The Incremental Effects of Fraud Crime on Suicide Among the Elderly in South Korea’s Aging Society

Abstract

Fraud has been steadily increasing in South Korea, with technological advancements in criminal techniques rendering older adults particularly vulnerable. Over the past 5 years, the number of reported fraud victims aged 60 and above has risen by 1.6 times. Given the difficulty of recovering assets lost to fraud, such crimes pose a significant threat to the social and economic security of older adults, with potential repercussions for both physical and mental health, including elevated suicide risk. This study investigated the contribution of fraud to suicide among the older adult population in South Korea, with particular attention to those living alone. Using open data from the National Police Agency (2018–2020) on fraud incidents, matched with demographic statistics from the National Statistical Office, we conducted hierarchical multiple regression analyses. The results revealed a significant positive relationship between fraud victimization and suicide rates among older adults. Moreover, fraud targeting older adults living alone exhibited a distinct and significant effect on suicide rates in this population. These findings highlight fraud as a critical public health issue that drives suicidal tendencies among older adults. We recommend strengthening older adults’ capacity for self-protection—particularly in electronic financial transactions—and establishing a private crime damage restoration network to provide comprehensive economic and psychological support for those affected.

Keywords

fraud aging society older adults older adults living alone suicide among older adults

Introduction

Technological advancement has contributed to a variety of major changes in economic environments. South Korea, which is among the most technologically advanced countries of the 21st century, has witnessed significant economic achievements in recent years (Jung, 2019). Technological advancement brings various benefits, including transaction convenience and security; for example, non-face-to-face technology facilitated individual transactions throughout the COVID-19 pandemic.

However, criminals also exploit these new technological abilities to commit crimes and cause harm. Increasingly advanced technology has allowed fraud to become more diverse and sophisticated (Korean Institute of Criminology, 2016). Moreover, fraud is now occurring with increased frequency: while approximately 270,000 instances of fraud were reported in 2018, accounting for 17% of all crimes, approximately 320,000 instances of fraud occurred in 2022, accounting for 22.6% of all crimes in South Korea (National Police Agency, 2023; 2020).

Fraud has resulted in a range of social problems in South Korea. It harms victims psychologically and mentally as well as economically (National Police Agency, 2021). Older adults, who lack knowledge and experience of rapidly changing technological tools, are naturally more vulnerable than younger generations to modern fraud modalities than other generations (Castelle, 2022). Moreover, criminals typically target individuals of higher economic status (Jang, 2009).

Because of the previous two factors, South Korea’s aging population has emerged as particularly problematic (K. W. Kim & Kim, 2020). According to Statistics Korea (2024), the number of people aged 65 or older in 2022 was approximately 9 million—17.5% of the population. According to the standards of the World Health Organization, when the proportion of people aged 65 or older in a given society exceeds 7%, 14%, and 21%, it is termed an ‘aging society’, ‘aged society’, and a ‘super-aged society’, respectively. It is anticipated that South Korea is expected to enter a ‘super-aged society’—in which more than one-fifth of the population is older adults—in 2026. As such, it leaves a mere 1 year for Korea to progress to a ‘super-aged society’ from now. An increase in the proportion of older adults in the population can contribute to various social problems, including the placement of a greater burden on medical care and welfare (Hwang, 2020).

From the perspectives of criminology and psychological well-being, crimes that target older adults, such as fraud, may be among the most pressing social issues in an aging society. The number of frauds targeting older adults increased from 22,483 in 2015 to 36,008 in 2020 (Korean National Police Agency, 2021). Given the proportionate growth of the older adult population, the risk of fraud targeting this generation is poised to become a major issue in the future. Furthermore, economic loss caused by fraud may impose excessive strain on older adults, thereby triggering suicide ideation (Saxby & Anil, 2012). Statistics suggest that South Korea has the highest rate of suicide in older adults among OECD countries at 46.6 per 100,000 people, surpassing the OECD average, which stands at 17.2 per 100,000 people (Ministry of Health and Welfare, 2021a).

Although the media often reports specific cases of older adult victims who commit suicide as a result of harm caused by fraud, these are not counted as official statistical data in South Korea (National Police Agency, 2021). Moreover, while instances of suicide precipitated by fraud among older adults have been studied qualitatively, researchers have largely neglected the relationship between fraud and suicide. Stress and depression have been found to have a positive relationship with suicide among older adults through various studies (Castelle, 2022; Duffield & Grabosky, 2001), and fraud causes extreme psychological stress in the older adults (Lapierre et al., 2011; Shang et al., 2022).

This study examines the effect of fraud on suicide among older adults. We matched fraud reports from 257 police stations in South Korea with suicide among older adults from 229 regions and conducted a hierarchical regression analysis. To account for variations across the 229 regions, the regression model included the proportion of older adult population and the percentage of older adults living alone as covariates. Since higher proportions of older adults are associated with increased suicide rates, we need to control the effects. As such, studies are necessary to provide evidence that fraud increases the risk of suicide among older adults after controlling for the proportion of the older population and the older individuals’ living conditions.

Fraud Against Older Adults

Some people mistakenly believe that fraud has minimal impact on victims’ lives (Button et al., 2014; Duffield & Grabosky, 2001; Fraud Advisory Panel, 2006). These arguments have been used to justify fraud as a minor offense. However, fraud can potentially destroy individual lives, interrupt economic growth, and exacerbate social distrust (Button et al., 2014). Even when its financial impact is minimal, fraud still has a devastating influence on its victims (Button et al., 2014; Office of Fair Trading, 2006; Pascoe et al., 2006; Spalek, 1999).

Older adults are more likely to be attractive targets for fraud for three key reasons. First, they are more likely to experience difficulties in judging situations (James et al., 2014). Cognitive ability naturally decreases with age and reduced cognitive ability negatively impacts decision-making processes, making fraud more difficult to prevent (Burnes et al., 2017; Scheibe et al., 2014). Second, older adults tend to judge situations more positively in a phenomenon called the ‘positivity effect’. The positivity effect is the tendency to favor positive or neutral information over negative information that individuals exhibit as they age (Carstensen et al., 2006; Mather & Carstensen, 2005). This effect has been identified as a key cause of older adults’ poor decision-making capacity (Shao et al., 2019)

Third, technological advances have also enhanced the older adult population’s attractiveness as a target for fraud (Carcach et al., 2001). For example, the increase in non-face-to-face economic activities as a result of the COVID-19 pandemic has likely facilitated the increase in fraud offenses (H. J. Kim, 2022). The number of banking tasks (e.g., account opening and loan requests) that can now be carried out via non-face-to-face means has more than tripled from 415 in 2017 to 1,463 in 2022 (ChosunBiz, 2022). While such situations have made the use of advanced technologies necessary, nevertheless, older adult customers may lack experience in using them, making them particularly vulnerable to modern fraud.

Suicide Among Older Adults

Given that suicide attempts are more lethal among older adults than among younger individuals (Levy et al., 2011; Minayo & Cavalcante, 2010), greater attention should be paid to suicide in the older adult population. Suicide risks and rates are higher in older adults than in younger people in most countries worldwide (Shah, 2007; Zhong et al., 2016). In South Korea, the suicide rate of older adults (43.8 per 100,000) is about 1.7 times higher than the average of those in their 20s and 30s (25.4 per 100,000) (Ministry of Health and Welfare, 2021a). Several studies have reviewed the various predictors of suicide among older adults, with several focusing on psychological disorders (e.g., anxiety and depression) that may increase suicide risk and are commonly caused by extremely stressful life events (Henriksson et al., 1995; Kulak-Bejda et al., 2021; Skoog, 2011; Waern et al., 2003; Yeh et al., 2020). Older adults who experience unexpected adverse events are likely to report psychological disorders and extreme stress (Lapierre et al., 2011). The death of a spouse, economic losses, and emotional illness are the main risk factors for suicide among older adults (Levy et al., 2011). In South Korea, the main factor contributing to suicide ideation in older adults is health problems at 23.7%, followed by economic difficulties at 23% (Statistics Korea, 2024). In other words, older adults who have been victimized by fraud are may be at greater risk of suicide owing to economic difficulties. Therefore, the economic harm caused by unexpected adverse events may increase the likelihood of suicide among older adults.

Older individuals’ vulnerability to suicide may be explained using Robert Agnew’s General Strain Theory (GST; Agnew, 1992). According to GST, three factors experienced by individuals during their lives might function as causes of self-destructive behaviors such as suicide. These three factors are the failure to achieve goals, the disappearance of positive stimuli, and the emergence of negative stimuli. Failure to achieve goals occurs when individuals fail to attain goals to which they ascribe positive value. For example, failure to achieve economic success, social status improvement, or academic accomplishments can induce stress. Disappearance of positive stimuli is the removal of stimuli that individuals positively value such as unemployment and divorce. The emergence of negative stimuli caused by unintended events including domestic violence or economic hardship, could trigger stress. Should such sources of strain intensify, the affected individuals may consider the self-destructive behaviors (e.g., self-torture or suicide) as a resolution to the stress (Agnew, 1992). While GST was originally developed to explain criminal behavior, it can also be applied to understand analogous behaviors, including substance abuse and suicide (Agnew, 1992; Stack & Wasserman, 2007).

We may assume that the suspension of income constitutes the disappearance of positive stimuli. Many older adults without jobs derive an income only from their savings or basic pensions. More than half of South Korea’s older adult population (49.5%) are out of work. The suspension of income diminishes their economic power, which can further increase the burden of fixed costs and lower living standards. Economic loss caused by fraud may be classified as the emergence of negative stimuli, causing particularly serious harm to the daily lives of older adults who have lost their economic agency. Statistics show that economic difficulties are among the main reasons that older adults contemplate suicide (23.0%) (Ministry of Health and Welfare 2021a). When these stimuli act in complex ways, they may be accompanied by extreme stress, inducing suicidal tendencies.

Older Adults Suicide in South Korea

On a global level, the rate of suicide among the older adult population is the highest across all age groups (Lapierre et al., 2011). According to 2019 statistics, the number of individuals aged in their 60s who committed suicide was 20 for men and 27 for women per 100,000, respectively (World Health Organization, 2023), and the number of individuals committing suicide in their 70s was found to be 27 in men and 30 in women per 100,000, respectively. The severity of the problem of suicide among older adults relative to other age groups is clear. For example, it is twice that of individuals aged in their 50s and 10 times that of those in their teens and 20s. Considering that the number of seniors and their proportion in the population is set to increase worldwide in the coming decades (Christensen et al., 2009), the absolute number of suicides among older adults is expected to increase accordingly. Population aging has become a particularly severe problem in South Korea, which is already entering an aged society in which the population of older adults exceeds 14% of the entire population (Statistics Korea, 2022). Considering the severity of both fraud and population aging in the South Korean context, it is expected that the suicide among the older adult population will increase because of social problems.

Suicide is already a serious social problem in South Korea, ranked fifth among the causes of death (Statistics Korea, 2022). The suicide rate in South Korea is 2.2 times higher than the average OECD member suicide rate. Despite a decline in the country’s overall suicide rate between 2011 and 2021, the country still maintains the highest rank among OECD countries. During the same period (2011–2021), the suicide rate among older adults also witnessed a decrease. Nonetheless, the suicide rate among older adults in South Korea is approximately three times higher than the OECD average (Ministry of Health and Welfare, 2021b).

According to Statistics Korea, older adults who live alone contemplate suicide more than twice as much as those living in couples (Statistics Korea, 2021). Among these, 21% of those living alone who contemplated suicide cited economic difficulties as the cause. Considering the increasing proportion of older adults living alone, we may predict that suicide will increase among the older adult population as a result of economic disorder or social isolation.

Methods

Research Model

This study verified the effects of fraud on suicide among older adults in South Korea while controlling for the older adult population. We integrated fraud reports from 257 police stations in South Korea with suicide among older adults from 229 regions. To address regional variations, we included older adult population variables as covariates in the research model. We performed two hierarchical regression models, distinguishing between the broader the older adult population and those living alone. The specific research hypotheses (see Figure 1) are outlined below.

Hypothesis 1: Fraud will account for additional variance in suicide among older adults while controlling for the older adult population.

Hypothesis 2: Fraud will account for additional variance in suicide among older adults while controlling for the older adult living alone.

Figure 1.

Hierarchical regression models of suicide among older adults, older adult population (older adult living alone), and fraud.

Data

The National Police Agency provided fraud data encompassing various crimes stipulated in the ‘Criminal Act’ and the ‘Act on the Aggravated Punishment of Specific Economic Crimes’, reported by 257 police stations nationwide from 2019 to 2020. For demographic variables, we collected older adult population data (including from older adults living alone) according to region from the census and information on suicide among older adults from cause-of-death statistics (Statistics Korea, 2022). Cause-of-death statistics encompass age, residential location, and cause of death for individuals deceased within the current year. Given that our focus is on suicide among individuals aged 65 and above, we filtered and restructured this specific demographic by region. To control for the impact of regional population sizes, we computed fraud rates per 10,000 population and demographic variables as rates per 100,000 population.

Finally, we streamlined the dataset to 221 units for analysis by integrating fraud data from 257 police stations and demographic variables from 229 regions. For cases in which multiple police stations operate within a single region, the number of reported instances of fraud from these stations was aggregated. For instance, in Seongbuk-gu, Seoul, which encompasses two police stations (Seongbuk Police Station and Jongam Police Station), the total number of frauds was derived by summing the reported cases from both police stations. Conversely, when a single police station governs multiple regions, the older adult populations from those respective areas are combined. For instance, Mokpo Police Station oversees Mokpo-si and Sinan-gun, and in such cases, the older adult populations of those regions were consolidated.

Table 1 presents the mean and standard deviation of variables of interest. In 2019, the mean number of suicides among older adults was 9.77 (SD = 6.32), declining slightly to 9.16 (SD = 6.12) in the subsequent year. Marginal increase was observed in the older adult population from 2018 (M = 2,004.68, SD = 798.62) to 2019 (M = 2,092.76, SD = 815.01). Similarly, the prevalence of older adults living alone showed an uptick in 2019 (M = 457.80, SD = 251.28) compared to 2018 (M = 438.94, SD = 250.03). Meanwhile, the average number of frauds rose from 49.95 in 2018 to 55.38 the following year.

Table 1.

Descriptive Statistics for Suicide Among Older Adults, Older Adult Population, Older Adult Living Alone, and Fraud (2018–2020).

(N = 221)
Year	Suicide among older adults		Older adult population		Older adult living alone		Fraud
Year	M	SD	M	SD	M	SD	M	SD
2018	9.11	5.30	2,004.68	798.62	438.94	250.03	49.95	31.08
2019	9.77	6.32	2,092.79	815.01	457.80	251.25	55.83	32.47
2020	9.16	6.12	2,205.80	842.23	489.73	259.25	58.34	34.54

Note. N means 221 cities, counties, and districts selected in the study; suicide among older adults is measured as occurrences per 100,000 people, older adult population and older adult living alone are measured as the frequency per 10,000 people; Fraud is measured as occurrences per 10,000 people.

Data Analytic Plan

Data analyses were conducted using IBM SPSS statistics (Version 25; IBM Corp., 2017). First, zero-order bivariate correlations were estimated among the study variables to identify potential covariates for the subsequent analyses. Second, we performed two hierarchical regression models to evaluate the two relationships between fraud and suicide among older adults in the preceding year, controlling for each of two older adult variables (i.e., the older adult population and older adults living alone). Specifically, the first hierarchical multiple regression model subsequently entered the predictors in the following models: (1) Model 1, older adult population; (2) Model 2, fraud. For the second hierarchical multiple regression analysis, we used older adults living alone rather than the older adult population as a predictor variable. Given that the impact of fraud on suicide does not occur on the same occasion, it is crucial to consider the temporal interval between the two variables. Consequently, we examined the longitudinal relationship between the predictor variable (both the older adult population, older adults living alone, and fraud) and the criterion variable (suicide among older adults) using data from the subsequent year. Furthermore, we analyzed matching older adults variables and fraud in 2018 with suicide among older adults in 2019 and older adults variables and fraud in 2019 with suicide among older adults in 2020.

Results

Table 2 presents the Pearson correlations among suicide among older adults, older adult population, older adults living alone, and fraud. In 2019, suicide among older adults was positively correlated with both the older adult population (r = .58, p < .001) and older adults living alone (r = .56, p < .001) from the preceding year. Additionally, fraud was negatively related to both the older adult population (r = −.23, p = .001) and older adults living alone (r = −.23, p = .001). Similarly, in 2020, suicide among older adults showed a positive correlation with the older adult population (r = .55, p < .001), older adults living alone, and fraud in 2019 (r = .52, p < .001). Fraud was negatively correlated with both the older adult population (r = −.23, p = .001) and older adults living alone (r = −.23, p = .001).

Table 2.

Pearson Correlations Among Suicide Among Older Adults, Older Adult Population, Older Adult Living Alone, and Fraud (2018–2020).

No.	Variables	1	2	3	4	5	6	7	8
1	Suicide among older adults 2019	1
2	Suicide among older adults 2020	.66***	1
3	Older adult population 2018	.58***	.55***	1
4	Older adult population 2019	.58***	.55***	1.00***	1
5	Older adult living alone 2018	.56***	.51***	.98***	.98***	1
6	Older adult living alone 2019	.57***	.52***	.98***	.98***	1.00***	1
7	Fraud 2018	.04	−.01	−.23**	−.22**	−.23**	−.23**	1
8	Fraud 2019	.13	.07	−.23**	−.23**	−.24***	−.23**	.92***	1

p < .05. **p < .01. ***p < .001.

The Older Adult Population and Fraud

Hierarchical regression was performed to predict suicide among older adults in 2019 based on the preceding year’s older adult population and fraud. These results are presented in Table 3. The older adult population was significantly associated with suicide among older adults in 2019 (β = .62, p < .001), as did fraud (β = .18, p = .001). Model 1 (Older adult population) accounted for 33% of the variance (R² = .33). When Model 2 (fraud) was added, a significant change was observed in R² (ΔR² = .03, F-change (1, 217) = 9.82, p < .001). The final model accounted for a total variance of 36% (R² = .36).

Table 3.

Hierarchical Regression Models Predicting Suicide Among Older Adults in 2019 and 2020 From the Previous Year’s Older Adult Population and Fraud.

	Suicide among older adults in 2019				Suicide among older adults in 2020
Predictors	R²	ΔR²	β	t	R²	ΔR²	β	t
Model 1
Older adult population	.33		.58***	10.44	.30		.55***	9.65
Model 2
Older adult population	.36	.03**	.62***	11.12	.34	.04***	.60***	10.50
Fraud			.18**	3.24			.21**	3.69

Note. All predictors refer to data from 1 year before the reference variable; Suicides among older adults are measured as occurrences per 100,000 people, older adult population and older adult living alone are measured as the frequency per 10,000 people, and fraud is measured as occurrences per 10,000 people.

p < .05. **p < .01. ***p < .001.

Another hierarchical regression analysis from the following year indicated that the older adult population (β = .59, p < .001) and fraud (β = .62, p = .002) were associated with increased suicide among older adults in 2020. In Model 1, the older adult population explained 30% of the variance (R² = .30). Upon including Model 2 (fraud), a significant change was observed in R² (ΔR² = .04, F-change (1, 217) = 13.61, p < .001), contributing to total variance of 34% in the final model (R² = .34). Consequently, these results supported the first hypothesis that, while controlling for older adult population, fraud would account for additional variance in suicide among older adults in the subsequent year.

Older Adults Living Alone and Fraud

We also examined the association between suicide among older adults, older adults living alone, and fraud. First, we performed the hierarchical regression to predict suicide among older adults in 2019 based on the preceding year’s older adults living alone and fraud. The results are presented in Table 4. Both older adults living alone (β = .60, p < .001) and fraud (β = .18, p = .002) were significantly associated with increased suicide among older adults. Initially, Model 1 (older adults living alone) explained 31% of the variance (R² = .31). The introduction of Model 2 (fraud) led to the emergence of a significant change in R² (ΔR² = .03, F-change (1, 217) = 9.82, p < .001), contributing to a total variance of 34% in the final model (R² = .34).

Table 4.

Hierarchical Regression Models Predicting Suicide Among Older Adults in 2019 and 2020 From the Previous Years Older Adult Living Alone and Fraud.

	Suicide among older adults in 2019				Suicide among older adults in 2020
Predictors	R ²	ΔR²	β	t	R ²	ΔR²	β	t
Model 1
Older adult living alone	.31		.56***	9.88	.27		.52***	8.87
Model 2
Older adult living alone	.34	.03***	.60***	10.52	.30	.03**	.56***	9.65
Fraud			.18**	3.13			.20**	3.49

Note. All predictors refer to data from 1 year before the reference variable. Suicides among older adults are measured as occurrences per 100,000 people, and older adult living alone are measured as frequency per 10,000 people. Fraud is measured as occurrences per 10,000 people.

p < .05. **p < .01. ***p < .001.

Similarly, for the subsequent year, both older adults living alone (β = .56, p < .001) and fraud (β = .20, p = .001) were significantly associated with increased suicide among older adults. Model 1 (older adults living alone) accounted for 27% of the variance (R² = .27). Upon introducing Model 2 (fraud), there was a significant change in R² (ΔR² = .03, F-change (1, 217) = 12.19, p = .001). The total variance accounted for by the final model was 30% (R² = .30). These results supported the second hypothesis that fraud would explain the additional variance of suicide among older adults when controlling for older adults living alone.

Discussion

This study examined the effect of fraud on suicide rates among older adults in South Korea. Using hierarchical regression analysis, we examined the effect of fraud on the subsequent year’s suicide rate among older adults, controlling for both the proportion of older adults relative to the total regional population and the proportion living alone. The results indicate that increases in fraud are significantly associated with subsequent rises in suicides among older adults, underscoring fraud as not only an economic crime but also a critical public health concern. The findings reinforce the established link between the economic harm caused by fraud and heightened suicide risk among older adults. Older adults are particularly vulnerable to fraud due to age-related declines in cognitive capacity for financial decision-making (DeLiema, 2018; Spreng et al., 2017) and limited familiarity with emerging technologies (Alwanain, 2020; Shang et al., 2022). From the perspective of Routine Activity Theory, these vulnerabilities position older adults as ‘suitable targets’ for offenders, as their accessibility and limited protective capacities create opportunities for victimization.

Beyond financial losses, fraud inflicts substantial psychological distress, which can precipitate self-destructive behaviors. GST offers a valuable lens for interpreting these findings. GST posits that extreme and unexpected strains impair decision-making and can lead to maladaptive coping, including suicide (Heydari et al., 2013; Zhang, 2019). Fraud constitutes a severe life event, inflicting both economic and psychological harm. Its impact is especially pronounced among older adults living alone, who have limited access to reliable social support networks. The COVID-19 pandemic intensified these challenges by accelerating economic and technological changes—such as the widespread shift to non-face-to-face financial transactions—which have increased older adults’ exposure to fraud. The pandemic also deepened social isolation and economic hardship, further elevating suicide risk (Druss, 2020; Zalsman et al., 2020).

In South Korea, the proportion of older adults living alone rose from 18.5% in 2015 to 22.1% in 2024 (Statistics Korea, 2024) and currently accounts for over one-fifth of the older population. As pandemic-driven structural changes have persisted in the post-COVID period, the vulnerability of older adults, particularly those living alone—remains high (Gaddis et al., 2024). These trends point to an urgent need for institutional measures to prevent fraud and to mitigate its psychological and economic consequences for the older adult population, particularly those living alone.

Currently, financial institutions operate Fraud Detection Systems (FDS) to identify irregular or potentially fraudulent activities, but these systems have not yet been fully institutionalized as regulatory measures specifically aimed at protecting older adults or other vulnerable groups. Consequently, intervention often relies on front-line bank staff detecting suspicious cases in person and taking immediate action, such as pausing transactions or requesting further verification. However, relying solely on general FDS operations may be insufficient to safeguard this population. Abnormal account activities involving older adults should be subject to proactive, targeted monitoring with potential fraud in mind, enabling timely intervention before substantial harm occurs.

Fraud inflicts not only substantial economic loss but also considerable psychological harm on victims. Globally, numerous organizations provide specialized services to address these impacts. For example, the ReST program, operated by the AARP Fraud Watch Network VOA in the United States, focuses on restoring trust and repairing the emotional damage caused by fraud (AARP, n.d.), while the National Centre for Victims of Crime (NCVC) offers targeted assistance to victims of identity theft and cybercrime. In contrast, South Korea lacks dedicated organizations or facilities that provide specialized care for older adults who have been victimized by fraud. Beyond maintaining a judicial system that prevents fraud, there is a pressing need to establish mechanisms that help victims regain psychological stability and rebuild their basic economic security. Currently in South Korea, the ‘Voice Phishing Zero’ organization offers psychological support and living expense assistance to victims of voice phishing and related fraud schemes. However, the capacity of a single organization is insufficient to meet the diverse needs of victims. Moreover, the program serves all age groups and delivers training primarily at the institutional level, limiting older adults’ access to individualized assistance. Accordingly, the scope of such initiatives should be broadened to ensure that older adults have direct access to comprehensive support that encompasses psychological care, livelihood assistance, and financial aid.

The South Korean government implements its Basic Suicide Prevention Plan every 5 years, which includes psychological support for high-risk groups (Ministry of Health and Welfare, 2025). Given the severe psychological harm and social isolation experienced by older adults who have been victimized by fraud, they should be formally recognized as a priority within these high-risk categories. This recognition underscores the need for accessible, in-person psychological support tailored to older adult fraud victims. To close this gap, the government should institutionalize fraud-victim–specific outreach programs that combine psychological counseling with financial recovery assistance. Such programs could involve proactive identification of victims through coordination between police and financial institutions, establishment of in-person counseling hubs within community welfare facilities or senior centers, deployment of mobile response teams to provide home visits for those with mobility limitations, integration of psychological care with legal and financial counseling, and follow-up monitoring to ensure sustained recovery and prevent recurrent suicidal ideation.

In parallel with these intervention measures, preventive strategies must also be strengthened. Although certain fraud modalities are already well known, older adults remain particularly vulnerable to intelligence crimes due to limited awareness of recent developments. In response, some local governments have introduced door-to-door education programs to prevent fraud among older adults (Lee, 2023). In collaboration with financial institutions, they also provide training aimed at enhancing financial security and digital competence, covering both emerging fraud techniques and guidelines for safe financial practices. Expanding and enriching these educational initiatives is critical to reducing fraud risk, and the central government should adopt and standardize such programs nationwide to raise awareness and reinforce prevention efforts.

This study has several limitations. First, the measure of ‘fraud’ used in our analysis was based on the total number of fraud offenses across all age groups, rather than offenses specifically targeting older adults. A more accurate assessment of fraud’s impact on suicide among older adults would require data on fraud incidents perpetrated against this demographic. However, such disaggregated statistics at the city–county level were not available from the National Police Agency. Despite this limitation, our findings revealed a significant correlation between overall fraud incidence and suicide rates among older adults, suggesting that fraud offenses specifically targeting older adults would likely demonstrate a similar, if not stronger, association. Using available official statistics, we confirmed that fraud constitutes a risk factor for suicide in later life. Nevertheless, the absence of age-specific fraud data constrains the precision of our conclusions. The establishment of detailed, age-disaggregated official statistics on fraud and suicide among older adults would provide a stronger empirical foundation for systematic academic research on this critical public health and criminological issue.

Footnotes

ORCID iDs

Seung Hyun Kim

Eun Seo Park

Seong Ki Lee

Young Il Cho

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A3A2A02089039).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

AARP. (n.d.). AARP fraud watch network. https://www.aarp.org/fraudupport

Agnew

(1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1), 47–88.

Alwanain

M. I.

(2020). Phishing awareness and elderly users in social media. International Journal of Computer Science and Network Security, 20(9), 114–119. https://doi.org/10.22937/IJCSNS.2020.20.09.14

Burnes

Henderson

C. R.

Jr. Sheppard

Zhao

Pillemer

Lachs

M. S.

(2017). Prevalence of financial fraud and scams among older adults in the United States: A systematic review and meta-analysis. American Journal of Public Health, 107(8), e13–e21. https://doi.org/10.2105/AJPH.2017.303821

Button

Lewis

Tapley

(2014). Not a victimless crime: The impact of fraud on individual victims and their families. Security Journal, 27, 36–54. https://doi.org/10.1057/sj.2012.11

Carcach

Graycar

Muscat

(2001). The victimisation of older Australians (Vol. 212). Australian Institute of Criminology.

Carstensen

L. L.

Mikels

J. A.

Mather

(2006). Aging and the intersection of cognition, motivation, and emotion. In Birren

J. E.

Schaie

K. W.

(Eds.), Handbook of the psychology of aging (6th ed., pp. 343–362). Academic Press. https://doi.org/10.1016/B978-012101264-9/50018-5

Castelle

(2022). Fraud in the elderly community [Capstone projects and master’s theses, California State University, Monterey Bay]. https://digitalcommons.csumb.edu/caps_thes_all/1293

ChosunBiz. (2022, December 11). FSS: Illegal private loan damages have doubled over the past three years [in Korean]. https://biz.chosun.com/stock/finance/2022/12/11/2G5S7NFVFBFWNDFMOLVENUSTJE/

10.

Christensen

Doblhammer

Rau

Vaupel

J. W.

(2009). Aging populations: The challenges ahead. The Lancet, 374(9696), 1196–1208. https://doi.org/10.1016/S0140-6736(09)61460-4

11.

DeLiema

(2018). Elder fraud and financial exploitation: Application of routine activity theory. The Gerontologist, 58(4), 706–718. https://doi.org/10.1093/geront/gnw258

12.

Druss

B. G.

(2020). Addressing the COVID-19 pandemic in populations with serious mental illness. JAMA Psychiatry, 77(9), 891–892. https://doi.org/10.1001/jamapsychiatry.2020.0894

13.

Duffield

G. M.

Grabosky

P. N.

(2001). The psychology of fraud (Vol. 199). Australian Institute of Criminology.

14.

Fraud Advisory Panel. (2006). Victims of fraud.

15.

Gaddis

Woollen

K. C.

Johnson

L. J.

Flaherty

T. M.

Byrnes

J. F.

(2024). A structural vulnerability approach to older adult suicides: Trends and potential impacts of the COVID-19 pandemic in Clark County, NV (2017–2021). Forensic Science International: Synergy, 8, Article 100454. https://doi.org/10.1016/j.fsisyn.2024.100454

16.

Henriksson

M. M.

Marttunen

M. J.

Isometsä

E. T.

Heikkinen

M. E.

Aro

H. M.

Kuoppasalmi

K. I.

Lönnqvist

J. K.

(1995). Mental disorders in elderly suicide. International Psychogeriatrics, 7(2), 275–286. https://doi.org/10.1017/S1041610295002031

17.

Heydari

Nouri

Ebrahimi

(2013). Strain theory and suicide ideation. Journal of Basic and Applied Scientific Research, 3, 475–480.

18.

Hwang

(2020). Welfare of the aged and community care in an aging society. Journal of Public Society, 10(2), 5–28.

19.

IBM Corp. (2017). IBM SPSS statistics for windows (version 27.0) [Computer software].

20.

James

B. D.

Boyle

P. A.

Bennett

D. A.

(2014). Correlates of susceptibility to scams in older adults without dementia. Journal of Elder Abuse & Neglect, 26(2), 107–122. https://doi.org/10.1080/08946566.2013.821809

21.

Jang

J. O.

(2009). No-in-beom-joe-wa beom-joe-pi-hae-e dae-han sil-tae-yeon-gu [Elderly crime and its victimization]. Korean Criminological Review, 77(1), 215–255.

22.

Jung

(2019). The fourth industrial revolution, knowledge production and higher education in South Korea. Journal of Higher Education Policy and Management, 42(2), 134–156. https://doi.org/10.1080/1360080X.2019.1660047

23.

Kim

H. J.

(2022). Jeon-hwa-geum-yung-sa-gi su-sa jeong-bo ja-dong chu-chul yeon-gu: ja-yeon-eo-cheo-li dib-leo-ning mo-del-eul jung-sim-eu-lo [An implementation of natural language processing and deep learning in phone scam investigation]. Journal of Korean Criminological Association, 16(1), 123–141.

24.

Kim

K. W.

Kim

O. S.

(2020). Super aging in South Korea unstoppable but mitigatable: A sub-national scale population projection for best policy planning. Spatial Demography, 8(2), 155–173. https://doi.org/10.1007/s40980-020-00061-8

25.

Korean Institute of Criminology. (2016). Korean crime victim survey in 2014.

26.

Kulak-Bejda

Bejda

Waszkiewicz

(2021). Mental disorders, cognitive impairment and the risk of suicide in older adults. Frontiers in Psychiatry, 12, Article 695286. https://doi.org/10.3389/fpsyt.2021.695286

27.

Lapierre

Erlangsen

Waern

De Leo

Oyama

Scocco

Gallo

Szanto

Conwell

Draper

Quinnett

(2011). A systematic review of elderly suicide prevention programs. Crisis, 32(2), 88–98. https://doi.org/10.1027/0227-5910/a000076

28.

Lee

S. K.

(2023). Legal improvement measure on preventing elder financial exploitation—Focused on reporting and withholding system of financial institution. Gachon Law Review, 16(1), 69–106.

29.

Levy

T. B.

Barak

Sigler

Aizenberg

(2011). Suicide attempts and burden of physical illness among depressed elderly inpatients. Archives of Gerontology and Geriatrics, 52(1), 115–117. https://doi.org/10.1016/j.archger.2010.02.012

30.

Mather

Carstensen

L. L.

(2005). Aging and motivated cognition: The positivity effect in attention and memory. Trends in Cognitive Sciences, 9(10), 496–502. https://doi.org/10.1016/j.tics.2005.08.005

31.

Minayo

M. C. D. S.

Cavalcante

F. G.

(2010). Suicide in elderly people: A literature review. Revista de Saude Publica, 44, 750–757. https://doi.org/10.1590/S0034-89102010000400020

32.

Ministry of Health and Welfare. (2021a). White paper on suicide prevention.

33.

Ministry of Health and Welfare. (2021b). White book 2020.

34.

Ministry of Health and Welfare. (2025). White book 2024.

35.

National Police Agency. (2021). 2020 Fraud occurrence and increase cause analysis and police response research.

36.

National Police Agency. (2023). Korean Police Crime Statistics in 2023.

37.

National Police Agency. (2020). Korean Police Crime Statistics in 2020.

38.

Office of Fair Trading. (2006). Fraud review: Final report – a consultation response. Office of Fair Trading.

39.

Pascoe

Owen

Keats

Gill

(2006). Identity fraud: What about the victim. CIFAS.

40.

Saxby

Anil

(2012). Financial loss and suicide. The Malaysian Journal of Medical Sciences: MJMS, 19(2), 74–76.

41.

Scheibe

Notthoff

Menkin

Ross

Shadel

Deevy

Carstensen

L. L.

(2014). Forewarning reduces fraud susceptibility in vulnerable consumers. Basic and Applied Social Psychology, 36(3), 272–279. https://doi.org/10.1080/01973533.2014.903844

42.

Shah

(2007). The relationship between suicide rates and age: An analysis of multinational data from the World Health Organization. International Psychogeriatrics, 19(6), 1141–1152. https://doi.org/10.1017/S1041610207005285

43.

Shang

Jiang

Chi

(2022). The psychology of the internet fraud victimization of older adults: A systematic review. Frontiers in Psychology, 13, Article 912242. https://doi.org/10.3389/fpsyg.2022.912242

44.

Shao

Zhang

Ren

Lin

(2019). Why are older adults victims of fraud? Current knowledge and prospects regarding older adults’ vulnerability to fraud. Journal of Elder Abuse & Neglect, 31(3), 225–243. https://doi.org/10.1080/08946566.2019.1625842

45.

Skoog

(2011). Psychiatric disorders in the elderly. The Canadian Journal of Psychiatry, 56(7), 387–397. https://doi.org/10.1177/070674371105600702

46.

Spalek

(1999). Exploring the impact of financial crime: A study looking into the effects of the Maxwell scandal upon the Maxwell pensioners. International Review of Victimology, 6(3), 213–230. https://doi.org/10.1177/026975809900600304

47.

Spreng

R. N.

Cassidy

B. N.

Darboh

B. S.

DuPre

Lockrow

A. W.

Setton

Turner

G. R.

(2017). Financial exploitation is associated with structural and functional brain differences in healthy older adults. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, 72(10), 1365–1368. https://doi.org/10.1093/gerona/glx051

48.

Stack

Wasserman

(2007). Economic strain and suicide risk: A qualitative analysis. Suicide and Life-Threatening Behavior, 37(1), 103–112. https://doi.org/10.1521/suli.2007.37.1.103

49.

Statistics Korea. (2022). Cause-of-death statistics.

50.

Statistics Korea. (2024). Ratio of elderly population. https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1YL20631&conn_path=I2

51.

Waern

Rubenowitz

Wilhelmson

(2003). Predictors of in the old elderly. Gerontology, 49(5), 328–334. https://doi.org/10.1159/000071715

52.

World Health Organization. (2023). Preventing suicide: A resource for media professionals, 2023 update.

53.

Yeh

S. T.

Y. Y.

S. C.

(2020). Association of psychiatric and physical illnesses with suicide in older adults in Taiwan. Journal of Affective Disorders, 264, 425–429. https://doi.org/10.1016/j.jad.2019.11.070

54.

Zalsman

Stanley

Szanto

Clarke

D. E.

Carli

Mehlum

(2020). Suicide in the time of COVID-19: Review and recommendations. Archives of Suicide Research, 24(4), 477–482. https://doi.org/10.1080/13811118.2020.1830242

55.

Zhang

(2019). The strain theory of suicide. Journal of Pacific Rim Psychology, 13, e27. https://doi.org/10.1017/prp.2019.19

56.

Zhong

B. L.

Chiu

H. F.

Conwell

(2016). Rates and characteristics of elderly suicide in China, 2013–14. Journal of Affective Disorders, 206, 273–279. https://doi.org/10.1016/j.jad.2016.09.003