between risk-taking and rating fraudulent ads as more credible. Earlier surveys by the FTC found that individuals who were identified as higher risk-takers were more likely to report being victims of fraud (Anderson, 2013). Others (Whitty, 2019a) reported that sensation-seeking scores (as a proxy for risk-taking) were associated with increased probability of being a fraud victim. Examining the 2017 FTC data, Anderson (2019) found that those reporting a high willingness to take risks were significantly more likely to report being a victim of some kind of fraud.
McAlvanah et al. (2015), using a somewhat similar approach to Anderson (2013), reported no relationship between risk-taking and fraud victimization. Focusing on older adults, Yu et al.’s (2023) data revealed no association between risk-taking and intention to respond to fraudulent solicitation. A systematic review of the literature (Dadà et al., 2025) also failed to find risk-taking as a predictive factor. Two experimental studies (Mueller et al., 2020; Wood et al., 2018), including both investment scams and lottery scams, also showed similar results. Interesting findings, however, did emerge from the studies by Mueller et al. (2020) and Wood et al. (2018). In these two separate investigations, the researchers demonstrated that risk perception—that is, participants’ perception of the benefits and the risks associated with the fraudulent offers—was the main predictor of participants’ intention to respond to the fraudulent solicitations. Participants who perceived the offers as more beneficial and those who perceived them as less risky were more likely to indicate intention to respond to them.
Unfortunately, very few studies on fraud victimization have included measures of risk-taking proclivities in their investigation. Despite the possible connection between risk-taking (after all, responding to these offers is risky) and scam victimhood, there are limited data on whether risk-taking is a predictive factor. Moreover, there are even less data on whether risk perception is a major driving force. Mueller et al. (2020) and Wood et al. (2018) provided strong indications that perceptions of benefits and risk are a major driving force, findings that match those found in many other risk domains (e.g., Hanoch et al., 2006).
Aside from the above factors, researchers have included other measures, although less systematically. Anderson (2013) and McAlvanah et al. (2015) demonstrated that general skepticism might serve as a protective factor; others have explored the role of living in different regions and in rural versus urban environments (Cross, 2020; Wang et al., 2025). Cognitive ability has also emerged as a possible predictor. Indeed, current research (Lambert et al., 2025), for example, has suggested that cognitive impairment is linked to vulnerability to exploitation. Mueller et al. (2020) included the adult Decision-Making Competency Scale (Bruine de Bruin et al., 2007) as a proxy for cognitive ability but did not find any relation to fraud susceptibility. Jones et al. (2019), using a different battery of cognitive tests, found largely similar results. Research with only older adults, however, does show a link between cognitive ability and scam susceptibility, discussed in detail later (Judges et al., 2017).
No doubt, understanding whether a certain characteristic (whether demographic or individual differences) serves as a risk factor is an important endeavor because it is in many other domains (e.g., health behaviors; for a summary of the research discussed above, see Table 1). Gaining insight might offer researchers, law enforcement agencies, and other organizations the ability to tailor messages and preventive measures to specific populations and scams. Yet there is also a danger in such a pursuit. Identifying certain risk factors might provide false assurances to those who do not fit the specific category. For example, arguing that males (or females) are at a higher risk might give false assurance to the other gender. We believe this is fundamentally wrong on two levels. First, fraudsters are not “fussy.” They target everyone and anyone without discrimination; nor do they “care” if a victim is a male or female, lives in a city or a village, is an atheist or religious, or went to university or did not finish high school. Indeed, data regarding the age of victims have changed in the past 20 years or so, with ever more young adults falling victim to scams. Second, methodological issues might also help explain the diverse results. Some studies rely on secondary data sets, whereas others are survey-based or experimental. Studies also use different measures (for impulsivity and risk-taking) and different conceptualizations of the dependent variable (scam susceptibility, scam victimization) and focus on different types of scams. Focusing on crypto fraud might provide a different profile and risk factors compared with job fraud or romance fraud (DeLiema, Li, & Mottola, 2023). There are also concerns regarding self-reporting victimhood in both research studies and to law enforcement agencies. Estimates suggest that most individuals do not report falling prey to scams. It is difficult to know, therefore, how accurate surveys and national data collections are. Stop! Think Fraud captures our sentiment perfectly: No one is immune to fraud. And as Yang et al. (2025) argued, financial exploration, such as fraud, is “dependent upon a combination of psychosocial, sociodemographic and health factors” (para. 1).
Summary of Empirical Evidence on Fraud, Deception, and Scam Research.
Note: BBB = Better Business Bureau; FTC = Federal Trade Commission; UAS = Understanding America Study; IACOFI = Italian Literacy and Financial Competence Survey; N/A = not applicable; CHFS = China Household Finance Survey; IIROC = Investment Industry Regulatory Organization of Canada; CSEW = Crime Survey for England and Wales; TCSEW = Telephone-Operated Crime Survey for England and Wales; IC3 = Internet Crime Complaint Center.
The Tools of the Trade: Mechanisms Scammers Use to Deceive Us
Daniel, a 46-year-old dentist, was driving around his hometown while visiting his mother when he received a call on his cell phone. The number and the caller ID said that it was the local police. Fearing that something may have happened to his mother, Daniel answered. The caller informed him that he had missed jury duty and the police were on their way to arrest him. He could avoid being arrested if he covered the court fine immediately, payable with $400 in Apple gift cards.
Daniel panicked. A month earlier, he had received jury summons at his dental clinic but set the letter aside because he needed to rush to his next patient. He had forgotten to respond. Fearing arrest and the impact on his reputation, Daniel drove to the nearest retailer and purchased Apple gift cards, or “government-approved vouchers” as the officer on the phone referred to them. He read the codes on the back of the cards and was told that more payment was needed before the charges could be dropped. Still terrified, Daniel went back into the store and waited in line to purchase another $400 in gift cards. This time, the salesclerk pulled Daniel aside and told him to hang up the phone, saying that he may be the victim of a scam.
Action Fraud, the United Kingdom’s leading national fraud and cybercrime reporting center, provides a long list of the types of fraud people encounter. The list includes well over 100 different scams and in all likelihood is far from exhaustive. Indeed, new types of scams are introduced regularly, and their sophistication is growing rapidly. Scams differ in many ways, including the techniques scammers use. To lure individuals, scammers have relied on and exploited a wide range of social engineering, persuasion techniques, and psychological vulnerabilities. Among these mechanisms, techniques, and vulnerabilities are affinity or personal connection, loss aversion, self-control, sense of scarcity, strong emotions (both negative and positive), sunk cost, time pressure, and trust in authorities. Scammers thus tend to exploit both vulnerabilities and biases that are inherent to human psychology, as well as engineering environments and conditions, to further reduce our capacity to resist their solicitations.
Theoretical models: how we process scam messages
In trying to understand how scammers devise persuasive messages and why people respond to their solicitations, several models have been proposed. Among these models, one can find the elaboration likelihood model (ELM; Petty & Cacioppo, 1986), the visceral influence on persuasion (Langenderfer & Shimp, 2001), and the scammers’ persuasive techniques model (Whitty, 2013). Although these models differ in several important ways, they do share one important and common theme. They all posit that scammers’ messages are intended to fuel strong emotions or visceral reactions and to reduce in-depth processing, attention to details, and reliance on rational faculties in assessing the messages. It is through this process that scammers motivate rushed decisions and increase errors in judgment and decision-making.
One of the most influential models in the field has been the ELM. The model was developed by Petty and Cacioppo (1986) as a dual-process theory of attitude change. Similar to System 1 and System 2 information processing (Kahneman, 2011), the ELM proposes that individuals process persuasive communication through either a central route (System 2)—careful and thoughtful consideration of the arguments presented—or a peripheral route (System 1)—reliance on heuristics and simple cues to make a judgment (Petty & Cacioppo, 1986). In line with several other models (e.g., Ebner et al., 2023; Langenderfer & Shimp, 2001; Norris & Brookes, 2021), the ELM proposes that both individual and situational factors influence the extent to which a person processes information through the central route and elaborates on (i.e., “thinks about”) issue-relevant information in a persuasion message. When a person is distracted, facing time pressure, or in a state of high emotional arousal—like Daniel in the car—they elaborate less on the quality of the arguments in the message and instead process the information superficially. Their attitudes and decision-making are influenced by peripheral cues—signs of authority, attractiveness of the offer, how they are feeling, the credibility of the source, and so on.
Scammers purposely create persuasion contexts (or social-engineer the decision environment) that make it difficult for targets to scrutinize information through central-route processing. They may impersonate authoritative or credible organizations (e.g., the police, software providers), use fear arousal (threats, intimidation) or phantom fixation (dangling the promise of financial rewards or romantic connection), and demand that the target act quickly to receive a reward or avoid punishment. These tactics place targets in states of high emotional arousal, causing more peripheral-route processing (Kircanski et al., 2018; Norris & Brookes, 2021). When Daniel was targeted by the police impostor while driving, not only did the premise feel plausible—he actually had missed jury duty—the scammer’s authority as a police officer and the threats of immediate arrest made him fearful. Daniel did not pause to rationally consider that being arrested for missing jury duty and paying a court fine with Apple gift cards were unreasonable. As a law-abiding citizen accustomed to complying with law enforcement, Daniel did as he was told until he was interrupted by someone who recognized the red flags.
Dual-process models such as the ELM are often cited in the literature on susceptibility to mis- and disinformation (i.e., “fake news”). Compared with legitimate news stories, fake news stories contain more emotional appeals, celebrities, and repetition—tactics that promote heuristic information processing (Whitty & Ruddy, 2025). Other peripheral cues, such as the perceived credibility of a source and verification checks, are associated with belief in fake news (C.-Y. Chen et al., 2021; Vu & Chen, 2024). To date, the literature on scam susceptibility has focused mainly on demographic and dispositional factors, but more attention to these contextual and affective factors is needed (Norris & Brookes, 2021). Indeed, surveys rarely measure the impact of stress or high arousal states on susceptibility to fraud, with only a handful of studies manipulating emotional arousal directly (Kircanski et al., 2018).
Even incidental emotions and cognitive states can bias attention and limit the depth of information processing (Forgas, 2017). In a qualitative study by DeLiema, Volker, and Worley (2023), victims of gift-card payment scams described receiving scam solicitations when they were busy at work, waking up in the morning, experiencing financial strain, rushing to an appointment, or under the influence of drugs. Although these incidental emotions and cognitive states are not induced by scam messages directly, they add cognitive load and impair a target’s ability to scrutinize information, thereby biasing judgment.
Scammers often deliver their solicitations when intended targets are most vulnerable. Many scams capitalize on historical events such as humanitarian crises, natural disasters, and even policy changes. Fraudsters may pretend to offer disaster-relief funds to hurricane victims, peddle fake home-repair services after a flood, or claim to be a charitable organization providing humanitarian relief to refugees (Cross, 2025; Davila et al., 2005). These scams are effective because they leverage social disorganization and collective trauma (Davila et al., 2005) and take advantage of the human desire to be helpful in the face of suffering.
Sweepstakes scams
The ELM provides a useful lens to understand how scammers manipulate information to increase compliance. It does not, however, capture the entire spectrum of techniques scammers use (see Table 2). For example, there have been laboratory studies in the area of phishing (Oliveira et al., 2017), sweepstakes scams (Wood et al., 2018), and investment pitches (Mueller et al., 2020). Others have adopted field-type experiments to better assess real-world behavior. Regardless of the research methodology used, compliance with scam requests has been higher than one might expect, ranging around 15% to 25% (Fischer et al., 2013; Wood et al., 2023; Yu et al., 2023). That being said, it should be noted that only a limited number of studies have systematically evaluated factors related to scam compliance.
Common Scam Techniques.
Note: FBI = Federal Bureau of Investigation.
Sweepstakes scams were named the fourth most common scam in 2023 by the FTC (FTC, 2024a). Sweepstakes scams attract victims for several reasons. First, there are many legitimate sweepstakes, and about 55 million Americans participate in sweepstakes each year (Clairborne & Milberger, 2008). Fraudsters draw on their popularity to mimic official-looking ones (both letters and emails). Because distinguishing between real and fake is not always trivial, scammers can get individuals to engage with them in what consumers judge to be a low-risk scenario. Later, consumers are asked to pay some type of advance fee, shipping, and/or tax to receive the prize. Victims then feel bound to continue sending money to scammers because they have already invested money, time, and effort. In addition to sunk cost, scammers also induce a sense of loss aversion, which tends to lead to higher risk behavior and an increased emotional reaction to the possibilities of loss.
Impostor scams remain highly effective, and some researchers have examined the role that authority or impersonating authority may play in compliance. For example, in 2023, the FTC reported a spike in sweepstakes scams impersonating Publishers Clearing House (Lazarus, 2023). In lab and field experiments, Wood et al. (2018) and Fischer et al. (2013) did not find an effect of authority in lottery-scam-type studies. However, these studies impersonated companies such as Target. Real-world data revealed that government imposter scams that imitate agencies such as the Internal Revenue Service (IRS), Medicare, and the Social Security Administration, as well as business imposter scams that impersonate companies and financial institutions (FTC, n.d.), were among the most common and successful scams. Yu et al. (2023) conducted a field study in which they contacted 644 older participants, telling them there had been a breach in fictitious government agency accounts and asking them for personal information. In this field study, 15% of participants engaged but did not comply, whereas 16.4% engaged and did comply, providing their private information. Researchers moving forward should consider all three subgroups of potential victims: those that do not engage at all, those that engage but do not comply, and those that engage and comply. In summary, it is typical for sweepstakes scams to impersonate some type of authority, and the evidence from both field and lab studies indicates certain impersonations are more successful than others.
In a series of experiments, Wood et al. (2018) reviewed sweepstakes scam material provided by the U.S. Postal Inspection Service to identify elements of persuasion used in these letters and individual difference factors related to compliance. Factors such as elements of scarcity and authority were manipulated experimentally, and 48.8% of participants reported some willingness to contact for more information. The best predictor of intention to contact the number on the sweepstakes was the in-the-moment subjective ratings of risks versus benefits of the sweepstakes. In one experiment, an activation fee of $0, $5, or $100 was added to determine whether that would impact participation, with about 25% of participants reporting some willingness to contact the number. At the same time, as the activation fee increased, the rate of willingness to participate decreased. The study indicated that, in the moment, lower perceived risk, higher perceived benefits, and lower education levels were the strongest predictors of willingness to contact the sweepstakes’ number.
In a separate study, Klapatch et al. (2023) used natural language models to analyze a batch of scam letters provided by the U.S. Postal Inspection Service. From this batch, the authors found four clusters of letters: negative/cold, one-reward letters (one prize, above-average amount of negative emotion, low in color); high-emotionality, high-scarcity letters, in which a prize is mentioned often (highest emotion, reward mentioned often, scarcity highlighted); very colorful multiprize letters (sweepstakes, many rewards mentioned, colorful, emotionally neutral); and low-emotionality, low-scarcity, cold letters (assumed to be more businesslike and contain more authority). Overall, despite identifying four types of letters, the authors found that compliance with instructions was not significantly different across the letter types and that perceived benefits and risks drove compliance. In this project, younger consumers showed increased interest and compliance rates.
Wood et al. (2023) completed a project using a mixed-methods design to better understand consumer decision-making. In this project, participant age and letter condition (hot vs. cold) had no effect, similar to Klapatch et al. (2023), but lower education and higher susceptibility to superficially profound but meaningless statements predicted a higher likelihood to indicate intention to respond to the sweepstakes scam. Lower risk assessment and higher benefit assessment were also significant predictors of intention to comply.
Qualitatively, participants identified risks such as identity theft, being forced to make a purchase or lose money, and concerns about excessive junk mail, as exemplified in the following quote: “I feel it would open my personal information up for sale to other phishing companies. I could have a breach [sic] of personal data at worst, or at least have my info sold to several companies wanting to sell me stuff.” Benefit themes included the belief that the offer was legitimate and the prospect of winning money: “Perhaps a company is telling you the truth and you do actually win this money.”
In a follow-up study that included an activation fee, lower risk assessments and higher benefit assessments were significant predictors of intention to comply. Thematic elements were also reviewed in the study. New themes that emerged included the detection of logical inconsistencies in the letters, such as “I don’t see why Costco, Target, Walmart, and Clearing House would all be involved in this when three of the four are competitors.” A new important theme was revealed, that is, the belief in the self-efficacy of the individual to control the outcome of an interaction with the sender of the offer. For example, “I think it [the risk] is low because they don’t have any information unless you give it to them. If you call and the letter isn’t real, it’s just a waste of time and that’s all.” This comment exemplifies the overconfidence consumers have when engaging with potential scammers, underestimating the scammers’ skills and tactics.
In summary, these projects indicate that consumers engage and participate with scam solicitation materials at high rates. Consumers display a competence/confidence gap and overestimate their ability to engage superficially to seek additional cues/red flags/green flags without losing money. Now, with the use of AI, there are fewer cues, such as spelling mistakes, and materials will be increasingly tailored to each consumer’s needs and desires. This research is consistent with DeLiema, Volker, and Worley’s (2023) work showing that in-the-moment, current mental status, instead of persistent individual differences, drives compliance with many scams.
Other tactics used by scammers
Sweepstakes scams are but one type of scam that individuals encounter. There are, as we indicated before, a wide range of scams and a wide range of tactics. Below, we consider several common scams and their psychological tactics before describing the impact on fraud victims, including research from affinity fraud, Ponzi schemes, and romance scams (see Table 2).
Fraud victims are often targeted by perpetrators through affiliations, such as church groups or other clubs, or through interactions with trusted financial institutions. Dearden et al. (2025) defined affinity fraud as scams perpetrated through groups with shared status, which can be small (e.g., investment club) or quite large (e.g., ethnic identity), and reported that potential investors weigh religious affiliation above educational credentials when choosing between hypothetical investment choices. A common affinity group is a religious organization, in which characteristics of the community make it easier for perpetrators to develop trusting relationships, leverage existing relationships between members, seek forgiveness, and discourage reporting (Dearden et al., 2025). Affinity scams in this context result in complicated emotional outcomes, including anger and betrayal, which may be quite distinct from those of other crime victims. Interestingly, Dearden and colleagues did not note that the social group itself dissolves following the scam. However, other affinity scams may result in changes to group and family dynamics and decreased social support.
Ponzi-scheme victimization is especially devastating because there are few red flags for victims who often see, at least on paper, promising investment returns. A recent take on Ponzi schemes is the notorious crypto-romance scam, also known as Sha Zhu Pan, or “pig butchering.” Pig butchering is the derogatory term criminals use to describe the process of stringing victims along, fattening up their digital wallets, and then ghosting, or stopping, all contact with the victims after months of an intimate friendship/relationship. These scams typically take place over many months, with hundreds of text messages relayed before any serious ask.
Victims invest slowly at first and can see their investment grow on an app that is programmed by the scammers to display strong gains. In fact, their money was never invested at all. It was merely transferred to a digital wallet controlled by the scammers. If the victims try to remove funds prematurely, there is a fee or other obstacle, making the transaction close to impossible. Once the victims have no more funds to invest, perpetrators will just disappear along with the account (Federal Deposit Insurance Corporation Office of Inspector General, n.d.).
Crypto romance is a recent scam (starting around 2022), and only limited research on the psychological tactics used to attract, groom, and scam victims exists. A study by Oak and Shafiq (2025) presented preliminary work from in-depth Zoom interviews with 26 victims (mean age = 48 years; range = 27–68 years). On the basis of these interviews, the authors described a complex process that walks through multiple stages that unfold over months. The stages described in crypto-romance fraud (although they can apply to other scams as well) include the lure, bond, bait, feed, squeeze, cut, and encore (see Oak & Shafiq, 2025). Initially, victims are lured either by cold texts, dating apps, job boards, or other social media. Next, scammers will deepen the relationship and then describe a cryptocurrency investment opportunity, often tailored to the individual’s financial needs. In the next stage, the feed, scammers will actively elicit contributions from their targets, leading to the squeeze, in which pressure tactics are used to maximize investments. The end stage is the cut, in which victims are tapped out and try to extract their investment but hit obstacles. Many victims report even speaking with helpful “customer support representatives” who may try to extract even more money by requiring advanced payment of capital gains taxes and so on. Once the victim realizes that it was all a scam, the scammers cut all communication and block all contact. For some unfortunate victims, there is an encore, in which scammers impersonate law enforcement officials to reestablish contact with the victims. They claim the victim was involved in a cybercrime and pretend that they are there to help recover assets but first need the victim’s account information to retrieve their funds. Other victims are threatened with owing taxes or being involved in an illegal scheme themselves.
Traditional romance scams share many characteristics with the long-con crypto-romance investment scams. Whitty (2015) described five stages of the typical romance scam that involve crafting a dating profile, grooming the victim through increased contact and sharing of personal information, requesting a small amount of money to resolve a “crisis,” a series of other crises with larger and larger fund requests, and, finally, revelation. The author noted that the potential for sextortion and involvement in money laundering can prolong the process and worsen the psychological outcome for victims.
Not all scams lure victims through the promise of positive rewards such as wealth and romance. Ruchika Tandon, a 44-year-old neurologist at one of India’s top hospitals, was ensnared in what felt like a high-stakes federal crime investigation. Under the pretense of arrest, Dr. Tandon was coerced into taking leave from work, surrendering her daily freedoms, and complying with nonstop surveillance and instructions from strangers on the phone who convinced her she was at the center of a grave investigation. Eventually, she transferred about $300,000 from bank accounts, mutual funds, pensions, and life-insurance plans (Biswas, 2024).
Dr. Tandon’s story showcases a relatively new type of fraud known as a digital arrest scam (Vijay, 2025). It has been reported in India and in the United States that scammers target specific professional groups, including PhD-level psychologists (Said, 2021) and physicians (Robeznieks, 2025; Wood, 2025). These scams are a type of impostor scam in which the perpetrators assume false identities such as law enforcement or government agencies and coerce victims into compliance. In this scam, victims receive a phone call from someone impersonating law enforcement and falsely accusing the victim of committing a crime. The scammers then ask for cash in lieu of bail to avoid arrest/solve the problem, and often scammers use FaceTime or other video conferencing to “monitor” the victim throughout the harrowing exchanges, sometimes demanding personal information or client information. These scams work by generating an immediate, intense emotional state that creates fear in the context of some intimidating authority figure. In this scam, the presence of authority/law enforcement, situational factors, and fear of dire consequences increase compliance. More research on the psychological tactics and stages of specific scam typologies is needed.
The Neuropsychology and Neuroscience of Scams
Joan Klunder’s story was featured on CNN (CNN, 2024). She was eventually diagnosed with Alzheimer’s disease; however, she started showing signs of poor financial decision-making years earlier. According to her son, scammers stole nearly $100,000. Before showing signs of poor financial decision-making, she worked with top executives and even U.S. presidents. In older age, she eventually started making “strange payments” according to her son. For example, she unnecessarily replaced windows and a refrigerator in her house. When her son decided to have her move in with him, she bought cruise tickets to Europe instead. On one occasion, she went missing overnight, bought a blanket at a drugstore, and slept in her car. This behavior was described by her son as “that’s just not her.”
An emerging line of neuroscientific work has focused on how financial decision-making, a correlate of financial vulnerability and scam susceptibility, may vary across age considerations (e.g., Samanez-Larkin & Knutson, 2015). However, to date, most published work has focused on older participants given clinical disease considerations and relevance to elder abuse. There is a broadly held assumption that greater susceptibility to scams in older age is primarily attributable to cognitive decline or cognitive impairment because of declining brain structure and consequent functional ability. Older adults with mild cognitive impairment (MCI), a condition marked by objective cognitive impairment but without a significant impact on the ability to live independently, show greater financial vulnerability (Fenton et al., 2023; Han et al., 2015a, 2015b). This has now been shown in multiple varying sized cohorts across different settings and measures of decision-making. Sensitivity studies within the field of neuropsychology have pointed to specific cognitive functions that may be associated with financial vulnerability. These include measures of episodic memory, processing speed, and various executive functioning abilities (Han et al., 2015a, 2015b; Lim et al., 2025).
Executive functioning abilities are frequently identified as important for financial decision-making. The ability to hold multiple pieces of information within working memory and inhibit prepotent impulses would be important for optimal decision-making. Episodic memory is important because the identification of potential scam scenarios often relies on remembering characteristics of a scam or trustworthy persons. Processing speed abilities are arguably the most directly linked to aging (Salthouse, 1996, 2000), with declines reliably predicted on the basis of increasing age. It is not a coincidence that many scam scenarios rely on time pressure to force targets to make decisions that consider many different pieces of information within a short time frame.
Although several studies have related various specific and global cognitive impairments to financial vulnerability (Fenton et al., 2023; Han et al., 2015a, 2015b), there has been less work focused on associations between longitudinal declines in cognitive functioning and vulnerability. One notable exception is the work from the Rush Memory and Aging Project. In one investigation, a group of more than 420 older adults without dementia in the Chicago metropolitan area was studied. Results showed that a more rapid cognitive decline was associated with greater susceptibility to scams and poorer decision-making across 5.5 years (Boyle et al., 2012). Another way to study the association of cognitive decline in older age with financial vulnerability is to focus on incident dementia. In a group of 935 older people, lower scam awareness was associated with a higher incidence of Alzheimer’s disease in longitudinal data spanning over 6 years (Boyle et al., 2019). A similar finding was observed with credit scores and Medicare data among more than 80,000 individuals. In those eventually diagnosed with dementia, missed payments on credit accounts and subprime credit scores preceded dementia diagnosis by about 6 years (Nicholas et al., 2021). Overall, these studies suggest not only that cognitive impairment is associated with greater vulnerability but also that the process of cognitive decline is associated with greater vulnerability in older age.
Some important questions remain regarding the association of cognitive impairment and cognitive decline with financial vulnerability. Although episodic memory, processing speed, and executive functioning seem important, it is unclear to what degree each of these is necessary to deem an older person vulnerable. Similarly, we do not know to what extent these abilities need to decline to deem an older person vulnerable. Importantly, although cognitive impairment and decline may make an individual more vulnerable, vulnerability may be independent of cognitive ability as measured by neuropsychological tools. In more than 600 older adults without dementia, 24% of individuals had a significant discrepancy between their decision-making ability and their cognitive ability (Han, Boyle, James, et al., 2016). This suggests some older adults may be cognitively intact yet show poor financial decision-making. We also observed the opposite to be true in the same study. Some of these discrepant older adults showed better decision-making ability relative to their cognitive ability. The findings overall highlight that although cognitive ability and decision-making ability may be closely aligned, this is not always the case in a sizeable portion of older adults. Moreover, much of this work has focused on older adults, and the link between cognitive ability and scam susceptibility has received far less attention in other age groups.
The reasons for discrepancies between decision-making ability and cognitive ability may be varied. What is considered “cognition” is a battery of historically established measures of specific cognitive abilities. These specific abilities (e.g., episodic memory, working memory, processing speed, visuospatial ability, language) have a history in cognitive psychology with well-defined brain mechanistic anatomical correlates and reliable methods of measurement. Decision-making does not currently have a standardized, reliable method of measurement, and the brain-system correlates of decision-making are often overlooked by historical cognitive measures. For example, many commonly utilized cognitive measures do not adequately capture the functions of the ventromedial prefrontal cortex (Damasio, 1996).
A notable fact is that cognitive decline in aging is due to the age-associated neuropathological impact on brain systems (Wilson et al., 2020), and this neuropathological accumulation may build over years before affecting cognitive function (Beason-Held et al., 2013). For this reason, neuroimaging has been a useful tool in examining brain characteristics that may show the effects of neuropathology even ahead of any noticeable cognitive impairment. Susceptibility to scams has been inversely associated with gray-matter density in the hippocampus, a brain region important in the pathogenesis of Alzheimer’s and vulnerable to age-associated neuropathology (Han, Boyle, Yu, et al., 2016). In an event-related functional MRI paradigm, younger and older participants showed different patterns of brain activity to the anticipation of monetary gains and losses, suggesting older adults may not be as sensitive to losses (Samanez-Larkin et al., 2007). Financially exploited older adults, compared with those who had not been exploited, showed cortical thinning of the insula and superior temporal regions and less functional connectivity in the default and salience networks (Spreng et al., 2017). Cortical thinning of the entorhinal cortex, commonly known as the first brain region to deteriorate in Alzheimer’s, was associated with financial exploitation vulnerability (Fenton et al., 2024). White-matter microstructure was associated inversely with measures of decision-making and scam vulnerability (Han, Boyle, Arfanakis, et al., 2016; Lamar et al., 2020). Multiple studies have also showed functional connectivity differences associated with measures of financial vulnerability in older age (Han et al., 2012, 2013, 2014; Weissberger et al., 2020). For example, using an insula-seed region of interest, Han et al. (2013) found that older adults who showed less impulsivity in a temporal discounting paradigm had greater functional connectivity of the medial temporal lobe and less functional connectivity of the ventromedial prefrontal cortex. In addition, greater functional connectivity between the anterior and posterior cingulate was associated with greater financial literacy, a factor that conveys protection against vulnerability (Han et al., 2014). In a separate sample, Weissberger et al. (2020) again found the medial temporal lobe, ventromedial prefrontal cortex, and posterior cingulate functionally correlated with a measure of financial vulnerability in older adults.
Much of the work involving the neuroimaging of financial vulnerability in older age has been informed by decision-making, behavioral economics, and neuroeconomics studies, often involving neuroimaging in younger samples. An exhaustive review of this important literature is beyond the scope of this article (for an example, however, see Dennison et al., 2022), although some findings are relevant to understanding scams and fraud in older adults. It is from this literature in younger samples that we understand reward and reward-based processing involves dopaminergic systems in the medial prefrontal cortex, striatum, and amygdala (O’Doherty, 2004), and many of these same systems are implicated in social hedonics and preferences (Fehr & Camerer, 2007). This important line of investigation, for example, has provided us with crucial insights regarding the role of the prefrontal, parietal, and insula cortices in decisions under uncertainty (Huettel et al., 2005). We also know from this literature that the integrity of the hippocampus and medial temporal cortex structures is critical for optimal decision-making (Delgado & Dickerson, 2012; Peters & Büchel, 2011).
Altogether, leveraging neuroimaging to investigate susceptibility to scams and financial vulnerability in older age has yielded many important insights. In general, stronger brain characteristics (e.g., microstructure, cortical thickness, structural and functional connectivity) in older age are associated with better decision-making. It is important to note that these findings are often above and beyond demographic factors and cognitive ability. This points to the importance of maintaining or improving brain health in older age as a protective measure against financial vulnerability to scams and fraud. When considering specific brain regions, the medial temporal, medial frontal, and entorhinal cortex and insula appear significant. The medial temporal lobe networks support episodic memory and prospective memory, or the ability to project into the future certain outcomes on the basis of previous experience (Dermody et al., 2016). The medial frontal lobe networks are involved in the determination of value in a decision context (Samanez-Larkin et al., 2007). The entorhinal cortex connects these two vital functional networks; thus, a breakdown in this brain region could leave an individual unable to foresee a negative outcome or recognize characteristics of a scam scenario and make appropriate value-based decisions in these situations. The insula cortex activates when someone experiences a gut reaction about a social situation, often in a negative manner (Han et al., 2021). Therefore, a breakdown in this brain region may fail to alert an individual to the potential dangers of a scam situation. Research on functional connectivity supports these narratives. The default network includes the medial prefrontal and medial temporal cortices and is involved in theory of mind and social cognition (Hughes et al., 2019). The salience network includes the insula and frontoparietal regions and is involved in attention and working memory (Menon & Uddin, 2010). Greater functional connectivity between these networks is associated with stronger decision-making (Fenton, 2025; Spreng et al., 2017).
In discussing the neuropsychology and neuroscience of scam and fraud, two points bear greater emphasis. Because a major consideration is the vulnerability of the victim, which depends on factors that are gradual and nonbinary (age-associated neuropathology, social isolation, medical or psychological symptoms), then vulnerability should be considered a spectrum rather than a binary construct. Accordingly, if factors such as a threshold level of age-associated neuropathology are used to determine vulnerability, then most older adults would not be considered vulnerable. Further, most older adults will not experience Alzheimer’s disease, and most will not even experience cognitive impairment. Vulnerability might be categorized according to the severity of neuropathology. However, the proportion of older adults with severe vulnerability will be less than that of those determined to have moderate vulnerability, and those with moderate vulnerability will be less than those with little to no vulnerability. Multiple lines of reasoning might be used to support this notion, but one example would be the prevalence of MCI in older adults, which goes up with age but in 60- to 64-year-olds is only 6.7% of the population and even in 80- to 84-year-olds is only 25.2% of the population (Petersen et al., 2018).
The other point that bears greater emphasis is the notion that financial vulnerability might be best understood as an intersectional model. Figure 1, taken from a model of financial vulnerability in older age, illustrates this point. There are multiple factors, both within and outside the older adult, that may intersect to provide a unique vulnerability profile that may predispose the older adult to scams. However, there may be no vulnerabilities within the older adult at all, and all factors that contribute to scam vulnerability may be external. There needs to be an appreciation not only for the vulnerability of the older adult but also the characteristics of the person committing the scam or fraud and the greater contextual factors that either contribute to or inhibit scam vulnerability. This approach parallels models of elder abuse, which incorporate these factors as three separate considerations (i.e., the vulnerability of the older adult, the person or entity committing the scam or fraud, and the contextual factors; Han and Mosqueda, 2020).
Intersectional model of financial vulnerability among older adults.
In conclusion, neuropsychological and neuroscience research on decision-making in older age has yielded significant insights into the cognitive and neuroimaging correlates involved in a risk profile for scam vulnerability. Limitations currently include relatively few longitudinal studies that clarify the temporal links between these factors and, in some cases, small study samples impacting generalizability. This work is also in many aspects still nascent; thus, the hope of establishing reliable neural screening or individualized risk-prediction profiles is at best a future endeavor.
Financial Decision-Making and Scams
Mr. Lee, an 82-year-old retired, divorced engineer and entrepreneur, became entangled in a romance-inheritance scam. He was contacted online and by phone over a period of a few months before learning that if he were to marry his newfound girlfriend they would receive $15 million in inheritance. She explained to him that, in her culture, one had to be married to receive an inheritance. Mr. Lee’s net worth was around $12 million, but most of that wealth was in properties that he owned. Over just 10 weeks, he sent more than $900,000 to the scammers to “clear up paperwork issues.” When his adult children came to visit, they found that he was neither eating nor sleeping much at all, and there was rotting food in his refrigerator. He was also about to have his house foreclosed on because of delinquent taxes. The children took Mr. Lee to meet with his bank president and an FBI agent. Both the bank president and the FBI agent tried to inform Mr. Lee that he was involved in a scam. He did not believe them. He did, however, want to meet his wife to be, and when she provided the name of the city she “lived in,” 1,000 miles away, he got in the car and began to drive to see her. He stopped only when he was involved in a car accident. His children moved him to another city and petitioned for guardianship. An independent psychological evaluation was conducted, and Mr. Lee showed some of the oft-found symptoms of scam victims: early cognitive decline, a high level of depression, perceived dramatic loss of status, and deficits and vulnerabilities in his financial decision-making. 8
This section examines financial decision-making through the lens of financial capacity research and through the lens of distinguishing features of financial decision-making and neurocognitive functioning. Marson (2016) believed existing measures were too basic to assess financial capacity and developed three approaches that underlie assessment tools that do more to directly assess financial capacity: the clinical model, which assesses financial skills relevant to independence; the decision-making model based on Appelbaum and Grisso’s (1988) approach to decision-making capacity; and financial capacity as financial function in the real-world model proposed by the Institute of Medicine (2016). Given our focus on financial decision-making regarding sending money and/or personally identifiable information to fraud criminals, we focus on the clinical model and the decision-making model.
Cohen et al. (2020) and Ghesquiere et al. (2019) reviewed 13 clinical assessment tools for measuring aspects of financial capacity and underscored the need for improved practice guidelines in the clinical assessment of financial capacity. Cohen et al. (2020) noted four challenges to assessing financial capacity. First, there is often variability within different domains of financial capacity (e.g., decision-making vs. performance). Second, the field currently relies too heavily on cognitive screening measures. Third, serious questions persist regarding the ecological validity of cognitive tests and their relation to financial capacity outcomes. Fourth, outcomes are inconsistent because of a lack of standardized assessment approaches. All but one of the tools assessing decision-making used neutral vignettes or semistructured interviews.
Financial capacity deficits, and especially deficits in financial management as well as decision-making, are linked to risk for financial exploitation and scams (Conrad et al., 2010). In their six domains of financial exploitation, with theft or scams being the way monies are lost, Conrad et al. (2010) listed deficits in financial decision-making and financial management as significant fraud risk factors. This is consistent with Marson’s (2016) conceptualization of the clinical model of financial capacity assessment. Deficits in measures of financial skills and decision-making heighten the risk of scams. The items from Marson’s Financial Capacity Instrument are traditional objective problems and vignettes that may or may not relate directly to the examinee’s life.
An alternative approach to assessing the relationship of fraud to financial decision-making was based on the person-centered approach to assessment and specifically from Mast’s approach to whole-person dementia (Mast, 2011), which seeks to better understand the history of a person’s values, likes and dislikes, and strengths. Lichtenberg et al. (2015) expanded on this concept by applying it to specific financial decisions and creating a person-centered financial decision-making assessment tool. Person-centered assessments place high importance on hearing the older adult’s decision-making perspective for an actual important decision in life. The decision to engage with a scammer is an example of a financial decision that is best understood from an analysis of the individual’s decision-making.
A person-centered approach to financial decision-making and relation to scams
The Lichtenberg Financial Decision Rating Scale (LFDRS) combines a financial decision-making framework from the literature on financial capacity with real-world financial capacity from the National Academy of Sciences (Lichtenberg et al., 2015). Building on the Appelbaum and Grisso (1988) model (see Fig. 2), the LFDRS was developed using context mapping to expand the conceptual framework for financial decision-making. The Appelbaum and Grisso model, based on the functional test used for guardianship and other related legal standards, focuses on the older person being able to communicate choice, understanding, appreciation, and reasoning. The LFDRS expands this model by measuring actual decisions (such as the decision to send money to a scammer), focusing on the older adult’s version of the decision, and analyzing these informed decision-making elements. The result was a clinician-administered scale used to assess financial decision-making ability. The scale contains 56 items across five subscales: financial situational awareness, psychological vulnerability, intellectual factors, susceptibility to undue influence, and past financial exploitation.
LFDRS conceptual model. LFDRS = Lichtenberg Financial Decision Rating Scale.
Interrater reliability was measured by having 10 raters view five different taped interviews of the financial decision-making scale assessments. The raters then rated the informed decision-making abilities of the older participant (Lichtenberg et al., 2015). Using a sample of 200 older adult community volunteers to investigate how well the factor analysis fit with the conceptual model, Lichtenberg et al. (2018) found that there was a good fit between items and their subscales. Using data from this same sample, Lichtenberg and colleagues found significant associations with cognition (Lichtenberg et al., 2018) and financial exploitation (Lichtenberg, Campbell, et al., 2020). Higher scores reflect more vulnerability across the different factors (i.e., contextual and intellectual) in financial decision-making. Flores and Lichtenberg (2023) conducted a cross-validation study of the scale and found that the LFDRS scores were significantly related to an executive functioning measure, above and beyond education and other demographic measures, and that higher financial decision-making vulnerability was significantly related to scam-victimization cases.
In general, there is a paucity of financial decision-making screening tools for use by professionals who are not psychologists, such as Adult Protective Services (APS) workers, financial services professionals, and law enforcement professionals. Those that do exist have less robust psychometric properties. One example is the Susceptibility to Scams questionnaire (STS; James et al., 2014), a five-item self-report questionnaire in which examinees indicate their agreement to a statement such as “If something sounds too good to be true, it usually is.” The items of the STS were derived from the findings of AARP and statements from the FINRA, which assesses personal characteristics and behavioral indicators that are related to risky financial decision-making (DeLiema et al., 2021; FINRA, 2021). The STS has the benefit of being extremely brief and likely nonthreatening to administer to an older adult. However, this measure relies on self-reports of the older adult’s beliefs about their behavior and does not directly assess financial decision-making or the experience of fraud.
Abrams et al. (2019) discussed the implementation of the Interview for Decisional Abilities (IDA) in APS offices in several states. The IDA is another semistructured interview designed to broadly evaluate an adult client’s decisional abilities to utilize services offered by APS. Like the Assessment of Capacity for Everyday Decision-Making (Lai et al., 2008), the IDA can be flexibly used in a variety of decisional questions, including financial decision-making and potentially in fraud cases; assesses the client’s ability to understand a specific decision; appreciates the potential risks and benefits of various options; and reasons through to a decision. This tool is not meant to provide a specific risk score for decisional abilities but rather to create a dialogue with the client about risk. To date, there is little empirical evidence about the use and implementation of these tools in fraud cases.
Lichtenberg, Campbell, et al. (2020) asked the conceptual question of whether the contextual aspects of financial decision-making were related to financial exploitation, independent of informed decision-making factors. Leaving out the questions aimed at measuring choice, understanding, appreciation, and reasoning, the authors compared responses of 78 verified scam and identity-theft victims to 164 nonvictims on contextual items of the LFDRS. The contextual subscales are self-reported items and encompass personal finance areas such as financial strain, financial self-efficacy, financial satisfaction, anxiety or depression regarding finances, the presence of or loss of a confidante with whom finances were discussed, relationship strain caused by finances, and conflicts about how money is spent. This study’s findings resulted in 17 items that differentiated victims of financial exploitation from nonvictims. These 17 items were then assembled into a new scale, the Financial Exploitation Vulnerability Scale (FEVS), and scale items demonstrated good internal consistency (α = .82) and area under the curve (.80). Moray and Lichtenberg (2025) cross-validated the FEVS findings on a new sample. The FEVS lends itself to work with victims of scams and fraud because of its range of topics assessed.
Since the introduction of the FEVS, there have been several more studies using the complete FEVS or versions of it. The Health and Retirement Study used six items from the LFDRS contextual items in 1,200 older adults and found higher levels of perceived financial vulnerability to be predictive of physical and mental health (Lichtenberg, Paulson, & Han, 2020) and future wealth loss (Maynard et al., 2025). High levels of interpersonal and social dysfunction, older age, lower household income, low self-rated health, a history of financial exploitation victimization, fewer/more years of education, low financial self-efficacy, increased levels of financial hassles, ageist attitudes, and older subjective age (Hall et al., 2022; Lim et al., 2023; Weissberger et al., 2023) have been associated with increased financial exploitation vulnerability. Using a single-item subjective cognitive-decline measure, Lichtenberg et al. (2021) found that subjective cognitive decline was associated with financial exploitation vulnerability, even after demographic measures were controlled for.
Researchers have explored other factors that might help explain vulnerability to financial exploitation. Lindez-Macarro et al. (2025) studied the growth between 1995 and 2024 of financial fraud studies. Their bibliometric analysis revealed that cognition and decision-making were two of the most prominent areas of study among older adults. In another line of investigation, Yang et al. (2025) found that increased persuadability and increased insensitivity to trustworthiness cues were related to increased vulnerability to financial exploitation, and Weissberger and Bergman (2025) showed a link between reflective functioning and financial exploitation.
Future directions
Although technology will hopefully provide many new solutions to scam detection and prevention, there will continue to be a need to address the decision-making process of the scam victim. Lichtenberg and Hall (2025) piloted a scam-prevention approach, based on a prevention science model, focused on reducing risk factors. This brief, three-session intervention focused on five areas: financial exploitation vulnerability, financial literacy, a mnemonic to convey common approaches by scammers and to be used as a quick reference and reminder, choosing a trusted advocate, and creating a financial inventory. The results from the first 50 participants were very promising in terms of reducing risk factors, and participants found the program very helpful and satisfying. This is but one example of using research and conceptual approaches to intervene with the potential scam victim before they are scammed or even as a secondary prevention approach. Reducing risk factors across several scam domains will likely be helpful to potential victims.
The Emotional and Psychological Impact of Fraud and Psychotherapeutic Interventions
Mr. and Mrs. Jones were a couple in their mid-70s. Mr. Jones worked as an engineer. He started his own company and retired with approximately $10 million in assets. Mrs. Jones worked as a physical therapist. They were looking forward to transitioning from working to golfing, traveling, and enjoying a high quality of life. Mr. Jones viewed himself as an experienced investor with some risk tolerance. His wife was much more conservative and preferred money-market-type investments. He was invited to join an investment club by his longtime friend. The club was ultimately revealed to be a Ponzi scheme. Total losses over 3 years were close to $8 million, he had an additional $2 million due in unpaid taxes on the withdrawn funds, and the IRS began to aggressively pursue him. 9
Mr. Jones was psychologically devastated after learning about the deception. He became depressed and reported suicidal ideation. He blamed himself. He suffered health problems, including high blood pressure, poor sleep, and frequent intrusive thoughts regarding his financial distress. Even worse, he recommended the investment pool to close friends and family. Additionally, Mr. Jones went into debt.
His wife, Mrs. Jones, was shocked and devastated. She had grown up in a poor family and thought she had escaped poverty and financial worries through education and hard work. She also developed high levels of anxiety and worry, lost sleep, and saw relationships with family deteriorate. The behavioral, psychological, and medical outcomes exemplified in this case are common sequelae of fraud victimization.
The psychological impact of fraud
This section reviews what is currently known in this emerging area and identifies potential areas of assessment and intervention for psychologists working clinically with individuals who have suffered from this type of crime.
Fraud victims typically report that the emotional impact of fraud victimization is worse than the financial loss. Modic and Anderson (2015) surveyed 10,000 participants and assessed the link between the types of fraud victimization and their impact. The study included a diverse range of fraud categories, including fake vacation rental/accommodation, computer hacking/tech scams, phishing, lottery scams, advance fee scams, romance scams, and pyramid/Ponzi schemes. Affective consequences were rated higher than the financial impact across fraud categories. The authors noted that pyramid schemes/Ponzi schemes had the highest financial and emotional impact of the types of fraud surveyed, possibly indicating a correlation between the sum of financial loss and its emotional consequence. Fraud victims are, of course, impacted financially, and how that interacts with the emotional outcomes depends on the type of scam, the stage of life, and the financial status/goals of the individual. Older consumers, for example, might have goals such as maintaining a certain quality of life during retirement or leaving a legacy succession of a family business, whereas middle-aged adults may have goals such as paying for college for their children and saving for retirement. Perpetrators often elicit this information, as well as other financial and personal information, so they can target the fraud to allegedly meet the goals stated by the consumer, making it more attractive to them. Of course, ironically, this engagement results in the opposite effect, leaving victims with no savings for college, limited retirement savings, and diminished quality of life as the individual ages, particularly if they are no longer in the workforce.
Cross et al. (2016) reported that among a sample of 80 substantiated fraud victims aged 30 to 77, the majority reported wide-ranging effects on mental health, physical health, and relationships and described the experience as “devastating, soul-destroying, and an event that changed their attitude to life.” Physical symptoms included changes in sleep, nausea, and weight loss. A minority of participants reported threats to physical safety, particularly in cases in which they traveled overseas to “meet” their partner or in cases involving blackmail/sextortion. The use of secrecy during the scam isolates the victim from support, and the large financial losses often impact the family system. In terms of interventions, Cross and colleagues reported that victims asked for counseling not only to address the aftermath of the fraud but also the preexisting conditions that resulted in increased risk of victimization in the first place.
In a study on the nontraditional costs of financial fraud, including its emotional impact, the FINRA sampled 600 self-reported victims over the age of 25 who reported losing money (FINRA, 2015). Per the FINRA, nearly two thirds of victims reported at least one nonfinancial cost of serious fraud: 50% reported severe stress, 44% reported anxiety, 38% reported difficulty sleeping, and 35% reported depression. Other key findings were that individuals who lose large amounts of money were more likely to experience greater nonfinancial costs/emotional distress. Victims confused about the details of fraud were far more likely to report experiencing nonfinancial costs to a serious degree. Moreover, 47% of victims reported blaming themselves, including experiencing emotions such as guilt, humiliation, and decreased confidence. Sixty-one percent reported that they felt as if they were defrauded for being too trusting, perhaps reducing their trust moving forward (FINRA, 2015). For example, in the case of Mr. and Mrs. Jones, the couple explained that they had some remaining assets, but they were paralyzed and did not trust their own judgment in terms of what to do. A similar victim commented, “I can’t make another mistake.”
Freshman (2012) surveyed 172 victims of the Bernie Madoff scheme and reported that the sudden, dramatic financial loss resulted in posttraumatic stress disorder (PTSD)-like symptomatology. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013), at this time, does not include devastating financial ruin as a qualifying Criterion A of PTSD. However, although fraud victims may not currently meet the full DSM-5 criteria for PTSD, many symptoms associated with PTSD occur in fraud victims. Freshman (2012) used the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5; Weathers et al., 1993) in her study of Madoff victims. Using the PCL-5 criteria and details, 56% of the sample met the criteria for PTSD as a group, using the DSM-5 for criteria, while acknowledging the lack of Criterion A that is a lack of a life threatening stressor. In addition, 61% reported high levels of anxiety, 58% reported high levels of depression, 34% indicated health-related issues, and more than 90% affirmed a loss of confidence in financial institutions.
In another survey of fraud victims from the Madoff scandal, Glodstein et al. (2010) conducted a secondary data analysis using 65 victim impact statements filed with the U.S. District Court in 2009 and later used for Madoff’s sentencing. These letters and emails were available as public access statements. According to the authors, the most frequently described emotional symptoms in these statements were hopelessness (18%); anger, rage, and pain (17%); emotional despair and devastation (17%); and anxiety (16%). The authors referred to these collective psychological outcomes as “fraud trauma syndrome” (Glodstein et al., 2010) and noted that many fraud victims reported suicidal thoughts.
Spalek (1999) conducted a qualitative analysis of individuals in the United Kingdom who were the victims of Robert Maxwell in another famous Ponzi scheme. In this case, retirees invested their pension money in the scheme, and according to Spalek, experienced psychological, emotional, physical, financial, and behavioral changes as a result of that victimization. The Maxwell Ponzi scheme impacted roughly 30,000 pensioners in the United Kingdom. Emotional symptoms included anger, anxiety, and stress. Spalek also noted the victims’ perception of their health or their partners’ health had worsened following the financial loss.
Recent work with the Ponzi-like scam known as pig butchering victims has described a similar psychological impact as described in earlier studies, including shame and embarrassment, loss of trust, and poorer mental-health outcomes, including depression, anxiety, and PTSD symptoms (Oak & Shafiq, 2025). The authors also noted that shame and embarrassment deterred the victims from coming forward. Those who did report were informed that there was not much that law enforcement could do because scammers often operated outside of the United States.
In their study regarding fraud sequelae, Button et al. (2014) surveyed 800 fraud victims by phone and completed 30 in-person, in-depth interviews. Victims reported increased stress, anger, decreases in self-esteem, self-blame, worse relationships, poor physical health, poor mental health, increased risk of suicidal ideation, loss of confidence, and changes in financial behavior.
Whitty and Buchanan (2016) conducted in-depth interviews with 20 individuals who self-identified as individuals who had been victimized in a romance scam, with the amount of money lost ranging from £300 to £240,000 (about $400 to $350,000). In this qualitative survey, victims reported feeling that they had been sexually abused, mentally raped, depressed, suicidal, and had symptoms of PTSD, including intrusive thoughts and hyperarousal.
Taken together, this review of available articles on the psychological impact of fraud reveals consistent themes emerging in terms of mood, symptoms, trauma, and negative beliefs about oneself, including blaming oneself, losing trust, and having lower confidence overall. Psychologists are well aware that high levels of stress can result in worse health outcomes (Candeias et al., 2024).
There is some research related to the physical health of fraud victims. Zunzunegui et al. (2017) surveyed 188 individuals who were either victims of preferred shares or foreign currency mortgages in Spain. According to the authors, individuals who were victims of fraud had poor health, more mental-health issues, poor sleep, and decreased quality of life compared with a comparable population matched for age. Notably, victims who received financial compensation ultimately had better health and better quality of life than victims who remained uncompensated (Zunzunegui et al., 2017). Sarriá et al. (2019), using data from the 2017 Madrid Health Survey, analyzed the impacts of financial fraud on health-related quality of life. The sample included 4,425 individuals with a mean age of 48.9 years. The self-reported prevalence of financial fraud was 10.1% for this sample. In this study, the quality of life worsened with increasing economic impact. More specifically, the authors reported that limitations in social activities as a result of health, feeling chronic pain, perceiving less availability of help, and having worse overall quality of life were significantly associated with the economic impact of fraud.
Beyond compensation, other moderators that have been reported in terms of increased risk of emotional distress include a previous history of depression, large financial losses relative to net worth, and a perception of a decreased standard of living (Ganzini et al., 1990).
In terms of the psychological impact on older victims specifically, there is evidence of disproportionate negative psychological harm to older adults. In a large study of 26,735 EU citizens, Kemp and Erades Pérez (2023) reported that older adults (over age 65) were more likely to be victims of fraud in general, and impersonation scams in particular, but less likely to be victims of online fraud. The authors reported that older adults experienced increased anger, irritation, embarrassment, and negative impacts on physical health. Older adults also have a reduced time horizon; that is, they are simply not able to replace stolen funds, which increases fears of financial insecurity and diminished quality of life in retirement. Pan et al. (2023) found that catastrophic financial losses were associated with increased risk of cognitive decline and dementia in a large U.S. sample, suggesting scam victimization may have long-term health and cognitive consequences.
Assessing emotional distress in victims of fraud or scams
Generally, the approach of a psychological assessment in these cases is similar to other generally accepted clinical interviews that take a biopsychosocial approach with a focus on financial decision-making. As noted above, because being a crime victim generally, and being the victim of financial fraud specifically, can be incredibly stressful, a review of the victim’s medical records before, during, and after the crime can also be helpful to better design interventions to address preexisting vulnerabilities and improve their quality of life. Interviewing fraud victims’ family members is also a crucial step in assessments. These individuals may have observations regarding behaviors that the victims themselves are too embarrassed or ashamed to report. Moreover, research has shown the importance of family members in protecting older adults against financial exploitation (Weissberger & Bergman, 2025).
In terms of psychological tools, these will depend on the age and symptomatology present in the victim. On the basis of the literature, it could be helpful to include an assessment of PTSD symptomatology, such as the PCL-5, acknowledging that Criterion A may not be present. The PCL-5 has been used in empirical literature with fraud victims, including in Freshman (2012), Nolte et al. (2024), and Weissberger and Bergman (2024). An age-appropriate tool to assess depression, anxiety, and self-reported physical health is also recommended.
Areas of focus in psychotherapy
In terms of psychotherapeutic approaches, there is currently limited empirical evidence regarding specific modes of intervention and outcomes with fraud victims per se. Suggested areas of research include examining the use of trauma-focused approaches, including those that acknowledge shame and self-blame as critical components of these cases, which could be beneficial. In addition, cognitive behavioral therapy and other cognitive approaches result in reframing negative cognitions that the individual may have related to themselves and the world. Tools to address anxiety, stress, and changes in sleep, such as meditation, mindfulness, and acceptance-related psychotherapies, may be beneficial. Some pilot groups are operating that created support groups for scam victims to create a community in which one can seek support without feeling judged. Skill building in the area of financial literacy has been another intervention that has shown some promising results (Lichtenberg & Hall, 2025).
In summary, understanding the psychological and emotional effects of the fraud experience is an emerging area of research. Many studies to date are limited to smaller samples and qualitative approaches given the ethical and practical difficulties of lab-based work in this area. Unfortunately, as scam rates soar, there will be more need for trauma-informed clinicians with experience to respond to the psychological aftermath of victimization, as well as consider approaches to address the preexisting risk factors that lead to increased victimization in the first place.
Scam Prevention
On October 10, 2023, a story in The Guardian (Jones, 2023) unraveled how a senior manager at an investment firm had lost £300,000 (about $400,000) to cryptocurrency scammers. It all started when he received a phone call from a friend who was using an app to trade cryptocurrency. Tempted by the lucrative possibilities, he was drawn into opening a crypto wallet. To test the waters, he placed only a small amount of money; it worked. He was not only making a profit but was able to withdraw funds into his bank account. After a month, he was told that to continue trading, he must increase his investment to £10,000 (about $13,000), which he was happy to do. Again, he faced no issues, and the profits kept on rising. Not long after, he was invited to a special event (called an airdrop), with the possibility of making further profits. However, he needed to invest at least £100,000 (about $134,000) to participate. Before transferring the funds, he spoke to a customer service representative. After a few more interactions, he wired all of his life savings. The ordeal did not end there. Via an elaborate scheme, the scammers demanded more and more money for various reasons. Needless to say, the manager lost everything.
Fraud prevention through education
Increasing scam resistance through education, awareness, and training is the most researched approach to fraud prevention. According to inoculation theory (McGuire, 1964), warning consumers about scams and training them to identify fraud increases scam resistance by helping to produce anticipatory counterarguments that ward off persuasive appeals. Indeed, a study of people who reported fraud found that those who knew about a scam before being targeted were 80% less likely to respond (DeLiema, Li, and Mottola, 2023). Another study that used a mock government imposter scam found that those who did not answer the scam call had the highest scam awareness, suggesting that prior knowledge is protective (Yu et al., 2023).
An inoculation study by Scheibe et al. (2014) experimentally tested the effectiveness of forewarning vulnerable consumers about telemarketing fraud and then exposed them to a mock scam. The initial forewarning messages were delivered over the phone by AARP Fraud Fighter volunteers, who either warned about the same scam that the participant would later be exposed to or a different scam. Effects were tested after a 2- or 4-week delay, at which time a former telemarketer called participants, pitching a federal stimulus grant and asking for personal information. Compared with no forewarning, both the same scam and different scam forewarning messages were effective at reducing engagement after a 2-week delay, but only the different scam warning was effective after 4 weeks.
Interactive training also improves fraud detection. DeLiema et al. (2025) tested the effectiveness of a digital fraud detection training program in which participants interact with emails and websites and label them either real or a scam. They get immediate feedback on accuracy, along with contextualized tips on what to look for to improve future judgments. Both the interactive training and the tips in written form immediately improved the accuracy of fraud detection, but only the interactive training preserved these effects after a 2- to 3-week delay.
Burke et al. (2022) tested the immediate and delayed effectiveness of investment fraud awareness training delivered through short educational videos or written text. Participants in both the video and text-based trainings were significantly less interested in fraudulent investment opportunities compared with participants who received no training. After a 6-month delay, however, only participants who received reminder messages showed reduced interest in the fraudulent investment opportunities, indicating that for inoculation to be effective, “booster” scam awareness messages are needed. Importantly, neither training modality in the Burke et al. (2022) or DeLiema et al. (2025) studies reduced participants’ evaluations of legitimate investment opportunities and digital content; however, in a Kenyan sample, participants who were given tips on how to spot text message scams became more cautious of text messages overall. In that study, participants correctly flagged scam text messages as fraudulent but falsely flagged legitimate text messages as fraudulent (Kubilay et al., 2023). These contrasting findings indicate that more research is needed to understand what training modalities help increase specificity in fraud detection without increasing the rate of false positives and reducing overall trust.
Most fraud awareness and training studies are delivered under controlled experimental or laboratory conditions. There are significantly fewer field experiments on the efficacy of large consumer awareness campaigns; however, one Danish study analyzed the impact of a fraud warning message sent to 11,447 banking clients aged 40 and older. There was no effect of the warning on subsequent rates of fraud victimization (Jensen et al., 2024). Another study tested a national countermarketing campaign to reduce the risk of revictimization among mail fraud victims. Langton et al. (2025) mailed fraud awareness materials to victim households identified by the U.S. Postal Inspection Service. Compared with households that received no materials, those that received a series of “Be a Fraud Fighter” letters, brochures, and flyers were less likely to respond to a subsequent mail scam in the following 4 months; however, the size of the treatment effect was small. These studies suggest that many recipients either do not attend to fraud prevention messages or that the messages are not sufficiently motivating to change behavior.
Chugh and Narang (2023) argued that heightened awareness may not translate into changed attitudes and behaviors because mass marketing campaigns underestimate the affective influence of scam messages that impair reasoning and decision-making in the moment (i.e., lead to System 1 processing). Consumers may also ignore generic messages that are presented out of context. On the basis of interviews with fraud victims, Wen et al. (2022) designed and tested different versions of consumer warning messages and found that warnings are most effective when delivered in the relevant context, such as on the target’s screen before authorizing a suspicious transaction, and when the warning refers directly to the suspicious activity, for example, “The current transaction is highly likely to be deceptive,” rather than a generic warning such as “Beware of fraud.”
Most fraud awareness messaging is focused on digitally active, English-speaking, middle-aged, and cognitively healthy older volunteers. Older adults with cognitive impairment are also harder to reach through mass marketing campaigns delivered through digital channels. If exposed to awareness messages, this population may be less likely to encode and recall the information. Indeed, survey research by Button et al. (2024) indicated that more than a quarter of older adults could not recall receiving any fraud prevention or awareness advice in the prior 6 months. The researchers also found that older adults preferred receiving advice about scam prevention from friends and family and perceived that advice as the most useful.
Children, young adults, and other vulnerable groups—such as non-English-speaking immigrants—also need tailored information and training on scams that they are most likely to encounter. Google launched a program called Be Internet Awesome (Google, n.d.) that includes resources on online scams for children, educators, and families. Fraud education should be embedded into primary and secondary school curricula and routine consumer activities in which fraud often occurs. Examples of settings and activities to embed consumer fraud awareness include opening a bank account, creating a social media account, beginning a new job, taking out a loan, and in the wake of any natural disaster.
Fraud prevention through advanced financial planning
Aside from education and awareness, another proactive strategy to reduce the likelihood of scam victimization is engaging in advance financial care planning. This involves identifying someone who is legally appointed to provide financial oversight and money management assistance in the future. Using legal tools such as trusts and durable powers of attorney, aging people can protect their future selves from many financial mistakes and pitfalls by selecting the right person to monitor their accounts and ensure their money is being used appropriately. Planning should begin prior to retirement, when a person is cognitively healthy and can make reasoned decisions about who in their social network is best suited for the role (Zheng & DeLiema, 2024).
Individuals can also engage in actions to safeguard their personal information and accounts online. Protective measures include activating two-step authentication or using a passkey to log in to online accounts via mobile phone biometrics. Individuals should always use unique and complicated passwords and limit the personal information they share on SNSs. These actions reduce exposure to scams and the likelihood of identity theft.
Future Directions: The Need for a Whole-of-Society Approach to Fraud Prevention
Fraud has existed since the dawn of the marketplace, and no regulation or enforcement actions, however sweeping, will fully eliminate these threats. However, like the multipronged efforts to reduce tobacco use, bold actions such as antifraud legislation, law enforcement actions, and consumer awareness campaigns may yield meaningful reductions in the prevalence of victimization and magnitude of losses in the future. Table 3 presents a summary of critical fraud prevention and response actions for each stakeholder within the fraud ecosystem.
A Whole-of-Society Approach for Fraud Prevention.
Note: SNS = social networking site.
Regulating industry
Given the multitude of errors and biases in human decision-making and the advanced social-engineering tactics used by scammers, the most effective fraud prevention strategy is to stop scam messages from reaching their targets in the first place. Efforts to mobilize the relevant stakeholders have been slow but have ramped up following the surge in financial crimes during the COVID-19 pandemic. Countries such as the United Kingdom, Australia, and Singapore have taken the most proactive measures to combat fraud to date. They have introduced new regulations, centralized reporting and investigation, modified information-sharing rules to facilitate cross-sector collaboration, and shifted liability and costs onto the private sector. In the United Kingdom, for example, electronic payment processors are required to reimburse fraud victims up to £85,000 (about $115,000) depending on their losses. In the first 3 months of the new law, 99% of victims were reimbursed £27 million (Payment Systems Regulator, 2025). In addition to making victims whole, the other legislative aim is to motivate financial services companies to institute more upstream fraud detection and prevention measures to avoid downstream costs and reputational harm.
Many scams originate on SNSs such as TikTok, Facebook, and Instagram and through caller ID spoofing using Voice over Internet Protocol technology. To hold companies accountable for scammers’ misuse of their services, countries are considering shifting liability more upstream by penalizing internet service providers for hosting bogus websites, SNS companies for allowing fraudulent content and fake profiles, and telecommunication companies for allowing fraudulent text messages and calls to reach their targets. A less punitive example in the United States is the Pallone-Thune Telephone Robocall Abuse Criminal Enforcement and Deterrence (TRACED) Act that requires voice service providers to implement protocols to authenticate calls and text messages to stop illegal robocalls and scam messages (Pallone-Thune TRACED Act, 2019). After the TRACED Act was enacted, the volume of illegal robocalls declined between 25% to 50%. However, criminals are using new strategies to outsmart call authentication protocols, and law enforcement does not have enough resources to trace and prosecute the vast majority of offenders (Prasad et al., 2025).
More recently, the U.K.’s Economic Crime and Corporate Transparency Act (Home Office, 2025) aims to hold corporations criminally liable for “failure to prevent fraud.” The law is intended to motivate private-sector entities to develop an antifraud culture and develop better detection and prevention protocols such as strengthening identity verification systems and quickly deactivating suspicious websites and profiles. Similarly, Australia is working on sector-specific codes to impose mandatory fraud controls on private-sector companies to prevent, detect, disrupt, respond to, and report scams. Companies that violate their sector-specific codes can be fined up to AU$50 million (Scams Prevention Framework Act, 2025). In 2023, the Australian government helped remove thousands of websites pitching fraudulent investment opportunities, resulting in a 29% decrease in reported investment fraud losses in the second half of 2023 (Jones, 2024). The U.K.’s Online Safety Act requires search engines and SNS companies to moderate and remove suspected fraudulent content and create channels for users to report scams on their services, such as the use of fake accounts or false advertisements. Companies that violate the act may be fined up to £18 million or 10% of global turnover, whichever is greater (Online Safety Act, 2023).
Bolstering law enforcement capacity
The United Kingdom and Australia are also combating fraud by hiring dedicated fraud investigators and investing in intelligence-sharing ecosystems to pursue fraudsters around the world (Home Office, 2023; Scams Prevention Framework Act, 2025). Both countries simplified the fraud reporting process to make it easier for victims to share their complaints and seek redress from companies that facilitate scams. Singapore launched the Anti-Scam Command, a national policing agency staffed with representatives from major banks and retail organizations that work hand in hand with police to trace funds and freeze accounts. Singaporean police also have the legal authority to stop transactions by placing temporary holds on victims’ accounts while the transactions are being investigated (Abraham et al., 2024). At the same time, there is a need for international law enforcement collaboration, including the prioritization of fraud by intelligence agencies.
In the United States, 10 the threat of fraud far exceeds the capacity of U.S. law enforcement agencies to investigate and prosecute transnational criminal organizations. In 2024, the FBI was only 66% effective in freezing fraudulent money transfers in response to 3,020 requests, but they received more than 880,000 complaints overall from individuals and organizations (FBI, n.d.). Transnational scams are deprioritized relative to violent crimes, and prosecutors and law enforcement agencies have petitioned Congress for more dedicated resources, claiming that they are outgunned and outmanned by fraud networks (Pirrello, 2024). Creating specialized antiscam task forces with dedicated personnel is critical to enhancing law enforcement capability. These specialized units need modern technological tools to collect and identify patterns in fraud reports and statutory authority to quickly freeze assets that are likely involved in criminal activity (Bourke et al., 2025).
Signal sharing
Nongovernmental organizations are filling the void by helping to develop coordinated national and global strategies to combat scams. All proposed strategies (e.g., Borque et al., 2025) point to the need for cross-industry information sharing to disrupt the global fraud enterprise, as well as the need for victim assistance through free helplines and support groups such as the AARP Fraud Watch Network or, in the United Kingdom, The Cyber Helpline. Technology, retail, and SNS companies such as Meta, Amazon, Apple, Microsoft, and Google need infrastructure to better share information on suspicious Internet Protocol addresses, fake profiles, and other digital signals that indicate fraud. Banks need to share information on compromised accounts and suspicious transactions, and telecommunication companies need to transmit information on offenders across call-screening networks. Law enforcement and criminal justice systems must support these efforts by identifying and arresting domestic coconspirators and working with financial institutions and payment processors to recover stolen funds.
Some of these efforts have already begun. Organizations such as the National Elder Fraud Coordination Center (NEFCC) are focused on supporting law enforcement by analyzing and linking data contributed by private-sector partners. By identifying unreported fraud incidents, the NEFCC can tie separate cases and victims together so that they meet the threshold for investigation. Similarly, the Global Signal Exchange is an international organization that brings together data from multiple economic sectors to detect and combat fraud.
Although the effectiveness of regulations, enforcement actions, and data-sharing practices has not been empirically studied, countries that have implemented more aggressive measures, such as Singapore, the United Kingdom, and Australia, have witnessed a drop in the average loss per victim (Global Anti-Scam Alliance, 2025) and in the number of consumer fraud reports (Stop Scams Alliance, 2025). These interventions are promising because they shift the burden of protection from consumers to the entities that facilitate fraud, thereby avoiding the need for consumers to overcome the errors in judgment and decision-making that scammers exploit. It also shifts the sense of blame from the consumer to the companies that allow scams to flourish. Consumer rights organizations and interest groups such as AARP and the BBB must put more pressure on lawmakers to enact legislation that holds the private sector accountable.
Barriers to a coordinated national strategy to fight fraud
Despite the recognition that immediate action is needed, there are many constraints and forces pushing back on a whole-of-society approach to fraud prevention. For one, private-sector entities tend to resist regulation that requires them to take on costs and liability. For many industries, fraud mitigation is a cost center rather than a revenue generator, and for telecoms, search engines, cryptocurrency platforms, dating apps, and SNS companies, scams actually generate revenue. Scammers pay these companies to use their services to target consumers with bogus ads, phone calls, and direct messages. However, fraud on these platforms and services is harmful to customer trust and brand reputation. Clear regulatory frameworks that specify fraud-fighting roles and responsibilities for each industry, coupled with appropriate safe harbors to protect companies that act in good faith, will motivate companies to be proactive.
Another barrier is that we still do not know the true extent of scam victimization or the base rate of attempted fraud because of fragmented reporting. Part of the issue is a lack of consistency in how consumers report fraud. Most victimizations (and targeting attempts) are never reported to anyone, especially law enforcement (Gottfried et al., 2025). When consumers do report, they typically complain to the entity most closely involved in their financial loss, such as their bank, an online retailer where the fraudulent goods were advertised, or the SNSs that hosted a fake profile. These companies do not necessarily share consumer complaints with regulatory or law enforcement agencies even when they have important intelligence on scam networks. A “no-wrong-door” approach or a single reporting portal is needed so that wherever consumers report scams, complaints are securely shared with the correct law enforcement agency that can analyze trends and prioritize cases for investigation (Borque et al., 2025).
Last, the fraud landscape is evolving faster than ever before. The lawmaking process cannot keep pace because the introduction of bills to fight fraud and protect consumers takes years to go through the system. This policy lag means that any legislation enacted today is already outdated by implementation, and scammers will have already adjusted their modus operandi to evade the new controls. Policymakers need to better grasp the emergency nature of the problem and develop means to fast-track actions and legislation. For example, in times of natural disasters or pandemics (e.g., COVID-19), national leaders can appropriate funding and resources (e.g., law enforcement agencies) and pass emergency legislation, such as through executive orders in the United States. They can also coordinate national and international efforts more rapidly.
Regardless of these barriers, it is imperative that bold actions be taken across all sectors. Transnational fraud organizations have already amassed substantial capital to fund new and more sophisticated scams. In the future, opportunities may arise to coordinate law enforcement actions around the globe so that the perpetrators behind scams are brought to justice and their enterprises dismantled.
Discussion
One of the primary objectives of Psychological Science in the Public Interest is to foster a dialogue among scientists, laypeople, policymakers, private and not-for-profit organizations, and other stakeholders. There is no doubt that fraud is of immense interest to the general public, governments, and various organizations worldwide. Probably no other crime inflicts such an extensive and profound impact on so many people. As we detailed throughout this article, fraud is associated with significant emotional, financial, health, and psychological consequences. It is also linked to the erosion in trust in key institutions. No one is immune—either directly or indirectly—to its pervasive impact. In other words, everyone is at risk regardless of their demographic or individual characteristics.
International crime groups perpetrate scams because they are “easier, less risky, and more profitable than other forms of organized crime” (Borque et al., 2025, p. 8). If the predictions by leading organizations and AI experts are correct, the problem is bound to get much worse. Despite its prevalence and impact, however, fraud has not received enough attention and resources from educational providers, financial institutions, law enforcement agencies, researchers, communication providers, and SNSs. To achieve a meaningful impact, fundamental and urgent changes must take place that reduce the rewards for criminals and shore up targets’ defenses. Aside from the recommendations listed earlier, we advocate for the following necessary steps:
View fraud from three lenses: criminal, national security, and public health.
Allocate funding to study fraud susceptibility, prevention, and treatment. Funding should come from government agencies (Department of Defense, Department of Health, Department of Justice, National Science Foundation, European Research Council, etc.) and the private sector (communication providers, financial institutions, SNSs, and tech companies).
Psychologists should devote attention to fraud as they do to deception and misinformation. There is currently a paucity of data about prevention and treatment. There is also a lack of cross-cultural, large-scale, and interdisciplinary studies.
Combine efforts and lobbying by psychological organizations. The American Psychological Association and the Association for Psychological Science, for example, should join forces to create a unified message and lobbying efforts. Similar efforts should be seen from similar organizations across the world (e.g., British Psychological Society).
Increase public awareness about fraud.
Tackle stigma about fraud. Victims are not to blame and should not feel shame or embarrassment.
Create national and international task forces to fight fraud.
The above suggestions are not meant to be exhaustive. Fraud is a complex phenomenon that involves many players and stakeholders. Its complexity, prevalence, severity, and sophistication are likely to increase, posing new challenges to individuals, governments, and organizations alike. Tackling a widespread and complex phenomenon such as fraud is not easy, but as previous examples illustrate, coordinated, cross-sector, and multimodal efforts can dramatically produce social and behavioral change. Thus, we are optimistic that a coordinated effort could lead to a reduction in the global fraud rate and improve services for fraud victims. There is no doubt that psychologists can and should play a vital role in the fight against fraud. This is a call to arms.
Footnotes
Acknowledgements
We would like to thank Hannah Peeples and Anjali Karp for their help in preparing this manuscript.
Transparency
Action Editor: Nora S. Newcombe
Editor: Nora S. Newcombe
Author Contributions
Y. Hanoch and S. Wood contributed equally to this manuscript and are listed alphabetically. All of the authors approved the final manuscript for submission.
1.
In this article, we focus only on fraud against individuals. The scope of the problem is far more extensive than we can cover and discuss here. Fraud against organizations (both for-profit and not-for-profit) and governmental agencies presents, however, very similar trends. The U.S. Government Accountability Office (GAO), for example, estimated that fraud cost the U.S. government hundreds of billions of dollars during the COVID-19 pandemic alone, largely because of false unemployment claims (GAO, 2025). Moreover, the rate of small and medium-sized businesses (SMBs) impacted by fraud is staggering, with a report by 
finding that 40% of SMBs have been victims of fraud, resulting in an average loss of more than $5,000. Large businesses and corporations also lose billions each year. Addressing this important and pressing issue would require a separate publication.
2.
In the United States, the Trump administration has been seeking to diminish the powers of the Federal Trade Commission and the Consumer Financial Protection Bureau, two agencies that could help protect consumers against fraud.
3.
The growth in scams has also fueled parallel criminal activity, that of human trafficking and the establishment of scam call centers, or compounds. In just one case, 7,000 individuals were rescued from a fraud compound in Myanmar, with thousands more being enslaved. Many law enforcement agencies (FBI, Interpol, National Crime Agency, etc.) have identified a strong link between fraud and human trafficking.
4.
An examination of three of the leading journals in the field of forensic psychology (Law and Human Behaviour, Psychological Assessment, and Psychology, Public Policy, and Law), for example, yielded not a single publication on the topic of fraud/scams, despite publishing several on deception. The journal Law and Human Behaviour, in fact, does not even list fraud/scams as a topic of interest in its current general call for papers (unless they view fraud/scams as a subset of deception). How is it possible that the most common crime in the world, with the highest financial impact and millions of victims, does not even have a single publication at these premier outlets?
5.
Interestingly, and despite the possible affinity, the growing literature on fake news and misinformation has also largely overlooked their possible link to fraud.
6.
A bibliometric review (Lindez-Macarro et al., 2025) of financial exploitation among older adults revealed interesting themes in the literature, including a focus on different types of financial abuse, protection against financial abuse, the role of cognition and decision-making, and, last, factors associated with financial exploitation.
7.
The literature that emerges from Asian countries, for example, has a very different ethnic composition than that from North America, and what is considered an ethic minority in the United Kingdom has little to no relationship to ethnic minorities in Africa.
8.
This case is based on a guardianship case that one of the authors (P. Lichtenberg) consulted on in 2016.
9.
This fact pattern is based on a real case, but to protect confidentiality, demographic and other details have been altered.
10.
In the United Kingdom, only 1% of police resources are devoted to fighting fraud. Law enforcement agencies in other countries likely face similar issues, although data are not always readily available.