Technology Support Fraud Analysis for the Elderly

Elderly vulnerability to fraud

The assessment of financial capacity among elderly individuals engaging with digital financial technologies has gained significant attention in recent studies. Tools such as Electronic Financial Instrument Screening Tool (EFIST) helps clinicians identify the risk of financial exploitation among elderly individuals. Additionally, the Financial Capacity Assessment Tool (FCAT), provides a structured evaluation on decision - making and financial knowledge.⁴ Despite their usefulness, these tools have their limitations, including the subjective nature of assessing financial capacity and the complexity of digital financial tasks.⁴ Importantly, impairments in digital financial skills should not automatically indicate an inability to manage finances.⁴ Additionally, elderly individuals often use technology for social engagement or leisure activities inadvertently increasing their exposure to risks like tech support scams and phishing attempts, underscoring the need for protective measures.

A comprehensive model for fraud prevention has been proposed across three key levels: individuals, communities, and companies.⁸ At the individual level, the model advocates educating elderly users on fraud risks and enhancing their digital security. Community level actions include identifying vulnerable individuals, mapping risks, and fostering social support networks, while the corporate level involves detecting fraud risks in transactions, interactions, and vendors.⁸ However, a gap remains in addressing the specific psychological barriers of the elderly reporting tech support fraud and the critical need for tailored prevention strategies that consider these unique challenges.

Tech Support Scam

Machine learning has been applied to detect Tech Support Scam (TSS) by identifying fraudulent patterns on malicious websites. The AI@TSS detection model achieves this by analyzing the host and code-based features, providing a sophisticated method to combat online scams.² However its current limitations - restricted applicability and reliance on specific dataset means that it may not be adaptable to emerging scam tactics, particularly for elderly users with varying degree of familiarity with digital technology.² Expanding the dataset and field testing could improve the model’s ability to protect vulnerable elderly populations.

Social engineering is central to TSS, with scammers using persuasive tactics to manipulate victims. Scammers build credibility through persuasive communication, often as part of organized call centers, to manipulate victims into compliance.⁹ These systematic approaches make it difficult for elderly victims to identify scams and report them. Unfortunately, current research on TSS fails to focus on elderly-specific vulnerabilities, such as reluctance to report incidents.

Psychological barriers to reporting fraud

Several psychological barriers prevent the elderly from reporting fraud with shame, lack of knowledge, and perceived ineffectiveness of reporting as common obstacles.^10,11 Studies have identified four key themes deterring victims from reporting cybercrimes (1) Shame and fear of repercussions, (2) Perceived ineffectiveness of reporting in achieving emotional and financial recovery, (3) Lack of awareness about scams and available support resources, and (4) the influence of social support in encouraging reporting.¹²

These barriers, compounded by emotional and social factors prevent many elderly victims from acting.¹³ However, substantial evidence of financial loss or support from strong social networks significantly increases the likelihood of reporting.¹³

A key limitation in these studies is the inconsistency in self-reporting of financial losses, which complicates efforts to verify and address the problem effectively. Moreover, cognitive health and the perceived credibility of victims influence reporting willingness.¹⁴ Victims who believe they will be taken seriously when supported by credible witnesses are more likely to report fraud.

In this study, we expand on these findings by incorporating data from the United States providing a cross-cultural comparison of elderly fraud reporting behavior.

Study design

To investigate the unique features of tech support fraud targeting older adults, this study employed a two-prong approach: a comprehensive literature review and a qualitative analysis of real-world fraud cases. For the literature review, the authors focused on reviewing research papers on Google Scholar relating to fraud schemes affecting the elderly, with an emphasis on tech support scams.

Data collection

For the qualitative analysis, data was sourced from the American Association of Retired Persons (AARP) fraud tracking map. We copied and pasted the URL (https://www.aarp.org/money/scams-fraud/tracking-map/) into google chrome. This was accessed on 26th August 2024. This resource was selected for its rich database of fraud complaints, offering raw data unavailable from alternative sources like Internet Crime Complaint Center (IC3) and Federal Trade Commission (FTC) reports, which only provide processed summaries. We inserted the Washington DC zip code 20,000, in the search for a location box. On the right-hand side of the page is a view filter icon. The available filter options included keyword, scam type, contact method, amount lost, payment methods, and date scam occurred. We applied the “date scam occurred” filter, selecting the following date ranges: January-December 2021, January-December 2022, January-December 2023, January-August 2024. For each selected year, we clicked “View Report” to retrieve datasets covering various scam types (e.g. romance scams, online scams, identity theft scams, business imposter scam etc.) across the United States. The data for each year was copied into an excel sheet and filters were applied to isolate cases related specifically to tech support scam yielding a total of 16 cases. While the sample size was small, it allowed for in depth qualitative analysis.

The dataset included detailed information on the type of scam, date reported, scam channel, a description of the incident, and the financial loss categorized into predefined ranges. Incident descriptions revealed varied tactics, such as alarm pop-ups on computers and fake antivirus subscription alerts. Interestingly, some cases labeled as tech support scams were misclassified, indicating the victim’s lack of awareness about different types of fraud.

Data analysis

Each case was systematically coded using MAXQDA, a qualitative analysis tool, to identify recurrent patterns and themes. Guided by deductive analysis and shaped by established concepts, we systematically coded each of the 16 victims’ report into predefined categories: trigger event, initial victim response, scammers tactics and claims, method of financial extraction, realization and aftermath, scam outcome- using different colours to distinguish between them. The data was further organized into analytical categories such as emotional manipulation, authority exploitation, and barriers to reporting aftermath, scam outcome.

However, the studies have several limitations. The reliance on self-reported AARP complaints introduces potential bias, as victims may omit critical details or hesitate to report incidents. The small sample size of 16 cases limits the generalizability of findings. Furthermore, the absence of cross-validation with alternative data sources, such as IC3 complaints, restricts the scope of this analysis. Future research could address these limitations by incorporating diverse datasets and expanding the sample size to enhance the robustness of findings.

Coding framework

Our analysis used a six-theme coding framework to categorize each report. The themes were designed to capture essential elements of the scam process and victim experience, as follows:

This structured coding approach enabled a systematic comparison of each case to identify common tactics, psychological triggers, and potential preventative measures. The data were further organized into analytical categories such as Modus Operandi, Emotional Manipulation, Barriers to Reporting, and Perceptions of Trust and Authority.

Once coded, the data underwent sentiment analysis. Sentiment analysis provided a deeper understanding of victims’ emotional states at different stages of the fraud process, highlighting moments of vulnerability and identifying potential psychological barriers to reporting.

Key metrics from dataset

The analysis of 16 tech support fraud cases revealed distinct patterns in scammers strategies:

Modus operandi and emotional manipulation

Scammers utilize fear-based tactics to manipulate victims. Pop up alerts and alarming visual or auditory cues were frequently employed to compel victims to act urgently, with 81.3% of victims responding by calling the provided number. Victims’ accounts emphasized the aggressive nature of scammer’s interactions. For instance, one victim shared, “that dude on the line got pissed off … I’m not giving him access to my device,” highlighting their resistance in response to mounting pressure. Another victim described receiving a pop-up alert warning of a “system wide security breach” created a sense of urgency that led to compliance. These findings underscore how emotional manipulation - especially fear - is a central tactic in tech support fraud. Increasing awareness of these strategies through fraud prevention education could perhaps mitigate the success of such manipulations.

Barriers to reporting fraud

Several psychological and contextual barriers hindered victims from reporting fraud:

These barriers highlight the importance of addressing emotional and social obstacles in promoting fraud reporting among elderly victims.

Perception of trust and authority

Scammers frequently leverage the perceived authority of reputable organizations to gain the victim’s trust. Many victims complied with the request, believing they were interacting with trusted entities. One victim recounted “Pretended to be from Apple support. I allowed access to screen share”. Another victim, whose father sent a scammer over $4,000, noted how easily the scammer established trust through a perceived association with legitimate companies.

These findings emphasize the need to educate elderly individuals about recognizing and verifying authority claims to reduce susceptibility to fraud.

By integrating these findings with existing literature, this discussion emphasizes their implications for fraud prevention and highlights directions for future research. These results align with⁸ suggesting that a holistic approach to fraud prevention should prioritize educating elderly users on fraud risks and strengthening their digital security measures. Scammers predominantly use pop-up alerts accompanied by urgent visual and auditory cues to provoke fear, triggering victims to call the provided numbers. This resonates with⁹ which expressed that scammers use aggressive tactics such as fabricated threats of system breaches to exploit victim’s emotional vulnerabilities, fostering compliance.

An essential insight is the reluctance of victims to report fraud when no financial loss occurs, corroborating findings from other studies suggesting that crimes perceived as less severe go unreported.^12,13 Emotional barriers such as shame and stigma were prominent deterrents, reflecting the profound psychological impact of fraud, even in cases without monetary consequences. Addressing these barriers requires creating supportive reporting environments where victims feel encouraged to report fraud regardless of financial impact. Educational initiatives should include narratives emphasizing the importance of reporting to track and mitigate scams effectively as a social good, helping others.

The role of family involvement emerged as a significant factor in overcoming psychological barriers to reporting. Victims with supportive networks were more likely to recognize scams and take appropriate action. These findings echo previous research emphasizing the influence of social networks in enhancing fraud resilience.¹² Fraud prevention strategies should integrate family focused interventions, encouraging open communication about scams and equipping family members with resources to assist potential victims.

One of the most significant contributions of this study is highlighting the role of perceived authority in fostering compliance—a factor not sufficiently emphasized in existing literature. Scammers’ ability to impersonate trusted entities, such as banks or tech companies, leverages the inherent trust many older adults place in these institutions.

Alignment with research questions

RQ1: Psychological triggers, such as emotional manipulation through fear and the exploitation of trust in authority were prominently identified as specific levers used by scammers.

RQ2: Emotional responses, including shame and embarrassment, deterred victims from reporting, while family involvement positively influenced reporting behavior. Although qualitative insights were rich, additional quantitative data could better illustrate the broader impact of emotional responses and family support on reporting rates.

RQ3: Barriers to reporting, including perceptions of insignificance, lack of awareness, and emotional barriers were identified. Educational campaigns aimed at destigmatizing fraud reporting and enhancing its importance- irrespective of financial loss emerged as viable prevention strategies. Existing literature also suggests that tailoring these campaigns to accommodate cognitive and educational diversity among older adults can enhance their effectiveness.¹⁵

RQ4: The findings emphasize the significant role of perceived authority in scammers’ success rates, suggesting that interventions must address authority exploitation. Practical recommendations include training programs that demystify authority claims and encourage verification of unsolicited communications.

Educational strategies and dissemination for fraud prevention

These findings of this study underscore the critical role of educational and training initiatives in equipping older adults with skills to recognize emotional manipulation, authority exploitation tactics, and the importance of reporting of tech support fraud. However, our results also highlight the importance of tailoring these programs to the diverse needs and preferences of older adults, leveraging insights from previous research to optimize their effectiveness.

The method of information dissemination is crucial for reaching specific demographics. For example, radio campaigns might resonate more effectively with male audiences, while internet based strategies may not adequately serve populations with limited digital literacy, such as nursing home residents or certain ethnic groups like Hispanics.¹⁵ This underscores the need for localized, culturally sensitive approaches, including community workshops, printed materials, and broadcast in areas with limited internet penetration. These methods ensure inclusivity and accessibility, particularly for vulnerable populations.

In addition to dissemination methods,¹⁶ propose innovative, non-digital educational tools, such as tabletop games and comics, which can stimulate fraud scenarios and teach countermeasures. These tools are particularly effective for older adults with low digital literacy, offering an interactive, hands-on-learning experience that fosters deeper engagement. Unlike digital or fast-paced formats, such as animations and films, these tools accommodate slower learning speeds and encourage active participation, enhancing retention and comprehension.

However, the limitations of some formats must be acknowledged. While films and animations can captivate audiences, they often promote passive consumption and may be too complex or fast paced for elderly learners. In contrast, non-digital tools and simplified materials, such as tabletop games, provide a more active learning environment, bridging the gap for those less comfortable with technology.¹⁶