Abstract
Background and Objectives
Elder financial exploitation, committed by individuals in positions of trust, and elder fraud, committed by predatory strangers, are two forms of financial victimization that target vulnerable older adults. This study analyzes differences between fraud and financial exploitation victims and tests routine activity theory as a contextual model for victimization. Routine activity theory predicts that criminal opportunities arise when a motivated offender and suitable target meet in the absence of capable guardians.
Research Design and Methods
Fifty-three financial exploitation and fraud cases were sampled from an elder abuse forensic center. Data include law enforcement and caseworker investigation reports, victim medical records, perpetrator demographic information, and forensic assessments of victim health and cognitive functioning.
Results
Fraud and financial exploitation victims performed poorly on tests of cognitive functioning and financial decision making administered by a forensic neuropsychologist following the allegations. Based on retrospective record review, there were few significant differences in physical health and cognitive functioning at the time victims’ assets were taken, although their social contexts were different. Significantly more fraud victims were childless compared with financial exploitation victims. Fraud perpetrators took advantage of elders when they had no trustworthy friends or relatives to safeguard their assets.
Discussion and Implications
Findings support an adapted routine activity theory as a contextual model for financial victimization. Fraud most often occurred when a vulnerable elder was solicited by a financial predator in the absence of capable guardians. Prevention efforts should focus on reducing social isolation to enhance protection.
Keywords: Victimization, Elder abuse forensic center, Adult protective services, Forensic neuropsychologist, Retrospective review
Elder financial exploitation and financial fraud targeting older adults are two forms of financial victimization often confounded in the elder abuse literature (Jackson, 2015). Financial fraud is “Intentionally deceiving a victim by misrepresenting, concealing, or omitting facts about promised goods, services, or other benefits and consequences that are nonexistent, unnecessary, never intended to be provided, or deliberately distorted for the purpose of monetary gain” (Beals, DeLiema, & Deevy, 2015 adapted from Titus, Heinzelmann, & Boyle, 1995). Fraud schemes are diversely tailored to lure people from different socioeconomic and demographic backgrounds, and seniors are just one targeted group. Older adults may be disproportionately solicited by fraudsters (Kieffer & Mottola, 2016) because they are at or near the peak of asset accumulation or because perpetrators assume that cognitive impairment and isolating life events such as retirement, widowhood, and disability make them more susceptible (Lee & Soberon-Ferrer, 1997).
Criminals who prey on elders may masquerade as care providers, estate planners, or other professionals to get access to older targets. Some fraudsters have frequent interactions with a specific person, for example, romance scams, although they often cast a wide net using mass marketing tactics to identify vulnerable people first (Holtfreter, 2014). Although anyone can be a victim of fraud regardless of age, this article focuses on fraud victims 65 and older where there is face-to-face interaction between the victim and the perpetrator(s).
The Centers for Disease Control (CDC) define financial exploitation as, “The illegal, unauthorized, or improper use of an older individual’s resources by a caregiver or other person in a trusting relationship, for the benefit of someone other than the older individual” (Hall, Karch, & Crosby, 2016). Unlike predatory fraudsters, financial exploiters are typically relatives, longtime friends, neighbors, and caregivers (Choi, Kulick, & Mayer, 1999) who live with or nearby their victims (Lachs & Pillemer, 2004; Schafer & Koltai, 2015). Whereas fraud perpetrators must convince their targets to willingly cooperate with the proposed exchange (Holtfreter, Reisig, & Pratt, 2008), many financial exploiters already have access to the elders’ accounts or the legal authority to act on their behalf (Payne, 2002). Thus, they can pilfer assets without the elders’ awareness or explicit agreement. These offenders may rationalize taking the elder’s money or property as compensation for providing care or feel entitled to the elder’s assets by virtue of being a relative. Issues such as mental illness or substance abuse can also contribute to financial dependence on an older family member (Conrad, Liu, & Iris, 2016; Pillemer, Burnes, Riffin, & Lachs, 2016). Unlike fraud, financial exploitation does not require that the perpetrator have an intent to deceive the elder, although exploiters sometimes make false promises, such as when a grandchild vows to care for his aging grandparents in exchange for inheriting their home.
Although some specific tactics overlap, another key difference is that fraud perpetrators must cultivate an illusion of trust and legitimacy to convince their targets to comply (Beals, DeLiema, et al., 2015), whereas by definition, financial exploiters already occupy positions of trust (Hall et al., 2016). As such, financial exploiters tend to be opportunistic; taking advantage of a preexisting relationship with an elder from within their social network (Bonnie & Wallace, 2003), and fraud perpetrators actively seek out potential targets. Thus, although these crimes share similar features, there are key distinctions that affect best practices for prevention, detection, and response.
Routine Activity Theory as a Model for Elder Financial Victimization
Most theories of elder abuse focus on victim and/or perpetrator risk factors. Criminological theories add an additional perspective by focusing on the situational factors affecting risk of victimization. According to Cohen and Felson’s (1979) routine activity theory, criminal acts require the convergence of three factors: (a) a motivated offender, (b) a suitable target, and (c) the absence of capable guardians. Rather than focusing on the demographic characteristics of victims and perpetrators, such as age and gender, the theory examines how day-to-day behaviors, activities, and situations increase opportunities for motivated offenders to come into contact with susceptible targets (Pratt, Holtfreter, & Reisig, 2010).
Although routine activity theory was developed as a model for street crime, it offers a promising conceptual model for financial crimes as well (Holtfreter et al., 2008). Reisig and Holtfreter (2013) tested the theory in remote purchasing fraud—making purchases over the phone, by mail, and online—among adults 60 and older. These technological advances in the consumer marketplace have created new opportunities for fraudsters to reach thousands of targets in poorly supervised payment settings (Holtfreter & Meyers, 2015). As hypothesized, the researchers found that older adults who engage in remote purchasing activities face greater risk of being targeted by fraud. Having low self-control also increased the risk of fraud victimization once targets were solicited in remote purchasing environments (Holtfreter et al., 2008; Reisig & Holtfreter, 2013).
Figure 1 presents an adaptation of routine activity theory applied to elder financial victimization. As depicted in the model, aging adults may be most vulnerable to fraud during the gradual period of cognitive and physical decline when deficits are hardest to recognize by capable guardians, such as family members, friends, or medical professionals. Although not all people develop dementia as they age, those who do often exhibit subtle signs of diminished problem solving and difficulties with complex transactions in the early stages of the disease despite normal functioning in other areas, such as language and semantic knowledge, and need no assistance with personal care (Triebel & Marson, 2012). These adults may even downplay their cognitive deficits in order to protect their financial independence. By the time capable guardians recognize the elder’s impairments, financial predators (motivated offenders) may have already succeeded in committing fraud. The resulting financial loss may be the event that causes others to step in.
Figure 1.
Theoretical model of elder financial victimization, adapted from routine activity theory (Cohen & Felson, 1979). Other personal vulnerability factors, such as wealth, lack of awareness of scams and persuasion, and negative life events may increase susceptibility to financial fraud but are not depicted in the model because these factors are not specific to older adults.
At the later stages of impairment, the model predicts that elders are more vulnerable to financial exploitation by “trusted others.” These are typically relatives or close friends or neighbors who provide care, including tasks such as paying bills or buying groceries. Although these trusted others may block fraud solicitations from outsiders, they use their position of influence to take advantage of the elder. The adapted routine activity theory focuses on the timing and context in which vulnerable older adults come into contact with motivated offenders, who may be strangers or people within their social networks.
The Present Study
A limitation of research on elder financial exploitation and fraud is that data are rarely collected on the social context of victimization, including how often the older person interacted with the perpetrator and the nature and length of their relationship. Researchers also face the difficult challenge of verifying how much money was stolen, and how, exactly, assets were misappropriated. Furthermore, cognitively impaired seniors are typically excluded from surveys and seniors tend to underreport fraud relative to other age groups (Beals, Carr, Mottola, Deevy, & Carstensen, 2015). For example, AARP found that only 37% of victims aged 55 and older acknowledged they were defrauded compared with 56% of victims younger than 55 years (Pak & Shadel, 2011).
Because of these limitations, we have only scratched the surface in our understanding of how risk factors and settings for elder fraud committed by strangers differ from financial exploitation committed by close friends and family members (Jackson, 2015). More grounded research is needed to conceptually disentangle these two phenomena. The present study analyzes differences in 53 fraud and financial exploitation cases presented to the Los Angeles County Elder Abuse Forensic Center (Forensic Center), a multidisciplinary team (MDT) that provides expert case examination, consultation, and documentation to enhance investigation of elder mistreatment and to support victims. Forensic Center case files contain rich qualitative information about the victim, the perpetrator, the crime, and the amount of assets stolen. These data help overcome some limitations of survey research. Victims are older and more functionally impaired than average respondents in national surveys, so the sample is a closer representation of adult protective services (APS) clients.
Based on the adapted routine activity theory presented in Figure 1, elders may be most vulnerable to fraud by strangers when deficits in financial decision making and instrumental functioning are mild, so capable guardians are not yet involved in their affairs. In comparison, financial exploitation may be more likely to occur when the elder’s impairments are more advanced, exposing them to exploitation by the person(s) trusted to provide care and financial oversight. Three hypotheses were tested with Forensic Center cases:
Elder fraud victims have better cognitive functioning than victims of financial exploitation.
Elder fraud victims have better health and instrumental functioning than victims of financial exploitation.
Elder fraud victimization occurs when an elder has mild impairments in cognitive and physical functioning combined with a lack of financial oversight from capable guardians.
No studies have analyzed APS and law enforcement records, victim neuropsychological evaluations, medical records, and interviews to create a comprehensive profile of older people victimized by fraud and compare them with those exploited by trusted others. In this article, I argue that recognizing the important distinctions between these financial crimes, which include the perpetrators, methods of exploitation, cognitive and physical characteristics of victims, and the social context, is an essential step to identifying areas for targeted prevention.
Methods
Data
Data were abstracted from 53 Forensic Center elder mistreatment cases drawn from a pool of 924 cases presented between March 2006 and August 2013. APS workers and law enforcement officers present their challenging cases at weekly Forensic Center meetings to receive additional investigation resources and expertise from the MDT. The vast majority of these cases involve serious abuse allegations and/or complex financial crimes (Gassoumis, Navarro, & Wilber, 2015), so the sample is biased toward more severe and complicated mistreatment scenarios. Most cases (72%) involved financial victimization of an elder or dependent adult in addition to other abuse types. Approximately 120 cases (13% of total) involved financial fraud by a stranger. Cases are unique in that all fraud perpetrators cultivated personal relationships with their victims via face-to-face interactions. The sample does not include mail, online, or telemarketing fraud cases.
Forensic Neuropsychologist Evaluation
In nearly one third of Forensic Center cases, the team sends a neuropsychologist to interview the victim and to assess cognitive, physical, and mental functioning. Assessment tools vary by case and are based on the neuropsychologist’s clinical judgment of the victim’s mental status and current cognitive abilities. Case files consistently include the Managing Money subtest of the Independent Living Scales (ILS; Loeb, 1996), a 17-item scale that assesses financial abilities and reasoning including checkbook balancing, making change, and bill payment, and the Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975) is used to measure orientation, immediate and delayed recall, attention, and calculation via serial seven subtraction. The purpose of the evaluation is to identify what specific areas of cognition, for example, processing speed, attention, financial decision making, are impaired. The neuropsychologist also back-dates cognitive functioning and financial capacity. This is deduced using evidence from the victim’s current cognitive performance. The objective is to help investigators determine the victim’s probable financial capacity and whether he or she could reasonably consent to the transaction(s) when the alleged crime occurred (Naimark, 2001). Their clinical judgment is documented in a comprehensive summary report provided to Forensic Center team members.
The neuropsychologists also document the elder’s living environment, educational and professional background, physical appearance, hygiene, medication use, and social activities. They assess orientation, signs of mental illness, and substance abuse through unstructured interviews with the victim. Depressive symptoms are measured using the Geriatric Depression Scale (GDS; Montgomery & Asberg, 1979) in many cases. This information is also summarized in the report.
Two thirds of the cases also contain victims’ medical records obtained by abuse investigators. These records are requested by the Forensic Center because they provide additional information on the victim’s cognitive status prior to financial victimization. Records might include chart notes on the victim’s past hospitalizations, chronic conditions, physical functioning, medications, cognitive status, mobility, and mental health. They may contain documentation of dementia, head trauma, or stroke.
Case Selection
Although documentation varied by case, the following minimum inclusion criteria were used to select cases into the study sample: (a) victim 65 years old or older (not a dependent adult); (b) victim evaluated by forensic neuropsychologist; (c) case contains APS and/or law enforcement reports on allegations; (d) allegations substantiated, meaning that following the investigation, the assigned APS caseworker decided that the allegations constitute elder financial abuse based on evidence that makes it more likely than not that abuse occurred (California Penal Code Section 11165.12); and (e) allegations involve financial abuse by trusted other OR fraud by stranger. There is a high co-occurrence of abuse types in Forensic Center cases. Thus, cases involving financial victimization in addition other mistreatment types (e.g., physical abuse, neglect, self-neglect) were included. However, cases in which the elders were financially victimized by both strangers and trusted others were excluded so that comparisons between victimization types could be analyzed.
Cases that met these criteria were identified using an existing database developed under a National Institute of Justice (NIJ)-funded study that examined Forensic Center case outcomes—rates of prosecution and conservatorship (Navarro, Gassoumis, & Wilber, 2013), and cost effectiveness. This database tracks investigation activities and includes sociodemographic characteristics on victims, the type of elder mistreatment reported, abuser characteristics, case outcomes, and whether the victim was evaluated by a forensic neuropsychologist.
The Forensic Center’s Project Manager used this database to identify cases that met inclusion criteria. The project manager also ensured that an equal number of financial exploitation and fraud cases were selected into the sample. Fraud cases are categorized as those in which the perpetrator was not a relative or longtime friend of the elder (relationship length < 10 years), where the relationship was initiated for the purpose of monetary gain, and where the perpetrator intended to deceive the elder to get access to his/her financial resources. The financial exploitation sample included cases where the perpetrator was a family member or close friend/neighbor that had a long-standing relationship with the elder (≥10 years). These crimes mainly involved abuse of fiduciary duty, whereby the individual entrusted to manage the elder’s finances (formally or informally) misappropriated these resources. Financial crimes could involve misuse of an elder’s bank account funds or credit cards, inappropriate transfer of property, falsely promising returns on an investment where no returns were intended to be provided, falsely promising to provide care in exchange for payment when no care was intended to be provided, misappropriation of an elder’s income or assets to benefit the perpetrator at the elder’s expense, and altering an elder’s will/trust without consent (U.S. Government Accountability Office, 2012).
Sample size was limited based on the few fraud cases that included an evaluation by the neuropsychologist and that had sufficient information on the perpetrator. From the pool of 924 Forensic Center cases, 31 fraud cases met inclusion criteria. These were counterbalanced by 31 financial exploitation cases. After data were abstracted, four graduate student researchers and one faculty expert in elder abuse convened to audit data abstraction and review the cases. Based on this review, nine total cases were dropped from the analysis: five cases involved both fraud and financial exploitation; one case had substantial missing data; one was excluded because the allegations involved theft (neither fraud nor financial exploitation); and two others were dropped because the allegations were ultimately deemed unsubstantiated by the Forensic Center team. This yielded 28 fraud and 25 financial exploitation cases in the final analysis.
Data Abstraction
Data were abstracted from the following case file documents, where available: (a) the Forensic Center case intake form completed by the case presenter; (b) SOC 341—a California-specific elder abuse reporting form completed by APS and forwarded to law enforcement; (c) SOC 343—a California-specific elder abuse investigation form completed by the APS worker assigned to the case that summarizes investigation findings; (d) Supplemental Report or Follow-Up Investigation Report from the police or sheriff’s departments; (e) victim medical records including physician and social worker notes and hospital records; (f) a report from the forensic neuropsychologist who interviewed and evaluated the victim; (g) completed and scored cognitive tests that were administered by the neuropsychologist; and (h) Forensic Center meeting notes (“minutes”) from the team’s discussion of the allegations and updated with case outcomes.
Data on victims’ demographic characteristics, current and past health, cognitive functioning, financial decision making, social engagement, living arrangement, home environment, and how they met the perpetrator(s) were abstracted from the case documents during the review and entered into an Excel spreadsheet. Perpetrator demographics and information about the allegations and losses were also abstracted. Case review consistently began with medical records and cognitive tests and continued to case intake forms, the neuropsychologist report, investigator notes, and meeting minutes.
Spreadsheet rows corresponded to the case ID numbers; columns corresponded to the information abstracted from the files (variables), such as “health conditions,” “number of children,” and “relationship to perpetrator.” The final database contained 142 columns. No personal information that could identify victims, reporters of abuse, or alleged abusers was abstracted. The process was supervised by the Forensic Center’s Project Manager, and the study protocol was reviewed and approved by the University of Southern California Institutional Review Board.
Analysis
Unstandardized neurocognitive scores were abstracted where available. There was significant variation in which cognitive tests were administered. Missing data ranged from 20% to 50% across cognitive domains such as immediate and delayed recall, verbal fluency, spatial reasoning, language, attention, and financial capacity. Quantitative comparisons between fraud and financial exploitation victims’ cognitive functioning were only possible with the MMSE and the Managing Money subtest of the ILS because these tests were consistently administered. Performance clustered toward low scores (poor functioning), so differences were analyzed using Poisson regression that accounted for non-normality. Models adjusted for victim age and education.
Abstracted data were recoded numerically to reflect the intensity, severity, or frequency of each variable—a procedure called magnitude coding (Saldaña, 2013). For example, if a victim had numerous chronic health conditions, multiple hospitalizations, and was nonambulatory, overall health was coded as “3,” where 0 = excellent health and 3 = very poor health. Other qualitative information such as financial capacity, level of memory impairment, mobility, and dependency were also assigned numeric values. Statistical differences between fraud and financial exploitation victims were analyzed using Fisher’s exact test because many variables had expected cell sizes of less than five.
A key objective of this study was to test the application of routine activity theory that posits that financial victimization is more likely to occur when the elder exhibits subtle declines in cognitive or instrumental functioning and thus lacks oversight from capable guardians. Using victims’ medical records, cognitive evaluations, and narratives about how relationships with perpetrators began and how events unfolded, a cross-case comparison analysis (Miles, Huberman, & Saldana, 2013) was conducted. The goal was to determine whether factors that purportedly increase opportunities for financial predators to take advantage of their targets—cognitive/financial decision-making impairment and lack of capable guardians—relate chronologically to financial loss.
Results
Target Vulnerability
Demographic characteristics are presented in Table 1. More than 46% of fraud victims and 56% of financial exploitation victims were female (p = .323). Fraud victims were 83.3 years old, and financial exploitation victims were 84.1 years old, on average (p = .630). Nearly half of the fraud victims reported high school as their highest degree. Two victims (~4%) did not complete high school, six victims (~21%) had some college education, and five victims (~18%) had an advanced degree. Six financial exploitation victims (24%) did not graduate high school, six (24%) attended some college, and three (12%) had an advanced degree. Sixty percent (n = 17) of fraud victims were non-Hispanic White compared with 48% (n = 12) financial exploitation victims. Differences in race and education were not significant (p = .263; p = .207).
Table 1.
Victim Characteristics
| Financial exploitation victims (n = 25) | Fraud victims (n = 28) | |||
|---|---|---|---|---|
| Victim characteristics | n | % of total | n | % of total |
| Average age (SD) | 25 | 84.1 (6.8) | 28 | 83.3 (5.0) |
| Sex (female) | 14 | 56% | 13 | 46.4% |
| Race | ||||
| Non-Hispanic White | 12 | 48.0% | 17 | 60.7% |
| Black | 6 | 24.0% | 4 | 14.3% |
| Hispanic | 4 | 16.0% | 3 | 10.7% |
| Asian/Pacific Islander | 1 | 4.0% | 4 | 14.3% |
| Other | 2 | 8.0% | 0 | 0.0% |
| Education | ||||
| Less than high school | 6 | 24.0% | 2 | 7.1% |
| High school graduate | 5 | 20.0% | 13 | 46.4% |
| Some college (1–3 years) | 6 | 24.0% | 6 | 21.4% |
| Trade school | 3 | 12.0% | 1 | 3.6% |
| College graduate (4 years) | 1 | 4.0% | 1 | 3.6% |
| Advanced degree (Master’s/PhD) | 3 | 12.0% | 5 | 17.9% |
| Unknown | 1 | 4.0% | 0 | 0.0% |
| Marital status | ||||
| Never married | 4 | 16.0% | 8 | 28.6% |
| Married | 2 | 8.0% | 6 | 21.4% |
| Widowed | 17 | 68.0% | 11 | 39.3% |
| Divorced/separated | 1 | 4.0% | 3 | 10.7% |
| Unknown | 1 | 4.0% | 0 | 0.0% |
| Present living arrangement | ||||
| Alone | 8 | 32.0% | 11 | 39.3% |
| Own home with spouse/partner | 1 | 4.0% | 2 | 7.1% |
| Own home with other family/friends | 4 | 16.0% | 3 | 10.7% |
| Own home with paid caregiver | 1 | 4.0% | 2 | 7.1% |
| Institutional care setting | 5 | 20.0% | 8 | 28.6% |
| Own home with abuser (relative) | 2 | 8.0% | 0 | 0.0% |
| Own home with abuser (nonrelative) | 4 | 16.0% | 2 | 7.1% |
| Lived with perpetrator at time of exploitation | 9 | 36.0% | 4 | 14.3% |
| Multiple perpetrators | 3 | 12.0% | 4 | 14.3% |
The majority of financial exploitation and fraud victims presented with deficits in some or all areas of cognitive functioning when they were evaluated following the allegations. As shown in Table 2, there were no significant differences in memory (p = .143), measured by immediate and delayed word recall, and no significant differences in financial capacity (p = .589) following the allegations. Fraud victims performed significantly better on the MMSE compared with financial exploitation victims (β = 0.142, p = .026) after controlling for age and education, but differences in money management on the ILS were not significant (β = 0.157, p = .127).
Table 2.
Differences in Cognitive Functioning Between Fraud and Financial Exploitation Victims
| Financial exploitation victims | Fraud victims | Fisher’s exact test | Poisson regression (fraud = 1) | ||||
|---|---|---|---|---|---|---|---|
| Cognitive functioning | Mean (SD) or % of total | Mean (SD) or % of total | p Value | Coefficient | 95% confidence interval | p Value | |
| Mini-Mental State Examination | 18.8 (5.0) | 21.4 (6.9) | 0.14 | 0.02 | 0.27 | 0.026 | |
| Money Management | 14.9 (9.8) | 20 (10.3) | 0.16 | −0.045 | 0.36 | 0.127 | |
| Memory | |||||||
| Not impaired | 0.0% | 7.7% | 0.143 | ||||
| Mildly impaired | 8.3% | 19.2% | |||||
| Moderately impaired | 33.3% | 11.5% | |||||
| Severely Impaired | 58.3% | 61.5% | |||||
| Financial capacity | |||||||
| Not impaired | 0.0% | 0.0% | 0.589 | ||||
| Mildly impaired | 4.6% | 14.3% | |||||
| Moderately impaired | 31.8% | 32.1% | |||||
| Severely Impaired | 63.6% | 53.6% | |||||
Note: The Poisson regression models adjust for victims’ age and education levels.
The neuropsychologists reported that most victims had poor insight into their cognitive deficits. The majority could not describe how to prevent being cheated out of money and made errors writing checks. Although most victims were oriented to person, place, and situation, 50% of fraud victims were incorrect on the date. The vast majority of financial exploitation victims were not oriented to date.
Sixty-four percent of victims in both groups had a history of cognitive impairment that was documented in their medical records or was described by collateral sources who provided information about the victim to investigators, such as family members, friends, neighbors, and caregivers. Among the fraud victims who tested as cognitively impaired by the neuropsychologist (85%) and had data on prior cognitive functioning, the average length of impairment was 3 years, whereas for financial exploitation victims (88% impaired), it was slightly longer—4.4 years.
As shown in Table 3, differences in overall health prior to the investigation were not statistically significant (p = .369). Based on victim medical records, cardiovascular diseases such as arteriosclerosis, hypertension, congestive heart failure, and other age-related conditions—cataracts, dementia, diabetes, stroke, and Parkinson’s disease—were common in both groups. The neuropsychologist assessed instrumental functioning through observation and interview. The majority of victims needed assistance with instrumental activities of daily living (IADLs)—driving, shopping, and money management, but needed help with only some basic activities of daily living (ADL) such as bathing, toileting, transferring, and getting dressed. Seventeen fraud victims reported they needed no assistance with ADLs, yet the neuropsychologists noted that two of these individuals had poor insight about their personal care needs and actually required significant care. Differences in ADLs and IADLs were not statistically significant (p = .841). Mobility differences were statistically significant (p = .049), such that only a third of fraud victims needed a cane, walker, or wheelchair to ambulate compared with 60% of financial exploitation victims who relied on a device.
Table 3.
Differences in Health, Mental Health, and Functional Impairment Between Fraud and Financial Exploitation Victims
| Financial exploitation victims | Fraud victims | Fisher’s exact test | |
|---|---|---|---|
| Health and physical functioning | n or % of total | n or % of total | p Value |
| Overall health | |||
| Good | 0 (0.0%) | 2 (7.1%) | 0.369 |
| Fair | 9 (36.0%) | 8 (28.6%) | |
| Poor | 6 (24.0%) | 9 (32.1%) | |
| Very poor | 10 (40.0%) | 9 (32.1%) | |
| Mobility | |||
| No difficulty/no assistive device | 10 (40.0%) | 18 (66.7%) | 0.049 |
| Uses an assistive device | 15 (60.0%) | 9 (33.3%) | |
| Functional dependency | |||
| Independent/little assistance needed | 12.0% | 14.8% | 0.841 |
| Some IADL and no ADL assistance | 24.0% | 33.3% | |
| All IADL and some ADL assistance | 28.0% | 25.9% | |
| Fully dependent on others | 36.0% | 25.9% | |
| History of depressiona | 11 | 13 | |
| History of psychosisa | 5 | 6 | |
| History of substance abuse problemsa | 3 | 3 | |
| History of stroke or transient cerebral ischemiaa | 7 | 8 | |
Note: ADL = activities of daily living; IADL = instrumental activities of daily living.
aDue to missing data on mental health and substance abuse, percent of total sample with the condition is unknown.
Five financial exploitation and six fraud victims had a history of psychosis: three were hospitalized due to episodes of delirium and volatile behavior associated with dementia; one person was diagnosed with obsessive compulsive disorder and hypochondria, and the others had episodes of paranoia, including hallucinations and delusions. Seven financial exploitation victims and eight fraud victims had a history of stroke. Only three victims in each group had substance abuse problems documented in their medical records.
A history of depression (prior to the allegations) was noted in 13 fraud victims’ case files and 11 financial exploitation victims’ case files. Eleven fraud victims and six financial exploitation victims were clinically depressed when evaluated by the neuropsychologist following the allegations. Recent negative life events, such as widowhood, hospitalization, and other forms of elder abuse, were also recorded. Financial abuse victims experienced high levels of co-occurring emotional abuse (six victims; 24%), caregiver neglect (four victims; 16%), and isolation (two victims; 8%). The most frequent co-occurring abuse type for fraud victims was self-neglect (four victims; 14%). Significant differences between victim groups and the percent of victims with these conditions/life events are not presented in Table 3 because it was not possible to differentiate which victims never experienced these conditions/life events and which simply had information missing in their files.
Motivated Offender Characteristics
Perpetrator characteristics are presented in Table 4. Fraud perpetrator(s) befriended or engaged with the victim for the sole purpose of monetary gain and used deception to obtain the victims’ money or property. Financial exploitation perpetrators had preexisting relationships with their victims (“trusted others”) that were not initiated for the purpose of financial gain. As such, the majority of financial exploiters were related to their victims: ten were adult children (40%), two were grandchildren (8%), and two were other relatives (8%). Four were neighbors (16%), one was a longtime friend (4%), and three were roommates/tenants who knew their victims well (12%). In contrast, fraud perpetrators were complete strangers (six perpetrators; 21%), recent acquaintances (three perpetrators; 11%), neighbors/tenants (four perpetrators; 14%), nonrelative caregivers (four perpetrators; 14%), self-proclaimed service professionals—financial planners, general contractors, and property managers (five perpetrators; 18%), and new romantic partners (six perpetrators; 21%). On average, fraud perpetrators had known their victims for 2.75 years by the time the case was investigated, whereas financial exploiters knew their victims ≥10 years, on average, or for a lifetime if they were relatives. This difference in victim–perpetrator relationship length was statistically significant (p < .001).
Table 4.
Perpetrator Characteristics
| Financial exploitation perpetrators | Fraud perpetrators | |||
|---|---|---|---|---|
| Perpetrator characteristics | n | % of total | n | % of total |
| Sex | ||||
| Female | 7 | 28.0% | 15 | 53.6% |
| Male | 17 | 68.0% | 7 | 25.0% |
| Both male and female perpetrators | 1 | 4.0% | 4 | 14.3% |
| Unknown | 0 | 0.0% | 2 | 7.1% |
| Agea | ||||
| 29 and younger | 1 | 4.0% | 2 | 7.1% |
| 30–39 | 0 | 0.0% | 4 | 14.3% |
| 40–49 | 8 | 32.0% | 8 | 28.6% |
| 50–59 | 10 | 40.0% | 6 | 21.4% |
| 60 and older | 2 | 8.0% | 0 | 0.0% |
| Unknown | 4 | 16.0% | 8 | 28.6% |
| Racea | ||||
| Non-Hispanic White | 9 | 36.0% | 7 | 25.0% |
| Black | 6 | 24.0% | 3 | 10.7% |
| Hispanic | 9 | 36.0% | 8 | 28.6% |
| Asian/Pacific Islander | 0 | 0.0% | 3 | 10.7% |
| Other | 1 | 4.0% | 4 | 14.3% |
| Unknown | 0 | 0.0% | 3 | 10.7% |
| Relationship to victima | ||||
| Total stranger | 0 | 0.0% | 6 | 21.4% |
| Son/daughter | 10 | 40.0% | 0 | 0.0% |
| Grandchild(ren) | 2 | 8.0% | 0 | 0.0% |
| Other relative | 2 | 8.0% | 0 | 0.0% |
| Nonrelative caregiver | 2 | 8.0% | 4 | 14.3% |
| Romantic partner | 1 | 4.0% | 6 | 21.4% |
| Business professional | 0 | 0.0% | 5 | 17.9% |
| Tenant/roommate | 3 | 12.0% | 2 | 7.1% |
| Neighbor | 4 | 16.0% | 2 | 7.1% |
| Friend (longtime) | 1 | 4.0% | 2 | 7.1% |
| Friend (new) | 0 | 0.0% | 1 | 3.6% |
Note: aIf multiple perpetrators in a case, data only include demographic information on the primary perpetrator.
More than a quarter of the fraud cases contained no information on the perpetrator’s age. Of the data available, fraud perpetrators were younger than financial exploiters, on average, but differences were not statistically significant (p = .130). The majority of perpetrators in both groups were between ages 40 and 59 years. Significantly more fraud cases involved female perpetrators compared with financial exploitation cases (15 vs 7; p = .008). Perpetrators were racially diverse: seven fraud perpetrators (25%) were non-Hispanic White compared with nine financial exploiters (36%); three fraud perpetrators (11%) and six financial exploiters (24%) were Black; eight fraud perpetrators (29%) and nine financial exploiters (36%) were Hispanic (p = .132).
Two financial exploiters had documentation of bipolar disorder, three had a criminal history, two had gambling problems, and one was substance abuser. These observations were not available for fraud perpetrators.
Absence of Capable Guardians
Significantly more financial exploitation victims were widowed prior to victimization—68% versus 39% (p = .023). Females were more likely than males to be widowed (p = .013), and these gender differences were present in both victimization groups. Most widows had been without their partner for six or more years. Just two financial exploitation victims (8%) were still married compared with six fraud victims (21%), some of whom married the perpetrator and were involved in romance scams. Eight fraud victims (29%) had never been married compared with four financial exploitation victims (16%). Fraud victims were significantly less likely to have children: 64% of fraud victims were childless compared with 36% of financial exploitation victims (p = .040).
Approximately 67% of fraud victims lived alone at the time of victimization compared with 48% of financial exploitation victims (p = .173). Significantly more financial exploitation victims lived with the perpetrator at the time of exploitation (36% vs 14%; p = .041), and following the investigation, six financial exploitation victims (24%) and two fraud victims (7%) were still living with the perpetrator. Seven fraud victims (26%) and five financial exploitation victims (20%) had relocated to live with friends, relatives, or into a long-term care facility. Based on the neuropsychologists’ reports, 14 financial exploitation victims (64%) and 13 fraud victims (54%) were intentionally isolated by the perpetrator during the period of financial loss. These differences were not significant (p = .562).
Financial Losses
Financial losses were more than three times greater among fraud cases than financial exploitation. Of the 24 fraud victims who had data available (86%), nearly $15 million was taken, or approximately $619,000 per victim, ranging from $1,700 to $5,000,000. Five fraud victims also lost a total of nine properties. Of the 20 financial exploitation cases that had data available (80%), victims lost nearly $4 million total, an average of $199,000 per victim. These losses ranged from $5,000 to $275,000. Six victims also lost eight properties combined.
Victims generally did not lose all of their assets in a single act of misappropriation or deception. Rather, perpetrators took small amounts at first—money to buy groceries, compensation for housekeeping services, small “loans”—and then later went after the elder’s larger assets—cars, homes, and investment properties. Based on the neuropsychologists’ interviews, most victims were unaware that someone had taken advantage of them, and among those who did acknowledge they had lost money, the majority believed they would eventually get some back from the perpetrator.
Discussion
According to routine activity theory, the presence of suitable targets in proximity to motivated offenders in an unsupervised context increases the likelihood of crime (Cohen & Felson, 1979). To a varying extent, the victims in these Forensic Center cases show evidence of being suitable targets. Their vulnerabilities include social isolation, poor health, and poor financial decision making. During the investigation, victims demonstrated little insight about these impairments and self-care needs. Many denied being financially mistreated. These findings indicate that some older victims may fail to recognize the extent to which they need assistance from others and when they are being financially manipulated.
There were no meaningful differences between fraud and financial exploitation victims’ financial decision making at the time of victimization based on the neuropsychologists’ assessments of prior functioning and review of their medical records. A proposed explanation for these lack of significant differences is that diminished financial capacity is a risk factor for both elder fraud and financial exploitation. Using neurocognitive data from similar Forensic Center cases, a pilot study found that 27 financial exploitation victims performed significantly worse on tests of processing speed, attention, financial decision making, and memory compared with a control sample of 32 healthy older adults (Wood et al., 2014). The present analysis also found that victims performed poorly, but cognitive scores were not compared with a healthy control group. A strength of this study is that in addition to tests administered following the allegations, information on victims’ prior cognitive functioning and health was abstracted from their medical records and the neuropsychologists’ reports. A limitation is the considerable variability in when victims were evaluated by health care professionals and which measures they used.
Medical problems and functional impairments were pervasive in both groups as well. More than 50% of all victims needed assistance with ADLs and nearly all required help with one or more IADLs. Common health conditions were cardiovascular disease, dementia, vision impairment, anemia, osteoporosis, and other debilitating illnesses that increase dependency. The one significant difference in health was that fraud victims presented with better mobility than financial exploitation victims, on average, when they were interviewed by the neuropsychologist. Routine activity theory predicts that engagement in activities away from the household increases opportunities for crime because it brings suitable targets in contact with motivated offenders (Cohen & Felson, 1979). Older adults have more opportunities to engage with community members if they are ambulatory (Webber, Porter, & Menec, 2010), including financial predators. Ambulatory adults also require less instrumental support from others who could potentially deter fraudsters’ solicitations.
The Cost of Victimization
Fraud victims lost significantly more money—an average of nearly $619,000 compared with $200,000 per person. One explanation is that financial exploiters are more opportunistic—they take advantage of vulnerable adults within their social networks who span the spectrum from rich to poor, whereas fraud perpetrators actively seek more lucrative targets. Total asset value before victimization was not collected by investigators so it is not possible to test the hypothesis that fraud perpetrators deliberately prey on wealthier individuals.
An alternative explanation is that financial exploitation may be detected earlier in the course of asset loss when other family members and friends become suspicious of the perpetrator and intervene. Fraud victims, who were less likely to have children in these cases, might have fewer capable guardians in their social networks to intervene on their behalf, therefore leading to greater losses overall. Of the data available, both victim groups lost a total of $19 million in savings and investments and 17 properties. Although these are unusually complex Forensic Center cases, they suggest that MetLife’s (2009) projection of $2.9 billion in losses underestimates the annual cost of elder financial victimization in the United States.
In the majority of both fraud and financial exploitation cases, perpetrators initially took only small amounts of money and then gradually increased to taking larger assets after the victim was fully under their control. The loss of these more substantial assets is often what drew the attention of people who reported the cases to APS and/or law enforcement. Given that initial losses are typically minimal, financial institutions should implement systems to flag small but unusual transactions and a system for notifying the authorized representatives on the elder’s accounts. These tools would help detect financial fraud and exploitation in the beginning and thus protect older adults from financial devastation.
The Social Context
In this study, fraud and financial exploitation victims had different family structures that may create different opportunity structures for crime. Fraud victims were significantly less likely to have children and also had fewer relatives nearby. Adult children are a key source of support for aging parents. They also have a financial stake in ensuring that their parents are not defrauded. Although the data do not support the hypothesis that fraud victims were only mildly cognitively and functionally impaired when they were first solicited by financial predators, qualitative findings strongly support the adapted routine activity theory that proposes that elders fall victim to fraud when there are no capable guardians to help safeguard assets.
Findings from this study suggest that family composition and the presence of a bad actor in the elder’s inner circle is a differentiating factor between fraud risk and financial exploitation risk. Although adult children may prevent strangers from establishing control over an aging person, their influence, if unchecked, presents other opportunities for financial mistreatment. Adult children tend to shoulder the responsibility of managing their parents’ finances in old age, and powers of attorney privileges are easily abused (Nerenberg, 2000). In this study, 15 out of the 25 exploiters were the victims’ appointed agents. In addition to these privileges, at least 20% of the exploiters had either mental illness (bipolar disorder), substance abuse, gambling issues, or a history of criminal activity. These problem behaviors are risk factors for elder mistreatment (Pillemer et al., 2016) and may create a pattern of reverse dependency, whereby the perpetrator relies on the older adult for financial support rather than the older adult depending on the abuser for care (Pillemer & Finkelhor, 1989).
Social isolation was common among victims in this study. Based on victim self-report and accounts from collateral sources, some elders became isolated after losing a spouse or becoming physically disabled, whereas others were lifelong introverts. Isolating life events may increase victimization risk by reducing the presence of capable guardians in addition to reducing psychological well-being. Lichtenberg, Stickney, and Paulson (2013) found that older adults with depression and low social-needs fulfillment experienced three times higher odds of fraud victimization.
The structural characteristics of an elder’s social network matter as well. Schafer and Koltai (2015) found that elders with dense social networks had lower risk of elder mistreatment, suggesting that group members deter others in the network from engaging in deviant behavior, including financial exploitation. These findings lend further support to routine activity theory, which posits that increasing the presence of capable guardians denies opportunities for crime (Cohen & Felson, 1979). Widening an elder’s social network (more eyes and ears), encouraging trustworthy family members and professionals to participate in financial decisions, and instituting legal/financial safeguards that protect the elder’s assets are promising interventions that might reduce risk of victimization.
Social isolation is not only a potential risk factor for financial victimization, it is also a tactic of undue influence—the substitution of one person’s will for the will of another (Quinn, 2000). Perpetrators begin by limiting and controlling their victims’ social interactions to create a sense of powerlessness and emotional dependency (American Bar Association Commission on Law and Aging & American Psychological Association, 2008). This makes victims easier to manipulate even if they are mentally competent. In this study, perpetrators actively isolated half of the fraud victims and 56% of financial exploitation victims. In one case, a fraud perpetrator “isolated the victim from family and previous employees,” and “withheld food to coerce victim to sell strip mall and fire long-term attorney and accountant.” Another changed the victim’s locks and unplugged her landline telephone to isolate her from her son, and in a third case, a group of perpetrators moved the elder into a long-term care facility in order to sell his house that they acquired through a quitclaim deed. In a financial exploitation case, the “grandson perpetuated a sense of fear and anxiety in victim to make her more afraid that her son was going to steal from her or kill her.”
Manipulation of Trust
A common thread running through the fraud cases was how perpetrators used false pretenses and fake identities to gain their targets’ trust. These imposters claimed to be personal care workers, social workers, housekeepers, an investment advisor, and a home repairman. They stalked places frequented by older people. One perpetrator met her victim in a supermarket parking lot, another at a hospital, and another in an assisted living facility. Using a false credentials to establish authority is a popular persuasion tactic among fraudsters (DeLiema, Yon, & Wilber, 2016).
Another popular influence tactic in this study was exploiting the victim’s need for companionship. Six victims in the sample were targeted in romance scams. One female perpetrator befriended an older gentleman by pretending to be a friend of another resident in his assisted living facility. They began a secret courtship that lasted between 6 and 10 visits according to the investigator’s report. She convinced him to sign his name on loan documents to purchase her a Mercedes that was missing by the time police investigated. In another case, a man with diminished capacity was seduced by the woman hired to provide care to his brother, and another victim gave money to three different women promising sexual intimacy. Desire for companionship may motivate some elders to provide financial favors in return for attention from an attractive stranger, and widowers might be particularly vulnerable. Romance scams are especially tragic because victims lose money in addition to having a broken heart. More research is needed to profile romance scam victims and determine whether widowhood is a precipitating life event.
Limitations
The Forensic Center investigates some of the most serious and complex cases of elder mistreatment in Los Angeles County. Cases are not representative of most reports to APS, nor do they capture the diversity of fraud schemes. For example, the sample does not include cases where perpetrators only interacted with victims online or by phone, such as telemarking or direct mail scams. Yet, because victimization is so well documented in Forensic Center files, data provide a unique in-depth look at fraud and financial exploitation and the conditions under which these crimes occur. Results need to be tested using a large number of geographically diverse cases reported to APS that were not presented to a Forensic Center.
Although this study found that victims of fraud and financial exploitation share similar health and cognitive vulnerability characteristics, the sample may be too small to detect significant differences that may in fact exist. These findings must be tested using a larger sample. The goodness-of-fit χ2 test was statistically significant for the models examining differences in ILS and MMSE performance. Additional predictor variables and a larger sample are needed to improve model fit.
There are a number of disadvantages associated with retrospective case reviews including a lack of standardization in data collection and assumptions that the information in the files is accurate, complete, consistent, and nonbiased (Hess, 2004). These are major assumptions that can only be addressed in a well-controlled prospective study. In Forensic Center investigations, the purpose of the victim neurocognitive evaluation and medical record review is to inform investigators about the elder’s probable capacity when the incident occurred and to assess current vulnerability. It was not to collect data for research. Although all files contained comprehensive reports on victims’ functioning, most were missing the raw scores on which these reports are based. They also varied as to which tests were used and how long after the incident they were administered. Furthermore, medical records were missing in more than 30% of cases. These issues can be addressed in future studies by standardizing data collection protocols in elder abuse investigations. Another option is to add items on the incidence of financial exploitation and fraud victimization to existing longitudinal studies such as the Health and Retirement Study.
Conclusion
Many scholars have emphasized a need to focus more on perpetrators whose characteristics and behaviors are more strongly predictive of elder mistreatment than victim factors alone (e.g., Jackson & Hafemeister, 2011; Pillemer & Finkelhor, 1989). This study goes a step further by focusing on the social context of victimization. A main finding was that the structure of an elder’s social network might differentiate fraud susceptibility from financial exploitation susceptibility.
Prospective longitudinal data is needed to determine what subtle cognitive changes precipitate victimization and at what point family members or professionals should get involved. In the Forensic Center cases, valuable assets were taken only after perpetrators realized they could get away with pilfering small amounts of cash and other valuables. To better protect older adults, financial institutions should build tripwires in transactional accounts that are sensitive to these marginal losses, and notify the elder’s trusted agent(s) if suspicious activity occurs.
Funding
This work was supported by the National Institute on Aging (grant number T32AG000037).
Acknowledgments
The author thank Prof. Kathleen Wilber for her support and assistance reviewing the manuscript. The author also thank Allyson Young for assisting with case selection and Jeanine Yonashiro-Cho, Zachary Gassoumis, and Yongjie Yon for reviewing the cases and assisting with categorization.
Conflict of Interest
None declared.
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