1. Introduction

Individual fraud victimisation in many industrialised countries has become one of the biggest crime risks individuals face. The Crime Survey for England and Wales (CSEW) in the year ending September 2022, showed fraud accounted for 41% of all crime (ONS, 2023a). Older adults are often viewed as being particularly vulnerable to fraud – although evidence from the CSEW shows they are at least in terms of victimisation, not the highest risk group (see later section). There is nevertheless plenty of anecdotal evidence and research illustrating the devastating impacts of fraud on some older adults (Alves and Wilson, 2008; Button et al., 2014, 2021; Cross, 2016a). Consequently there have been plenty of initiatives to prevent fraud in general and particularly against older adults. There has, however, been no attempt at mapping the diverse preventative measures aimed at protecting individual older adults from fraud, other than one broader attempt at applying the 25 techniques of preventions at fraud in general (Button and Cross, 2017). This paper seeks to provide the first typology of the different tools and strategies which are used to prevent fraud against older adults with particular reference to the level of sophistication of technology used in them. The research is built upon the two countries the UK and South Korea, which are both countries with ageing populations and a significant fraud problem. The typology also illustrates any evidence which exists supporting whether they actually work. The paper ends by drawing together all these strategies to illustrate a model of how these could all be applied together to prevent fraud against older adults (see Fig. 7).

The paper begins by exploring the problem of fraud against older adults, before examining the limited literature evaluating fraud prevention measures either specifically directed at older adults or frauds they are frequently victims of. After setting out the methodology the paper then identifies a wide range of schemes and products directed at fraud prevention. It then groups them according to the level of technology involved, with particular reference to the Fourth Industrial Revolution and the level of technology involved. Finally, the paper sets a holistic model for the prevention of fraud against older adults.

2. Older adults, fraud and prevention

Table 1 illustrates rates of fraud victimisation among older adults in England and Wales between 2019 and 2022. The overall victimisation rate was 7.8% in 2022, which compared to 7.6% for 65–74 year olds and 5.8% for over 75s. The most at risk group was actually 45–54s, at 9.3%, but what is interesting is over this period the two groups with the biggest increase in victimisation are the 65–74 age group (58.4% increase) and over 75s (61.8%). The impact of the pandemic, likely contributing to this increase among older age groups (Kemp et al., 2021).

Table 1. CSEW fraud victims by age group 2019-22 Year ending March (ONS, 2023b).

2.1. Losses to fraud

Older adults may not be the most at risk group, but they tend to lose more. Table 2 shows as the age rises so does the average losses, with the 65–74 and 75+ losing the most. Many of these are in positions in life where its harder to recover from losses, dues to fixed pensions.

Table 2. Average losses by age group reported to Action Fraud 2020–2022 Group 2020 2021 2022 (FOI Request).

2.2. Frauds and scams

Fraud and scam are often used interchangeably to describe deceptive behaviours that cause a person some form of financial loss. They are often used as synonyms, although some have noted differences between the two. For instance, Button and Cross (2017) note scams can be deceptive behaviours which cause a loss, which are clearly unethical, but lawful; whereas frauds are always unlawful. Another term important to grasp in this context is financial abuse, which is also a term with much debate on the scope, but generally considered to cover the improper or illegal exploitation or use of funds/resources of an older person (Fealy et al., 2012). It is also usually more associated with those close to the older adult such as family, carers or professionals working with them. Cybercrime is a much broader concept that covers both economic, psycho-social and state cybercrimes (Ibrahim, 2016). This article is only interested in the former along with frauds, scams and financial abuse.

There are a number of methods of fraud and cybercrime which are common vectors for defrauding them. Doorstep frauds/scams: rogue tradesmen who massively overcharge for their services and/or conduct works not required or to a poor standard (Phillips, 2016). Financial abuse of older adults by carers, relatives or friends (Dalley et al., 2017). Telephone scams, where there is high pressure sales of worthless goods or service, particularly investments; impersonation scams that trick victims into transferring money and vishing, where sensitive personal information is sought (Benbow et al., 2022; Carter, 2021; Choi et al., 2017; DeLiema et al., 2020a; 2020b; Lee, 2020; Payne, 2020). Postal scams which utilise fake lotteries, bogus charities and investment schemes to name some touted through traditional mail (Rebovich and Corbo, 2021). The Authorised Push Payment Fraud (APP) where the victim is deceived into authorising a payment to a criminal via impersonation is another common fraud (National Fraud Authority, 2011; Age UK, 2023). Identity frauds: where victims are impersonated to use their financial credentials or identity fraudulently frequently occur (Cifas, 2022; DeLiema et al., 2021). Finally, there are also cyber-frauds covering a wide range of scams using email, the internet and social media (Button and Cross, 2017; Age UK, 2015). Covid-19 has also pushed many older adults towards technological services they didn't previously use which has opened up many more fraud and cybercrimes against them (Benbow et al., 202; Hakak et al., 2020).

Many older adults are lucrative potential targets, as large numbers have lifesavings, retirement pots and investments. Some are also more at risk to fraud victimisation as they fit a trait where there is evidence that makes them more likely to be fraud victims such as suffering cognitive impairment, experiencing health problems, living alone, lonely and a lack of social networks (Alves and Wilson 2008; Cross, 2016b; DeLiema 2018; DeLiema et al., 2018; Duke Hana et al., 2015; James et al., 2014; Judges et al., 2017; Lee and Soberon-Ferrer, 1997; Peterson et al., 2014; Ueno et al., 2021; Wen et al., 2022; Xiang et al., 2020).

3. Fraud prevention literature

This paper will reveal a large number of different initiatives that are and have been used to prevent frauds and scams against older adults. There is, however, very little high-quality evaluation of many of these schemes, as Prenzler (2020, p83-84) notes, regarding the 19 fraud prevention projects found, documented in 24 studies in a systematic review:

Given the size and growth of the fraud problem, it would be reasonable to expect a large number of well-documented intervention studies aimed at demonstrating successful antifraud strategies. However, this does not appear to be the case. The fraud literature has been characterised by descriptive statistics of the dimensions of the problem, and analyses of victim and offender characteristics and opportunity factors, with very little on prevention, especially in terms of applied projects.

Many of the studies on fraud prevention are also directed at organisational and financial statement related fraud (Button et al., 2023a, Button et al., 2023b). The strategies and tools to prevent fraud against older adults that will be explored, many lack evidence of their effectiveness in preventing fraud. This doesn't mean they don't work, rather there is no evidence that proves they do, which raises an important question the authors will return to later in the discussion, over whether it is even necessary to be sure such schemes work using the highest quality evaluations available. This section will briefly explore the smaller body of knowledge that has offered some evidence of effective fraud prevention schemes, however weak. Before this is done it is important to note what is meant by high quality evidence a scheme works.

Sherman et al. (1997, 1998) were able to provide a comprehensive analysis of hundreds of crime prevention projects using the Maryland framework to determine what works in preventing crime and what does not. The Maryland framework has roots in medicine and the use of very high quality evaluations ranging from assessments before and after an intervention has been introduced, through to randomized control trials. This scientific analysis has fundamentally influenced the approach many governments and law enforcement agencies take in their effort to develop effective crime reduction strategies (Sherman et al., 2002; College of Policing, 2022). However, as this section will show the limited literature on fraud prevention generally does not use a methodology that fits this scale. Instead for many there is no evidence or other forms of evaluation are used, some of which evaluate a different issue related to the impact on fraud, such as confidence in spotting frauds or stopping scam call and utilise different methodologies rooted in: literature based studies; views of practitioners or offenders, based upon their past experience through interviews or surveys; experiments with students, members of the public or victims to test whether certain schemes work or not; the use of an existing dataset (such as credit card transactions, with known fraud and correct) which is then tested to produce tools/algorithms to detect/prevent fraud; and surveys of victims and non-victims along with prevention methods and security behaviours they use, to test statistically between the two groups which of these measures may have an impact on victimisation.

The focus of this section will be specific fraud prevention studies relevant to older adults, but it's important to note there are other relevant studies targeted more generally, beyond the scope of this review (see for example Edwards et al., 2017; Leukfeldt and Yar, 2016). One of the most common fraud prevention initiatives relates to fraud awareness training. These measures essentially seek to raise awareness of scams in an individual so they can spot them and avoid falling victim. In one scheme developed and evaluated by Age UK (A UK NGO providing support to older adults) they implemented an awareness raising strategy. The scheme was evaluated using surveys of older adults, telephone interviews with partners and interviews with key stakeholders. The evaluation showed some positive results in terms of increasing the awareness of scams among older adults, improving the feelings of safety and that they were more likely to report scams, among others. However, the evaluation did not explore if it had any impact on victimisation and did not conduct a Maryland level evaluation exploring before and after.

Other research by Mears et al. (2016) suggested that the better educated and more financially secure gain more from awareness raising measures. There is also research which has looked at how older adults are victimised and noted the need for tailored messaging to meet the needs of specific segments of older adults, the types of fraud they are at risk of and the importance of using established forums and networks to disseminate these messages (Oliveria et al., 2016; Xiang et al., 2020). A review of fraud awareness messaging in multiple jurisdictions based upon the views of experts also noted how the use of real case studies of victims was seen as more effective in preventing investment fraud. Studies using experimental research found an important message for potential victims is to not rush financial decisions and postpone them; they found being in a high state of arousal when making such decisions increases the likelihood of being victimised (The Board of The International Organization of Securities Commissions, 2015; Kircanski et al., 2018.

In some initiatives the awareness raising measures amount to much more deeper training. In one scheme in which potential victims received Outsmarting Investment Fraud (OIF) training they were contacted three days later by a skilled telemarketer to ask if he could send information about a proposed investment, of which 18% who had received the training did, compared to 36% in the control group who hadn't received the training (Shadel et al., 2010). Although clearly a positive the experiment didn't involve a test of victimisation and was only three days after the training.

Reverse boiler rooms have also been used in some schemes where the authorities conduct fake scams calls to potential victims to see if they are susceptible. This has also been used for websites, fake phishing emails, leaflets etc. In one study several experiments were undertaken where potential victims were given fraud awareness training and then several days later telemarketers pretended to be scammers and contacted them with a fake scam to determine if the now trained potential victims would still be susceptible, alongside a control group with no training. Those who were victims of the scam were then offered further help to try and prevent them doing so again (AARP, 2003). The various experiments showed response rates to the scams could fall by half in some cases.

In another scheme (Project Sunbird) in Australia through the use of financial intelligence to determine payments being made to West Africa, the police wrote to these potential victims warning them to stop paying fraudsters. As a result of this intervention, 73% stopped sending money after the first letter, and 87% after the second letter (Cross, 2016b).

Call blockers have also become a tool to prevent telemarketing fraud. There are a variety of products and apps available and they do vary in how and the amount of scam/nuisance calls they block. In one scheme, however, the use of Truecall's technology (which essentially blocks all but approved numbers - and there are variations on the system), in an experiment with 1084 devices fitted found 99% of scam and nuisance calls were blocked, 99% of those in the scheme also felt happier as a result of the calls being blocked and the scheme claimed a 32–1 return on investment (National Trading Scams Team, 2020). Another evaluation of the same product found positive results too (Rosenorn-Lanng and Corbin-Clarke, 2020, p 91). Both these evaluations provide clear positive evidence of the benefits of call blockers, but again there is no evidence they actually reduce victimisation – although one could theorise the reduced opportunities would have an impact.

Another important type of intervention which has been advocated and evaluated is the specialist training of those professionals who work with older adults to spot potential fraud victimisation or financial abuse to report such behaviours or if feasible to intervene to stop victimisation. There have been a variety of schemes targeted at roles such as social workers, healthcare workers and bankers to name some. In a large experimental study AARP Public Policy Institute (2019) developed a programme of training for bank staff to recognise financial exploitation in older adults and to intervene by reporting it, with 82 participating branches and ultimately 1816 participants (bank staff) allocated to control and experimental groups. The experimental group were much more likely to report abuse and saved $900,915 compared to only $54,384 in the control group. In a study of medical professionals who were trained to recognise financial exploitation a study illustrated a positive view of the programme and 6 months after the programme with 24 of those completing questionnaires (from 67 who agreed to take part in the evaluation) had identified 25 patients vulnerable to financial exploitation (Mills et al., 2012, p 358).

It was noted earlier isolation and mental health issues were associated with increased risk of fraud victimisation. Social prescribing, where individuals are referred to non-clinical services to enhance their well being, such as fitness clubs, arts groups, social groups to name some, have been identified as a potential solution for some problems with some evidence they have a positive impact, but like so many of the measures already discussed in this section no evidence they impact upon fraud victimisation rates (Cooper et al., 2022).

4. Aims, methods and gap

4.1. Aims and background to research

It is first important to note this research emanates from a research fund from the Economic and Social Research Council (ESRC) (Grant number ES/W011085/1) aimed at developing better relations between the UK and South Korea. The theme the authors secured funding under was ageing and technology. Both countries have ageing populations and South Korea is considered be one of the most advanced countries in technological innovation (Dayton, 2020). These countries therefore provided a useful contrast to explore the different measures that have developed to prevent fraud against older adults. The aim of this paper was not comparison, but using these two countries as the starting point to map measures and tools to prevent fraud. As the exercise developed strategies from other countries were noted which were not in use in the UK or South Korea, which were also added to the database. The main aims of this paper were:

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  to map the products and strategies which are used to prevent fraud against older adults (or frauds they frequently are victims of);

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  to secure any evidence that they may work;

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  and to assess their technological development.

4.2. Methods

To achieve these aims a variety of methods were undertaken. First of all, a literature review was conducted seeking research related to fraud prevention specifically for older adults and then more widely relating to prevention directed at frauds that older adults often are victims of. This review noted a wide range of strategies and these were then used to partly populate an Excel sheet of known schemes preventing fraud, with particular reference to older adults. As was noted earlier in the literature review only a small number of studies were found evaluating fraud prevention in general and even less for older adult frauds. The only attempt at mapping a wide range of fraud prevention tools for individual victims was the Button and Cross (2017) study. This literature review confirmed a clear gap in the literature.

Alongside the literature review the researchers visited some of the websites of key organisations working with older adults or the prevention of fraud, such as Age UK, Action Fraud, Cifas to name some. Various Google searches were also conducted using search terms such as ‘fraud prevention’, ‘scam prevention’, ‘phishing prevention’, ‘cybercrime prevention’, ‘call blockers’ etc. Every time a scheme or product was found it was noted in the database with a variety of entries to describe and classify the scheme/product. Particularly for commercial products once a reasonable sample and range were identified no further additions were made. For example, anti-virus products are offered by multiple companies and there was little need in this project to find all providers, rather it was just important to note one as representative of many such products. All distinct products and schemes found were noted in the database. As was established earlier this project started from the basis of exploring the UK and South Korea. The search, however, led the authors to other schemes and products in other countries, particularly the USA which were not found in the two countries. These were also added. In total the researchers identified 106 schemes and products which are directed either specifically at fraud prevention against older adults or a fraud they are victims of in significant numbers. The following results section will explore these schemes and products in more depth.

4.3. Fourth industrial revolution

Before this analysis is presented, however, it is also important to briefly explore the concept of the fourth industrial revolution (4IR). The reason for this is the researchers were particularly interested in the extent to which the technologies associated with 4IR are being applied to fraud prevention. Schwab (2017) argues the first industrial revolution was associated with steam power and mechanisation; followed by the second where electrical power was utilised on a mass scale; and the third industrial revolution which was characterised by electronics and informational technology applied to automation. Building upon the third industrial revolution Schwab (2017) argues there is a 4IR occurring encompassing significant advancements in technology, proceeding at pace, around three broad areas:

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  Physical: autonomous vehicles, 3 d printing, advanced robotics, drones and new materials.

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  Digital: ‘the internet of things’, block-chain, big data, artificial intelligence etc

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  Biological: genetics, synthetic biology (Schwab, 2017).

The researchers were particularly interested, given South Korea is at the forefront of some of these technologies, which of these new and developing technologies were being directed at fraud prevention, particularly older adults (Chung and Kim, 2016). The subsequent analysis therefore also considers the level of technology involved in some of the preventative techniques.

5. The methods of prevention

There have been a variety of attempts at classifying crime prevention, with one of the most famous Clarke's 25 techniques of prevention, which under five broad categories of: increasing the effort, increasing the risk, reducing rewards, reducing provocations and removing excuses unfold another 5 categories each (Smith and Clarke, 2012). Measures found in this research can be mapped into the categories, but many are left blank, such as reducing provocations and assisting compliance, because Clarke's scheme is orientated towards many volume crimes undertaken by opportunistic offenders. While such an approach may work for workplace frauds where there are many potential opportunistic offenders, individual frauds against older adults are often perpetrated by organised crime groups and dogged fraudsters (often based abroad) determined to be successful, so measures which assist compliance are redundant (see Button et al., 2023a, Button et al., 2023b). One of the aims of this project was also to explore technological solutions linked to the 4IR to preventing fraud, so this was an important element in the classification the authors have created.

The sections below explore the variety of schemes and products found preventing frauds against older adults specifically or more generally for frauds they tend to be targeted with. It explores in three parts largely according to the degree of technology utilised before a brief examination of partnership. Some common measures which often illustrate strong resilience to fraud, such as strong family networks were beyond the scope of this research. Included in the table is also a note on evidence of whether they work. As was noted earlier the Maryland scale offers a means to evaluate whether measures have an impact on fraud. Some measures had no such evidence, others had indirect evidence. For example, there have been studies to evaluate whether spam detection works in preventing unwanted emails, but these do not demonstrate whether they reduce fraud – although one could infer that it is likely. These nuances in evidence of whether they work are explored in the figures below. Where there are websites listed in the tables all have been saved at Button et al. (2024) should they no longer be live.

5.1. Traditional products and solutions rooted in traditional crime prevention with limited use of modern technology

The researchers identified a variety of products and schemes which used very little technology and could be considered as rooted largely in the technologies and modus operandi of the first and second revolutions. This included physical products such as stickers, spyholes, awareness raising measures rooted in letters, leaflets and public meetings; and the use of staff who interact with older adults to look out for older adults. These initiatives are very common in more general crime prevention too, such as locks, shutters, awareness through to neighbourhood watch to name some. This section sets out some of these measures applied to frauds against older adults using four sub-divisions: physical crime prevention, traditional crime prevention, awareness raising measures and non-technological applications applied by third parties. Fig. 1 begins this section exploring some of the physical measures which are used of where there is no high quality evidence any of them work.

Fig. 1. Traditional physical crime prevention applied to fraud.

The next set of strategies and tools are also low tech, but not actual physical products in Fig. 2. They include a range of strategies which are used with and by individuals to try and prevent fraud victimisation. Visiting victims and potential victims to conduct a risk assessment relating to fraud and then implement a variety of strategies to reduce the risk is one example of such a scheme. There are also examples of trusted trader schemes where lists of vetted and reputable service providers are provided and then older adults (or others) can choose to use these, reducing the risk of experiencing a rogue trader. Another traditional method is the provision of a service to block junk mail – although this is unlikely to stop determined fraudsters who may secure list of potential victims through other means. There are also services where mail can be redirected so that mail can be vetted. This is usually for older adults who have significant dementia. Also listed is social prescribing which tackles problems such as mental health and isolation, which indirectly – given the links to fraud – provides a form of social crime prevention. With these strategies, other than Project Sunbird and social prescribing there is not much research evidence to show they have a real impact on fraud. This figure also includes some measures discussed earlier which have been evaluated such as warning victims and training bank staff to recognise fraud.

Fig. 2. Traditional crime prevention applied to fraud (Cooper et al., 2022; Cross, 2016b; AARP Public Policy Institute, 2019; Boyle, 2020; Fenge and Lee, 2018; Gunther and Teaster, 2019; Harries et al., 2014; HM Government, 2021; Mills et al., 2012; Oliveria et al., 2016; Payment systems Regulator, 2024).

One of the most common forms of methods used to prevent fraud are awareness and behaviour change related schemes. Multiple examples of these were found, with also a much stronger body of research evaluating them. The component parts are listed below, but some of these use overlapping strategies from both Fig. 3 and other figures in this section. Apart from helplines there is a body of research evidence showing positive results (noted earlier), but the context and nature of the delivery is important.

Fig. 3. Awareness and behaviour related prevention schemes targeted at fraud Protection using modern technologies to prevent fraud (AARP, 2003; Abu-Nimeh et al., 2007; Age UK, n.d.; Allen, 2000; The Board of The International Organization of Securities Commissions, 2015; Shadel et al., 2010; Government events, 2021).

5.2. Protection using modern technologies to prevent fraud

Fraud has also spawned a variety of largely electronic based solutions of varying sophistication to target frauds too. These are based more upon technologies associated largely with the third industrial revolution. They include technologies such as personal alarms linked to communication systems, call blockers rooted in blocking calls not on a customer's list or suspect numbers that have been reported and video door bells. There are also products and services that enable the management of personal data (to reduce identity fraud), services that provide general alerts, warning lists, services that apply additional checks to accounts and payment cards/accounts with built in monitoring restrictions (see Fig. 4).

Fig. 4. Protection using modern technologies to prevent fraud (National Trading Scams Team, 2020; Rosenorn-Lanng and Corbin-Clarke, 2020).

5.3. Protections using 4IR technologies to prevent fraud

The final category covers those products and schemes rooted in technologies associated with the 4IR. The assessment of products and schemes found most of these were rooted in using some of the advancing data-analytics linked to artificial intelligence, big data etc. Some of these are ubiquitous general products targeted at individuals such as spam detection, anti-virus. Others use data to tailor more personalised alerts to individuals. Some of these services are provided by organisations which enable individuals to use, such as Scamadvisor, which is website rooted in sophisticated data analytics to rate the potential risk of fraud of shopping websites. Many of the products are directed at organisations such as banks and retailers and are aimed at using data to protect their clients from frauds such as credit card frauds and identity frauds (see Fig. 5).

5.4. Partnerships to prevent fraud

Given mainstream crime prevention is dominated by partnerships (Gilling, 2013) it was interesting that very little evidence of strong partnerships to deal with frauds against individuals and older adults was found (Homel and Brown, 2017). A few examples are noted in Fig. 6.

Fig. 5. Protections using 4IR technologies to prevent fraud (Abu-Nimeh et al., 2007; Khonji et al., 2013; Post and Kagan, 1998; Sukwong et al., 2011).

Fig. 6. Partnerships to prevent fraud.

6. Towards a holistic prevention model

This paper has identified some of the many strategies and tools which are used to prevent frauds that older adults are frequently victims of the paper has also explored any evidence of their effectiveness and in doing so highlighted there is a lack of high quality evaluations that meet Maryland level standards. Instead there are some tools and strategies with no evidence at all that they work and others with indirect evidence, such as strategies which stop linkages between offender and victim, such as call blockers and anti-spam detection systems, but which still lack evidence of impact on fraud victimisation against older adults. Evaluation is not the only research gap, there is also little evidence of the extent to which some of these different measures are used.

An important question that arises is do we need to know to a very high standard if something works? The answer has to be ideally yes, but quality evaluations cost money and fraud is rarely an issue that has abundant funding. Having a body of evidence as to whether measures work, even if weak is better than nothing. There are also theoretical observations that can be made, such as routine activity theory, to develop prevention strategies with some confidence. Nevertheless, it is important more work on evaluation is undertaken and as strategies are proven or unproven and then strategies that are applied are adapted according to this.

This paper has also highlighted the technological basis of different measures and products. It has shown a dominance of activities rooted in traditional crime prevention techniques and low tech. Evidence of high technology solutions rooted in the 4IR were found in both the UK, South Korea and other countries. Again, the extent of their use is difficult to determine, but there would clearly be more scope for products and services to embrace 4IR. There are also opportunities for more debatable practices to be considered such as reverse scamming to identify high risk individuals and then work with them.

Drawing upon the analysis of strategies leads us to propose the following holistic prevention model for older adults (see Fig. 7). The absence of extensive high quality evidence strategies and tools work has led us to add all of them into this model, but grouped under specific targets for action: the individual, government/law enforcement and organisational context. It also identifies where the basic building blocks of 4IR could be applied to produce even more effective tools and services. Such is the diversity and extent of different measures we do not claim the totality of measures or identify all the 4IR opportunities, but we are confident of noting the most important. We use an example of an older adult living alone with limited use of modern technology such as online shopping and banking, but this could be adapted for other types of individual. It sets out an ideal approach and identifies potential solutions not yet been delivered, but where there is the potential with technology to develop. The model is divided into four parts centred on the potential older adult.

Fig. 7. The older adults holistic prevention model.

The first focuses upon individual older adults and the starting point is understanding risks and protections. The individual alone – using appropriate resources or with the help of a professional should conduct a risk assessment related to frauds and scams. They should engage in Continuous Scam Awareness (CSA) by attending relevant training, reading appropriate materials in leaflets, websites etc of appropriate bodies and they should receive alerts on the latest scams. More personalised alerts should also be pursued suited to the individual's needs and activities. These already exist for paying customers in relation to mobile phone calls, emails, credit files and financial transactions. But there are opportunities to develop these even further by relevant bodies sharing data, utilising AI and tailoring to individuals (see third part of model). So, for example in the future emerging intelligence of a particular investment scam, could be addressed by warnings which could be disseminated to those who are most likely to buy such investments based upon AI. Another example could be a person online shopping and they visit a website and are notified this is a high risk of scam as soon as they arrive.

The second part of the model is protecting the physical and digital habitus of the older adult. Many of these products already exist, but there is also the potential to further enhance with technology. A video doorbell for example could be further enhanced to conduct facial recognition of a visitor or assess their identify card to check their validity. There are already facial recognition services for retailers to deal with shoplifters (see https://www.facewatch.co.uk/facial-recognition-for-retail-sector/ ), so an offender who defrauded an older adult on the doorstep, whose image is captured could be placed on the system. Their face could then automatically trigger a warning and even a call to the police. Wearable personal alarms which are used for health and safety reasons too, could also aid protection. For the very vulnerable such devices could transmit audio conversations which are analysed by AI for phrases in conversations which could be a risk, triggering a response.

Call blockers have been discussed above and clearly have a use, but they could be even smarter. The movement to digital landlines and greater use of mobile provides much more opportunity for applications to block/warn calls based upon AI based data analysis. The scope for conversations to be monitored too with trigger phrases prompting warnings and/or termination of a call or intervention of a trusted third party. Communication has also become much more diverse with systems like Zoom, Whatsapp etc and these need to be covered too. Anti-virus and spam filters are already very advanced and it is important older adults have these too and are up-to-date when they use such technologies. Encouraging the use of websites such as Scamadvisor and developing these to the next level so the analysis is automated and covers other services is another opportunity. For the most vulnerable in society, such as those suffering significant cognitive decline third party (partner, family, friends, professionals) monitoring and control of accounts is an important tool.

Finally, individuals who are alone or lonely – given the risk this creates for fraud – should be encouraged and helped to participate in social events. They should also be encouraged to discuss concerns within their social networks related to scams and particularly any unusual approaches they may have received. Taken together these provide for a well protected individual, but there are other important parts to the model.

The second part of the model is the role of community through the police, NGOs and the government. The activities proposed in this part vary in who has responsibility in different countries, but whoever is responsible these are the important elements. It is important to understand in a community who are the vulnerable who might fall for frauds and understand the risks. Agencies need to find these people and work with them. Some will not know how to do a risk assessment and this is where agencies can help too in advising on appropriate measures to reduce risks. Earlier it was noted the importance of training individuals who work with older adults to spot signs of vulnerability and report and this is an important part of this process. Cross's (2016b) research illustrates how important it is to also alert potential victims and the intelligence gathered by agencies can be used to do this when evidence meets appropriate thresholds.

Another aspect of this model is improving the understanding of the risks and ways to protect. Central to this is fraud awareness training utilising actual training, presentations, websites, leaflets, videos etc. It is important the advice is appropriate and tailored to the appropriate demographics. Generic (and where possible tailored) alerts of emerging frauds should also be provided based upon the latest intelligence. Lists of traders who meet certain standards should also be disseminated to older adults to make informed choices and those lists should be policed so unethical behaviours lead to removal. More controversially it might be appropriate to reverse scam in certain contexts to find those more at risk and then try and work with them. Agencies can also try to help individuals enhance their physical and digital habitus. The resources of older adults vary and some will need help to purchase products to protect them such as call blockers, video doorbells etc.

Communities should also work together to support social activities (subsidizing where appropriate) and provide social prescribing services. Governments and other relevant bodies should also pursue regulations which reduce fraud risks. The final part has not really been the focus of this article, but it would be wrong to not note strategies such as disrupting fraudsters (closing websites, bank accounts etc) and catching and then applying appropriate sanctions after prosecution to aid specific and general deterrence.

The third part of the model related to the companies that provide services which are used for frauds, most notably the financial institutions, telcos and tech companies. The research for this paper revealed many initiatives already occurring to reduce fraud and therefore is so much more potential for these companies to protect their customers from fraud. As with communities the starting point has to be the finding of vulnerable clients, which can be done through a variety of means. An important element of this for the banks is educating staff who deal with customers to intervene – as noted earlier a proven strategy (AARP Public Policy Institute, 2019). There are then, in these types of companies multiple opportunities to use data and AI to identify risky transactions, interactions, customers and vendors. These can be used to block and warn, sometimes not even involving the customer and potential victim – creating unseen protection. Much of this is already occurring, but more could happen, such as sharing of data on vulnerable older adults. For example, if banks had real-time access to mobile phone or internet activity of a client this could be very useful. A customer who is trying to pay a new person who at the same-time or hours before has been on a phone-call with a number the telco deems high risk, should provoke an intervention from the bank. There are of course huge privacy implications, but the potential of data-sharing with AI is huge. Like the second part of the model dedicated at community measures there is also scope for companies to also improve understanding of the risks and to disrupt fraudsters.

The final part of the model advocates partnership, co-ordination and data-sharing between the organisations in the community and private entities. This research has uncovered multiple agencies doing work to prevent fraud against older adults. In the UK this includes the many police forces, local authority trading standards departments, social work departments, healthcare providers, NGOs like Cifas, UK finance, Age UK and Reengage, many banks, tech companies and Telcos to name some. There is limited national and local level partnerships, data-sharing and co-ordination. There are often slightly different messages in awareness campaigns, different approaches and lack of data-sharing, with organisations working alone in a silo or small group of silos. If a bank identified a vulnerable client, it would be highly beneficial to share that data with other appropriate agencies, so the police or NGO visit undertake a risk assessment, provide awareness and training and relevant products and other companies are alerted to the risk with this person. Campaigns and guidance should be similar and co-ordinated. So central to the success of this model are also structures that facilitate greater partnership and a national and local level, which then lead to greater co-ordination and data-sharing.

7. Implications and limitations

It is important to note the limitations of this research. Noted throughout this paper is the lack of high quality evidence of whether tools and strategies work in preventing fraud in general and against older adults in-particular. An extreme perspective could have been if there is no evidence they work, don't recommend them. This would have left a very thin number of strategies. In the absence of this evidence base the authors have tried to bring all of the strategies together targeting the three key areas: individual, community and organisations. The authors are firmly of the belief it is better to do this than advocate only those that have been proven to work because of the importance of protecting this group. The implications of the findings from this paper and the model are the need for much more research and evaluation of the different measures used to prevent fraud, using high quality methodologies. As this is the first paper the authors are aware of linking all available strategies together, another implication is to expose practitioners to the diversity of tools they can use. It is highly likely many practitioners do not know the full tool-box available. The final implication is the finding of limited use of the latest technologies associated with 4IR. This paper has identified some areas where greater innovation could be applied. There are likely to be many more. Much more investment in technical innovations applied to the problem of fraud against older adults needs to be explored, developed and evaluated.

8. Conclusion

This paper has explored the prevention of fraud against older adults. The paper began by illustrating the scale, challenge and impact of fraud on older adults. The small research base of studies that have evaluated fraud prevention measures either directed at older adults or for frauds they tend to be victims of, was then considered. After outlining the methodology of the paper it then set out the first comprehensive assessment of the many tools and strategies used to prevent frauds that older adults are often victims of along with any evidence if they work and their degree of technical sophistication. From the many tools and strategies identified this paper they were then linked together to produce a holistic prevention model for preventing fraud against older adults rooted in three key parts: the individuals themselves, their communities and the companies that provide services to them which are conduits for fraud. This model is not set in stone and as new strategies and technologies emerge it should be adapted, particularly where high quality evidence of effectiveness emerges. Measures that work should become more prominent and those that don't should be dropped. The model will be useful to law enforcement, those agencies working with older adults and policy-makers, as well as companies offering services to older adults where frauds occur (banks, telcos etc) and those developing tools to tackle this fraud. The evidence is fraud is growing and in ageing societies the number of older adults is getting bigger. It is vital adequate prevention is applied to protect these (and all) citizens.

Introduction

Fraud against individuals has become a major crime risk in many industrialized nations. For example, in England and Wales, fraud made up 41% of all reported crime in the year ending September 2022. While older adults are often seen as highly vulnerable, crime surveys indicate they are not always the group most frequently victimized. However, research and personal accounts highlight the devastating effects of fraud on some older individuals. Although many efforts exist to prevent fraud generally, and especially against older adults, a complete overview of these prevention methods has been lacking.

This document aims to provide the first classification of various tools and strategies used to prevent fraud targeting older adults. It considers the level of technology involved in these methods, including sophisticated technologies. The research focuses on the United Kingdom and South Korea, both countries with aging populations and significant fraud issues. The classification also notes any available evidence regarding the effectiveness of these prevention methods. The document concludes by proposing a comprehensive model for preventing fraud against older adults.

The discussion begins by detailing the problem of fraud affecting older adults. It then examines existing literature on fraud prevention measures, particularly those relevant to this age group. Following a description of the research methods, a wide range of fraud prevention schemes and products are identified and grouped based on their technological sophistication, with reference to the Fourth Industrial Revolution. The document concludes by outlining a complete model for fraud prevention tailored for older adults.

Older Adults, Fraud, and Prevention

Data from England and Wales shows fraud victimization rates among older adults between 2019 and 2022. While the overall victimization rate was 7.8% in 2022, the 45-54 age group had the highest risk at 9.3%. However, the 65-74 and over 75 age groups experienced the largest increases in victimization, rising by 58.4% and 61.8% respectively during this period, possibly due to the impact of the pandemic.

Losses to Fraud

Although older adults may not be the most frequently victimized, they tend to experience greater financial losses. Data shows that average losses from fraud increase with age, with individuals aged 65-74 and 75+ losing the most. For many, these losses are harder to recover from due to fixed incomes like pensions.

Frauds and Scams

Fraud and scam are terms often used to describe deceptive actions leading to financial loss. While sometimes used interchangeably, some define scams as unethical but lawful deceptions, whereas fraud is always unlawful. Financial abuse is another related term, generally referring to the improper or illegal use of an older person's money or resources, often by family members, caregivers, or professionals. Cybercrime is a broader concept, encompassing economic, psychosocial, and state-sponsored digital crimes. This discussion focuses on economic cybercrimes, frauds, scams, and financial abuse.

Common methods used to defraud older adults include doorstep frauds by rogue tradesmen, financial abuse by those close to them, telephone scams involving high-pressure sales or impersonation, postal scams using fake lotteries, and Authorized Push Payment (APP) fraud where victims are tricked into sending money directly to criminals. Identity fraud and various cyber-frauds via email, internet, and social media are also frequent. The shift of many older adults to new technologies during the Covid-19 pandemic has also created more opportunities for these crimes.

Many older adults are attractive targets for fraudsters due to their savings, retirement funds, and investments. Certain characteristics can also increase their risk, such as cognitive impairment, health problems, living alone, loneliness, and limited social networks.

Fraud Prevention Literature

This document identifies many initiatives designed to prevent frauds and scams against older adults. However, there is very little high-quality evaluation of these schemes. Despite the growing problem of fraud, there are few well-documented studies demonstrating effective anti-fraud strategies. Much of the existing literature focuses on describing the problem, victim characteristics, and offender patterns, with less attention to applied prevention projects.

Many studies on fraud prevention target organizational or financial statement fraud. The strategies for preventing fraud against older adults often lack strong evidence of their effectiveness in actually preventing fraud. This does not mean they are ineffective, but rather that scientific proof is often missing. High-quality evidence typically involves rigorous evaluations, such as assessments before and after an intervention, or randomized control trials. While such methods are common in other crime prevention fields, they are rarely used in fraud prevention research.

Instead, many fraud prevention studies rely on other forms of evaluation, such as literature reviews, interviews with professionals or offenders, experiments with participants, analysis of existing datasets, or surveys comparing victims and non-victims. One common initiative is fraud awareness training, which aims to help individuals recognize and avoid scams. Evaluations of these programs, such as one by Age UK, have shown positive results in increasing awareness and feelings of safety, but they did not measure an actual reduction in victimization rates. Other research suggests that awareness efforts may benefit better-educated and more financially secure individuals more. Tailored messaging, real-life case studies, and advice to avoid rushed financial decisions have also been suggested as effective.

Some prevention efforts involve deeper training, such as programs where potential victims receive training and are then tested with simulated scams. For example, in one study, individuals who received investment fraud training were less likely to provide information to a fake telemarketer than those in a control group. "Reverse boiler rooms" and similar techniques have also been used, where authorities conduct fake scam calls or send fake phishing emails to test susceptibility and then offer help to those who fall for them. In Australia, "Project Sunbird" involved police writing to potential victims identified by financial intelligence, which resulted in a high percentage of recipients stopping payments to fraudsters.

Call blockers are another tool used to prevent telemarketing fraud. Evaluations of certain call-blocking technologies have shown high success rates in blocking scam and nuisance calls, leading to increased feelings of happiness among users. While these studies show clear benefits, they do not directly prove a reduction in actual victimization rates, although it can be inferred that fewer opportunities would lead to fewer victims.

Another important intervention is specialized training for professionals who work with older adults, such such as social workers, healthcare workers, and bankers. This training helps them spot potential fraud or financial abuse and intervene or report it. A large study on bank staff training showed a significant increase in abuse reporting and a substantial amount of money saved for older adults. Studies on medical professionals trained to recognize financial exploitation also reported positive outcomes. Lastly, social prescribing, which connects individuals to non-clinical services like social groups, has been identified as a potential solution for problems like isolation and mental health issues, which are linked to increased fraud risk. While it shows positive impacts on well-being, there is no direct evidence linking it to reduced fraud victimization rates.

Aims, Methods, and Gap

Aims and Background to Research

This research was funded by the Economic and Social Research Council (ESRC) to foster better relations between the UK and South Korea, focusing on aging and technology. Both nations have aging populations, and South Korea is technologically advanced, offering a useful contrast to explore different fraud prevention measures for older adults. The main goals of this document were to classify products and strategies used to prevent fraud against older adults, identify any evidence of their effectiveness, and assess their technological sophistication. The project expanded beyond the UK and South Korea to include strategies from other countries, notably the USA, that were not found in the initial two.

Methods

Various methods were employed to achieve these aims. A literature review identified research on fraud prevention, specifically for older adults or frauds they commonly experience. This review confirmed a gap in existing knowledge regarding comprehensive mapping of prevention tools, with previous attempts being less detailed. Researchers also visited websites of key organizations involved in elder care or fraud prevention and conducted numerous online searches using relevant terms. Any found scheme or product was recorded in a database, with details for description and classification. For commercial products, a representative sample was collected rather than an exhaustive list of all providers. In total, 106 distinct schemes and products focused on fraud prevention for older adults were identified.

Fourth Industrial Revolution

Before presenting the analysis, it is important to understand the concept of the Fourth Industrial Revolution (4IR). The first industrial revolution involved steam power and mechanization, followed by the second with mass-scale electrical power, and the third with electronics and information technology leading to automation. Building on the third revolution, the 4IR represents rapid advancements across three main areas: physical (e.g., autonomous vehicles, 3D printing), digital (e.g., Internet of Things, big data, artificial intelligence), and biological (e.g., genetics). Given South Korea's leadership in some of these technologies, the researchers were particularly interested in how these new technologies are applied to fraud prevention, especially for older adults. The subsequent analysis therefore also considers the technological level of prevention techniques.

The Methods of Prevention

Various attempts have been made to classify crime prevention. This research's findings can be mapped onto some existing frameworks, but many specific measures, like those designed to assist compliance, do not fit well because fraud against individuals is often perpetrated by organized, determined criminals. A key aim of this project was to explore technological solutions, particularly those linked to the 4IR, for fraud prevention.

The following sections categorize various schemes and products used to prevent fraud against older adults, or frauds they frequently experience. The categorization largely depends on the level of technology used, followed by a brief examination of partnerships. While important, factors like strong family networks, which often provide resilience against fraud, were beyond this research's scope. The effectiveness of these measures is also noted. As mentioned earlier, high-quality evaluations of fraud prevention methods are rare. Some measures have no evidence of impact, while others have indirect evidence, such as stopping unwanted communications (e.g., call blockers), but without direct proof of reducing actual victimization.

Traditional Products and Solutions with Limited Use of Modern Technology

A variety of products and schemes identified use minimal technology, similar to approaches from earlier industrial revolutions. These include physical products like stickers and spyholes, awareness campaigns delivered via letters, leaflets, and public meetings, and the use of staff who interact with older adults to watch for warning signs. These are common in general crime prevention, similar to locks or neighborhood watch programs. This category covers physical crime prevention, traditional crime prevention, awareness-raising measures, and non-technological applications by third parties. Examples include trusted trader schemes, mail redirection services for vulnerable individuals, and social prescribing to address isolation. For most of these, direct research evidence of impact on fraud is limited.

Protection Using Modern Technologies to Prevent Fraud

Fraud has also led to many electronic solutions, primarily based on technologies from the third industrial revolution. These include personal alarms linked to communication systems, call blockers that filter numbers based on approved lists or reported suspects, and video doorbells. Other products and services manage personal data to prevent identity fraud, provide general alerts, offer warning lists, or apply additional security checks to accounts and payment cards with built-in monitoring restrictions.

Protections Using 4IR Technologies to Prevent Fraud

The most advanced category includes products and schemes rooted in technologies associated with the Fourth Industrial Revolution, primarily using advanced data analytics linked to artificial intelligence and big data. Some are common general products for individuals, like spam detection and antivirus software. Others use data to provide tailored, personalized alerts. Some services, such as "Scamadvisor," use sophisticated data analytics to rate the potential fraud risk of shopping websites. Many products in this category are designed for organizations like banks and retailers to protect clients from frauds such as credit card fraud and identity fraud using data analysis.

Partnerships to Prevent Fraud

While mainstream crime prevention heavily relies on partnerships, this research found very little evidence of strong, coordinated partnerships dedicated to tackling individual fraud, particularly against older adults. Despite the existence of many agencies working on the issue, examples of comprehensive collaboration remain limited.

Towards a Holistic Prevention Model

This document has identified numerous strategies and tools used to prevent frauds targeting older adults. It highlights a general lack of high-quality evaluations that meet rigorous standards. Consequently, some tools and strategies have no direct evidence of effectiveness, while others offer only indirect evidence, such as preventing contact between offender and victim, without proving a reduction in actual victimization. There is also limited information on how widely some of these diverse measures are used.

While it is ideal to have strong evidence of effectiveness, quality evaluations are costly, and fraud prevention often lacks sufficient funding. However, even weak evidence is better than none. Theoretical approaches, such as routine activity theory, can also help develop prevention strategies with some confidence. Nevertheless, more evaluation work is crucial, so that strategies can be adapted based on proven or unproven results.

The paper also shows that many measures are rooted in traditional crime prevention and low-tech solutions. While evidence of high-technology solutions from the 4IR was found in the UK, South Korea, and other countries, their overall extent of use is difficult to determine. There is significant potential for more products and services to incorporate 4IR technologies. Controversial practices, such as "reverse scamming" to identify high-risk individuals for targeted intervention, could also be considered.

Based on this analysis, a comprehensive prevention model for older adults is proposed. Given the absence of extensive high-quality evidence, all identified strategies are included and grouped into specific targets for action: the individual, government/law enforcement, and organizational contexts. The model also suggests how 4IR technologies could enhance existing tools and services. While not exhaustive, it highlights the most important measures. An example of an older adult living alone with limited technology use is provided, but the model can be adapted for various situations. It outlines an ideal approach, identifying both existing solutions and future possibilities with technology. The model has four main parts, centered on the older adult.

The first part focuses on individual older adults, starting with understanding risks and protections. Individuals, either alone or with professional help, should conduct fraud risk assessments. They should engage in continuous scam awareness by attending training, reading materials, and receiving alerts on the latest scams. More personalized alerts, already available for paying customers regarding calls, emails, and financial transactions, could be further developed through data sharing and AI to tailor warnings based on an individual's specific needs and activities. For instance, AI could disseminate warnings about specific investment scams to those most likely to fall victim, or notify an online shopper about a high-risk website instantly.

The second part of the model concerns protecting the older adult's physical and digital environment. Many protective products already exist but could be enhanced with technology. For example, video doorbells could use facial recognition to identify visitors or verify identity cards, potentially triggering warnings or police calls if an image matches a known fraudster. Wearable personal alarms, used for health and safety, could also aid protection. For very vulnerable individuals, these devices could transmit audio conversations analyzed by AI for risky phrases, prompting a warning or intervention by a trusted third party. Call blockers are useful but could be smarter; the shift to digital landlines and mobile phones offers more opportunities for AI-based blocking and warning applications. Communication platforms like Zoom and WhatsApp also need coverage. Antivirus software and spam filters are crucial and must be kept up-to-date. Websites like Scamadvisor should be encouraged, and their analysis capabilities automated and expanded to other services. For the most vulnerable, third-party monitoring and control of accounts by partners, family, friends, or professionals is a vital tool. Encouraging social participation and discussion about scams within social networks also enhances well-being and protection.

The third part of the model involves the role of communities, including police, non-governmental organizations (NGOs), and government bodies. Responsibilities vary by country, but essential elements include identifying vulnerable individuals, helping them assess risks, and advising on protective measures. Training professionals who work with older adults to spot signs of vulnerability and report concerns is critical. Gathering intelligence to alert potential victims, as demonstrated by previous research, is also important. Improving understanding of risks and protection methods through awareness training, presentations, websites, and generic or tailored alerts based on the latest intelligence is key. Disseminating lists of vetted traders helps older adults make informed choices, with ethical policing ensuring their reliability. More controversially, reverse scamming could identify those most at risk for targeted intervention. Communities should also support social activities and social prescribing services, and governments should pursue regulations to reduce fraud risks. Finally, disrupting fraudsters (e.g., closing websites, freezing bank accounts) and applying appropriate sanctions after prosecution are vital for deterrence.

The fourth part of the model focuses on companies providing services used in frauds, particularly financial institutions, telecommunication companies (telcos), and tech companies. Many initiatives already exist to reduce fraud, and there is significant potential for these companies to enhance customer protection. Finding vulnerable clients is a crucial starting point. For banks, training staff to intervene when they suspect financial exploitation is a proven strategy. These companies also have numerous opportunities to use data and AI to identify risky transactions, interactions, customers, and vendors. This can lead to blocking or warning actions, sometimes without direct customer involvement, creating "unseen protection." While much of this is already happening, more could be done, such as sharing data on vulnerable older adults. For example, if banks had real-time access to a client's mobile phone or internet activity, an attempted payment to a new person after a high-risk phone call could trigger an intervention. While privacy implications are significant, the potential for AI-driven data-sharing is immense. Like community measures, companies also have scope to improve risk understanding and disrupt fraudsters.

The final element of the model advocates for partnership, coordination, and data-sharing among community organizations and private entities. This research revealed many agencies working on fraud prevention in the UK, including police, local authorities, social work departments, healthcare providers, NGOs, banks, tech companies, and telcos. However, national and local partnerships, data-sharing, and coordination are limited. Awareness campaigns often have differing messages, approaches vary, and organizations frequently operate in silos. If a bank identifies a vulnerable client, sharing that data with relevant agencies (police, NGOs) would be highly beneficial, allowing for risk assessments, awareness training, provision of protective products, and alerts to other companies. Campaigns and guidance should be harmonized and coordinated. Therefore, structures facilitating greater partnership, coordination, and data-sharing at both national and local levels are central to this model's success.

Implications and Limitations

It is important to acknowledge the limitations of this research. As noted throughout, there is a lack of high-quality evidence regarding the effectiveness of many fraud prevention tools and strategies, both generally and specifically for older adults. An extreme approach might be to recommend only proven strategies, but this would leave very few options. In the absence of such an evidence base, this document has sought to bring together all strategies, targeting three key areas: the individual, the community, and organizations. The belief is that it is better to propose a comprehensive set of measures, given the importance of protecting this vulnerable group.

The implications of these findings and the proposed model include the urgent need for more research and evaluation of different fraud prevention measures using high-quality methodologies. As this is likely the first paper to connect all available strategies, another implication is to expose practitioners to the diverse range of tools at their disposal, as many may not be aware of the full toolkit. A final implication is the finding of limited use of the latest technologies associated with the 4IR. This paper has identified areas where greater innovation could be applied, and many more opportunities likely exist. Significant investment in technical innovations for preventing fraud against older adults needs to be explored, developed, and evaluated.

Conclusion

This document has examined the prevention of fraud targeting older adults. It began by illustrating the scope, challenges, and impact of fraud on this population. The limited research base on evaluated fraud prevention measures, whether specifically for older adults or for common frauds affecting them, was then considered. Following an outline of the methodology, the paper presented the first comprehensive assessment of various tools and strategies used to prevent frauds against older adults, along with any evidence of their effectiveness and their level of technological sophistication.

From the many identified tools and strategies, a comprehensive prevention model for older adults was developed. This model is rooted in three key areas: individuals themselves, their communities, and the companies that provide services which may be exploited for fraud. This model is not fixed; it should adapt as new strategies and technologies emerge, especially as high-quality evidence of effectiveness becomes available. Measures proven to work should become more prominent, while ineffective ones should be discontinued. The model is intended to be useful for law enforcement, agencies working with older adults, policymakers, companies providing services where fraud occurs (like banks and telcos), and those developing tools to combat fraud. As fraud continues to grow and societies age, adequate prevention is vital to protect these and all citizens.

Introduction

Fraud against individuals has become a major crime risk in many developed countries. For instance, in England and Wales, fraud made up 41% of all crimes in the year ending September 2022. While older adults are often seen as particularly vulnerable to fraud, data shows they are not always the group at highest risk of being victimized. However, there is much evidence showing the severe harm fraud can cause to some older adults. This has led to many efforts to prevent fraud, especially against older people. Despite these efforts, there has not been a detailed mapping of the various prevention methods aimed at protecting older adults from fraud.

This document presents the first comprehensive classification of tools and strategies used to prevent fraud against older adults. It specifically looks at how advanced the technology used in these methods is. The research is based on studies from the UK and South Korea, two countries with growing older populations and significant fraud problems. The classification also highlights any evidence showing whether these prevention methods are effective. The document concludes by proposing a model for how these strategies could work together to prevent fraud against older adults.

Older Adults, Fraud, and Prevention

Although older adults may not experience fraud victimization at the highest rates, they tend to lose more money when they are victimized. Data shows that as age increases, the average financial losses due to fraud also increase, with individuals aged 65 and older typically losing the most. Many in these age groups rely on fixed incomes like pensions, making it harder for them to recover from financial losses. Between 2019 and 2022 in England and Wales, fraud victimization rates among those aged 65-74 and over 75 increased significantly, by 58.4% and 61.8% respectively, possibly due to the impact of the pandemic.

Fraud and scams involve deceptive behaviors that result in financial loss. While often used interchangeably, some define scams as unethical but lawful deceptions, whereas frauds are always illegal. Financial abuse, a related term, typically refers to the misuse of an older person's money or resources, often by close family members, caregivers, or professionals. This paper focuses on economic crimes, including frauds, scams, and financial abuse.

Many types of fraud commonly target older adults. These include:

• Doorstep frauds: Rogue traders overcharge for services or perform unnecessary work.

• Financial abuse: Misuse of funds by those close to the older adult.

• Telephone scams: High-pressure sales of worthless goods or services, impersonation scams, and attempts to get sensitive personal information (vishing).

• Postal scams: Fake lotteries, bogus charities, and investment schemes sent through traditional mail.

• Authorized Push Payment (APP) fraud: Victims are tricked into sending money directly to criminals.

• Identity frauds: Impersonators use victims' financial details or identities fraudulently.

• Cyber-frauds: A wide range of scams using email, the internet, and social media.

The COVID-19 pandemic also led many older adults to adopt new technologies, creating more opportunities for fraud and cybercrime. Older adults can be attractive targets for criminals because many have savings, retirement funds, and investments. Some are also more vulnerable due to factors such as cognitive impairment, health problems, living alone, loneliness, or limited social connections.

Fraud Prevention Literature

Many different initiatives have been used to prevent frauds and scams against older adults. However, there is very little high-quality research evaluating the effectiveness of these programs. Researchers have noted a lack of well-documented studies that show successful anti-fraud strategies, with most literature focusing on describing the problem rather than evaluating prevention methods.

Much of the existing fraud prevention research targets organizational fraud rather than individual victimization. Therefore, many strategies and tools aimed at preventing fraud against older adults lack strong evidence that they actually work. This does not mean they are ineffective, but rather that their effectiveness has not been scientifically proven. Evaluations often use less rigorous methods than desired, such as surveys, interviews, small experiments, or existing data analysis, rather than comprehensive "before and after" studies or randomized controlled trials.

One common fraud prevention method is fraud awareness training, which aims to help individuals recognize and avoid scams. Some programs have shown positive results in increasing awareness, improving feelings of safety, and encouraging reporting of scams among older adults. However, these evaluations often do not measure whether the training actually reduces the number of people who fall victim to fraud. Research suggests that those who are better educated and more financially secure may benefit more from awareness campaigns. Messages are often more effective when tailored to specific groups of older adults, focusing on the types of fraud they are most at risk of and delivered through established community networks. Experts suggest using real victim case studies to make awareness campaigns more impactful, and experimental studies indicate that advising potential victims not to rush financial decisions can reduce their risk.

More intensive training programs have also been explored. In one study, individuals who received "Outsmarting Investment Fraud" training were less likely to engage with a fake telemarketer offering an investment three days later compared to a control group. "Reverse boiler rooms" and similar techniques (fake scam calls, emails, or websites) have also been used to test susceptibility after training, showing that response rates to scams could be significantly reduced.

Call blockers are another tool to prevent telemarketing fraud. Devices that block unwanted calls have been shown to stop a high percentage of scam and nuisance calls, leading to increased feelings of happiness among users. While these studies show clear benefits of call blockers, they do not directly prove a reduction in fraud victimization, though it can be inferred that fewer opportunities for scams might lead to less victimization.

Another important intervention involves training professionals who work with older adults, such as social workers, healthcare providers, and bankers, to recognize and report signs of financial exploitation or abuse. A large study found that bank staff trained in this area were significantly more likely to report abuse and saved customers substantial amounts of money compared to untrained staff. Similarly, medical professionals trained to identify financial exploitation also showed positive results. Finally, initiatives like "social prescribing," which connect isolated individuals to community activities, are believed to help reduce risk factors for fraud, such as loneliness and mental health issues, but direct evidence of their impact on fraud victimization rates is currently limited.

Aims, Methods, and Gaps

This research, funded by the Economic and Social Research Council, aimed to improve relations between the UK and South Korea, specifically focusing on aging and technology. Both countries have aging populations, and South Korea is known for its technological innovation. These countries provided a useful context to explore various measures developed to prevent fraud against older adults. The main goals were to identify and map products and strategies used to prevent fraud against older adults, gather evidence of their effectiveness, and assess their technological sophistication.

To achieve these aims, a literature review was conducted to find research on fraud prevention, particularly for older adults. This review highlighted a significant gap in existing literature, as few studies comprehensively mapped fraud prevention tools for individual victims. Researchers also visited websites of key organizations working with older adults or fraud prevention and conducted various online searches. Each time a relevant scheme or product was found, it was added to a database, noting its characteristics and classification. For commercial products, a representative sample was collected rather than every single provider. While the project started by focusing on the UK and South Korea, schemes and products from other countries, especially the USA, were also included if they were not found in the initial two countries. In total, 106 distinct schemes and products aimed at preventing fraud against older adults or frauds they commonly experience were identified.

Before presenting the analysis of these prevention methods, it is important to understand the concept of the Fourth Industrial Revolution (4IR). This concept describes significant, rapid advancements in technology across three main areas: physical (e.g., autonomous vehicles, 3D printing), digital (e.g., Internet of Things, blockchain, big data, artificial intelligence), and biological (e.g., genetics). Given South Korea's leadership in some of these technologies, researchers were particularly interested in how these new and developing technologies are being applied to fraud prevention, especially for older adults. Therefore, the analysis of prevention techniques considers their level of technological involvement.

Methods of Prevention

Various attempts have been made to classify crime prevention strategies. This research found a wide range of products and schemes that prevent fraud against older adults, or against frauds that commonly target them. The strategies are largely grouped by the level of technology used and also briefly examine partnerships. Some measures, like strong family networks that offer resilience against fraud, were beyond the scope of this research.

The first category includes methods using very little technology, rooted in traditional crime prevention. These involve physical products (like stickers, spyholes), awareness campaigns (through letters, leaflets, public meetings), and staff who interact with older adults and are trained to identify potential fraud. Examples include schemes where professionals visit potential victims to assess risks and implement strategies, or trusted trader schemes that provide lists of vetted service providers to reduce the risk of rogue traders. Other traditional methods include services to block junk mail or redirect mail for vetting, particularly for those with significant dementia. Social prescribing, which addresses issues like mental health and isolation, also indirectly contributes to social crime prevention given its links to fraud vulnerability. While some of these measures, such as warning victims and training bank staff, have been evaluated with positive results, many lack strong research evidence of a direct impact on fraud.

A common approach to fraud prevention involves awareness and behavior change programs. These schemes aim to educate individuals about scams and influence their behavior to avoid victimization. While specific helplines are part of these efforts, a larger body of research supports the positive results of many awareness campaigns, emphasizing the importance of context and delivery.

Modern technologies also offer various electronic solutions to combat fraud, mostly associated with the Third Industrial Revolution. These include personal alarms linked to communication systems, call blockers that filter unwanted or suspicious numbers, and video doorbells. Other services help manage personal data to prevent identity fraud, provide general alerts and warning lists, or apply additional checks to financial accounts and payment cards with built-in monitoring features.

The most advanced category covers products and schemes rooted in technologies of the Fourth Industrial Revolution (4IR). Many of these utilize advanced data analytics, artificial intelligence (AI), and big data. Some are general products like spam detection and antivirus software. Others use data to provide personalized alerts, such as websites like Scamadvisor, which uses sophisticated data analytics to rate the risk of shopping websites. Many 4IR-based products are designed for organizations like banks and retailers, using data to protect clients from credit card or identity fraud.

Finally, while mainstream crime prevention often relies heavily on partnerships, there is limited evidence of strong partnerships specifically addressing fraud against individuals and older adults. A few examples exist, but overall, collaboration appears to be less common in this area.

A Holistic Prevention Model

This paper has identified many strategies and tools used to prevent frauds that frequently victimize older adults. It also highlights a general lack of high-quality evaluations that definitively prove the effectiveness of these measures. Some tools have no evidence of impact, while others have indirect evidence (e.g., call blockers stopping unwanted calls, but without proof of reducing actual fraud victimization). There is also limited information on how widely these different measures are used.

Ideally, knowing if a prevention method works is crucial. While high-quality evaluations are costly, and funding for fraud prevention is often limited, having some evidence, even if weak, is better than none. Theoretical frameworks can also help develop prevention strategies with some confidence. Nevertheless, more research and evaluation are needed to adapt strategies based on proven effectiveness. This paper also shows a dominance of traditional, low-tech crime prevention techniques. While some high-tech solutions from the 4IR exist in the UK, South Korea, and other countries, there is significant potential for more products and services to incorporate 4IR technologies. This includes considering more debated practices like reverse scamming to identify and assist high-risk individuals.

Based on the analysis of strategies, a holistic prevention model for older adults is proposed, grouped under specific targets for action: the individual, government/law enforcement, and organizational contexts. This model also identifies where 4IR technologies could be applied to create more effective tools and services. While it does not claim to include every possible measure or 4IR opportunity, it highlights the most important ones. The model considers an older adult living alone with limited use of modern technology but can be adapted for other situations. It outlines an ideal approach and identifies potential solutions that technology could enable, even if not yet fully implemented. The model has four main parts centered on the potential older adult.

The first part focuses on individual older adults, starting with understanding their risks and protections. Individuals, perhaps with professional help, should conduct a fraud risk assessment and engage in continuous scam awareness (CSA) through training, materials, and alerts about new scams. More personalized alerts, tailored to an individual's specific needs and activities, could be developed by sharing data and using AI. For example, future intelligence on an investment scam could lead to warnings for individuals most likely to be targeted based on AI analysis. Or, an individual could be immediately notified of a high-risk scam website while online shopping.

The second part of the model involves protecting the physical and digital environment of the older adult. Many protective products already exist, but technology can further enhance them. For instance, video doorbells could be improved with facial recognition or identity card validation. Images of doorstep fraudsters could be added to a system that triggers warnings or calls to the police. Wearable personal alarms, used for health and safety, could also aid protection by transmitting audio conversations analyzed by AI for risky phrases, prompting a response. Call blockers can become smarter with digital landlines and mobile usage, allowing AI-based data analysis to block or warn about calls. Communication platforms like Zoom and WhatsApp also need coverage. Antivirus software and spam filters are crucial for older adults using technology and should be kept up-to-date. Encouraging the use of websites like Scamadvisor and automating their analysis for other services is another opportunity. For the most vulnerable, such as those with significant cognitive decline, third-party monitoring and control of accounts by partners, family, or professionals is an important tool. Finally, individuals who are alone or lonely should be encouraged to participate in social events and discuss scam concerns within their social networks. Together, these measures create a well-protected individual.

The third part of the model concerns the role of communities, including police, non-governmental organizations (NGOs), and the government. It is important for communities to identify vulnerable individuals and understand their risks, with agencies helping to advise on appropriate risk reduction measures. Training professionals who work with older adults to spot and report vulnerability is also essential. Intelligence gathered by agencies can be used to alert potential victims, as demonstrated by research showing the importance of such warnings. This aspect also involves improving understanding of risks through fraud awareness training (presentations, websites, leaflets, videos), ensuring advice is tailored to demographics, and providing alerts based on the latest intelligence. Disseminating lists of approved traders and policing those lists is also vital. More controversially, reverse scamming could be used in some contexts to identify and work with at-risk individuals. Agencies can also help individuals enhance their physical and digital protection, assisting with the purchase of protective products like call blockers. Communities should support social activities and provide social prescribing services, while governments should pursue regulations that reduce fraud risks. Lastly, strategies like disrupting fraudsters (closing websites, bank accounts) and applying sanctions after prosecution contribute to deterrence.

The fourth part of the model relates to companies that provide services used in frauds, particularly financial institutions, telecommunication companies, and tech companies. Many initiatives already exist to reduce fraud, and there is significant potential for these companies to further protect their customers. Finding vulnerable clients is a starting point, and educating staff to intervene, as demonstrated by studies, is a proven strategy for banks. These companies have many opportunities to use data and AI to identify risky transactions, interactions, clients, and vendors, allowing them to block and warn, often providing "unseen protection" without direct customer involvement. While much of this is already happening, more could be done, such as real-time data sharing on vulnerable older adults. For instance, if banks had real-time access to a client's mobile phone or internet activity, an intervention could be triggered if a client attempts to pay a new person shortly after a high-risk phone call. While privacy implications are significant, the potential of AI-driven data sharing is vast. Like community measures, companies can also improve risk understanding and disrupt fraudsters.

The final element of the model advocates for partnership, coordination, and data-sharing among community organizations and private entities. This research revealed many agencies working on fraud prevention in the UK, but national and local level partnerships, data-sharing, and coordination are limited. Often, awareness campaigns have differing messages, approaches vary, and organizations work in silos. If a bank identifies a vulnerable client, sharing that data with appropriate agencies (police, NGOs) would be highly beneficial, allowing for risk assessment, awareness, training, and the provision of relevant products. Campaigns and guidance should be consistent and coordinated. Therefore, structures that facilitate greater partnership, coordination, and data-sharing at national and local levels are central to the model's success.

Implications and Limitations

It is important to acknowledge the limitations of this research. As noted, there is a lack of high-quality evidence proving whether many tools and strategies are effective in preventing fraud, especially against older adults. An extreme view might suggest only recommending strategies with proven effectiveness, which would leave very few options. In the absence of such strong evidence, this paper attempts to bring all identified strategies together, targeting three key areas: the individual, the community, and organizations. The belief is that it is better to present these strategies than to advocate only for those with robust proof, given the importance of protecting older adults.

The implications of these findings and the proposed model include the need for much more research and evaluation of fraud prevention measures, using rigorous methodologies. As this is the first paper known to link all available strategies, another implication is to inform practitioners about the wide range of tools available to them, as many may not be aware of the full scope. Finally, the research highlights the limited use of the latest technologies associated with the Fourth Industrial Revolution (4IR). This paper identifies areas where greater innovation could be applied, and many more are likely to exist. More investment in technical innovations for preventing fraud against older adults needs to be explored, developed, and evaluated.

Conclusion

This paper has examined fraud prevention specifically for older adults. It began by illustrating the scale, challenges, and impact of fraud on this population. The limited body of research evaluating fraud prevention measures, whether aimed at older adults directly or at common frauds they experience, was then discussed. After outlining the research methodology, the paper presented the first comprehensive assessment of the many tools and strategies used to prevent frauds that frequently victimize older adults, along with any evidence of their effectiveness and their technological sophistication. From these identified tools and strategies, a holistic prevention model for older adults was developed, rooted in three key areas: the individuals themselves, their communities, and the companies providing services that can be used for fraud. This model is adaptable; as new strategies and technologies emerge, especially those with strong evidence of effectiveness, the model should be updated. Measures that prove effective should be prioritized, while those that do not should be discontinued. This model will be valuable for law enforcement, agencies working with older adults, policymakers, companies offering services (like banks and telecommunications providers), and developers of anti-fraud tools. With fraud growing and older populations increasing in aging societies, it is essential to apply adequate prevention to protect all citizens.

Introduction

Fraud against individuals has become a significant crime risk in many developed countries. While older adults are often considered highly vulnerable to fraud, data indicates they may not consistently be the group most frequently targeted. However, older adults tend to experience greater financial losses from fraud, and the rate of victimisation among those aged 65 and above has seen a notable increase in recent years. This rise is partly attributed to factors such as the pandemic, which pushed many older adults to use new technologies. Common methods of fraud include doorstep scams, financial abuse by trusted individuals, telephone scams, postal scams, identity theft, and various cyber-frauds. Older adults can be attractive targets due to savings and investments, and some are at higher risk if they have cognitive impairment, health issues, live alone, or lack social connections. This paper explores the diverse tools and strategies used to prevent fraud against older adults, assessing their effectiveness and the level of technology they involve, particularly in the UK and South Korea.

Prevention Efforts and Their Evaluation

Despite the growing problem of fraud, there is limited high-quality research evaluating the effectiveness of prevention measures, especially those targeting older adults. Many studies lack the rigorous "before and after" assessments needed to definitively prove whether a scheme reduces actual fraud victimisation. Instead, evaluations often show indirect benefits, such as increased awareness of scams, improved feelings of safety, or a reduction in unwanted calls. Common prevention initiatives include fraud awareness training, which can improve an individual's ability to spot scams, and specialized training for professionals (like bank staff) to recognize and intervene in financial exploitation. Tools like call blockers have been shown to significantly reduce nuisance calls, potentially reducing opportunities for fraud, although direct evidence of reduced victimisation is often absent. This research involved reviewing existing literature and examining websites of relevant organizations to identify 106 distinct prevention schemes and products.

Categories of Prevention Methods

The identified prevention methods can be broadly categorized by their technological sophistication. Many methods are traditional, relying on low technology or physical products. These include awareness campaigns delivered through letters, leaflets, or public meetings, as well as physical measures like security stickers and spyholes. Traditional strategies also involve services like trusted trader schemes, junk mail blocking, and in-person risk assessments. A second category involves methods using modern technologies, often associated with the third industrial revolution. Examples include personal alarms linked to communication systems, call blockers that filter unwanted numbers, video doorbells, and services for managing personal data to prevent identity fraud. The most advanced category incorporates technologies from the Fourth Industrial Revolution (4IR), such as artificial intelligence (AI) and big data. These are seen in spam detection, anti-virus software, and tools that provide personalized alerts based on data analytics, like websites that rate the risk of shopping sites. Many 4IR solutions are also used by organizations, such as banks, to detect fraudulent transactions or identity fraud. While numerous measures exist, there is limited evidence of strong, formal partnerships between different organizations to coordinate fraud prevention efforts.

A Holistic Prevention Model

Based on this assessment, a holistic prevention model for older adults is proposed, recognizing the need for comprehensive and coordinated action across multiple fronts. This model emphasizes action in three key areas: the individual, the community, and organizations. At the individual level, it encourages personal risk assessments, continuous scam awareness through training and alerts, and the use of protective physical and digital tools (e.g., smart call blockers, advanced anti-virus, video doorbells potentially enhanced with AI for recognition). It also stresses the importance of social engagement to combat isolation, which is a risk factor for fraud. Within the community, the model highlights the role of law enforcement, NGOs, and government agencies in identifying vulnerable individuals, providing awareness training, supporting social activities, and implementing regulations to reduce fraud risks. For companies—especially financial institutions, telecommunication providers, and technology companies—the model advocates for identifying vulnerable clients, training staff to intervene, and extensively using data and AI to detect and prevent risky transactions, often providing "unseen protection" to customers.

Implications and Conclusion

A significant limitation of current fraud prevention efforts is the widespread lack of high-quality evidence proving their effectiveness in directly reducing fraud victimisation. While indirect benefits are often observed, more rigorous evaluation is crucial. This paper's findings emphasize the need for continued research and investment in assessing existing strategies and developing new ones. There is also a clear opportunity for greater innovation and application of advanced 4IR technologies to fraud prevention, particularly for older adults. This includes the potential for enhanced data sharing, with appropriate privacy safeguards, between different entities like banks and telcos to create more robust, real-time protection systems. Ultimately, effectively preventing fraud against older adults requires a multi-faceted approach. A coordinated effort, involving individuals, communities, and private companies, with robust data sharing and continuous evaluation, is essential to adapt and refine prevention strategies as the threat of fraud evolves in an increasingly aging global population.

Introduction

Being a victim of fraud is a serious problem for people in many rich countries. In England and Wales, a survey in 2022 showed that fraud was 41% of all crimes. Many people think older adults are easy targets for fraud. But studies show they are not always the group most likely to be victims. Still, many stories and studies show that fraud can hurt some older adults very badly. So, many plans have been made to stop fraud, especially for older adults.

However, no one has tried to list all the different ways to protect older adults from fraud. Only one study looked at general fraud prevention methods. This paper aims to list the different tools and ways used to stop fraud against older adults. It will also look at how much technology these tools use.

The study looked at the UK and South Korea. Both countries have many older people and a big fraud problem. The list also shows if there is proof that these methods work. The paper ends by showing how all these ways could work together to stop fraud against older adults.

The paper first looks at why fraud against older adults is a problem. Then it looks at what has been written about stopping fraud, especially for older adults. After explaining how the study was done, the paper lists many plans and products used to stop fraud. These are then put into groups based on how much new technology they use. In the end, the paper suggests a full plan to stop fraud against older adults.

Older Adults, Fraud, and Prevention

Studies show how often older adults in England and Wales were fraud victims between 2019 and 2022. In 2022, about 7.8% of all adults were victims. For people aged 65-74, it was 7.6%, and for those over 75, it was 5.8%. The group most at risk was actually people aged 45-54, at 9.3%. But it is important that the number of victims went up the most for those 65-74 (58.4% more) and over 75 (61.8% more) during this time. The pandemic likely caused more older people to become victims.

Losses to Fraud

Older adults may not be victims most often, but they usually lose more money. Studies show that as people get older, the average amount of money they lose to fraud goes up. Those aged 65-74 and over 75 lose the most. Many older adults have fixed incomes, like pensions, which makes it harder for them to get back money they lost.

Frauds and Scams

Fraud and scam are words often used to mean the same thing: tricking someone into losing money. While they are often used alike, some say scams can be tricky but legal, while fraud is always against the law. Another important word is financial abuse. This means someone wrongly or illegally uses an older person's money or things. This often happens with people close to the older adult, like family, caregivers, or workers. Cybercrime is a wider term. It includes online crimes about money, people's minds, or even crimes by countries. This paper only looks at money-related cybercrime, fraud, scams, and financial abuse.

There are many ways older adults are tricked. These include:

• Doorstep frauds: When fake workers charge too much or do bad work that is not needed.

• Financial abuse: When caregivers, family, or friends misuse an older adult's money.

• Phone scams: When people try to sell useless things, like fake investments, or pretend to be someone else to get money or private details.

• Mail scams: When fake lotteries, charities, or investments are sent by mail.

• APP fraud: When a person is tricked into sending money directly to a criminal, often because the criminal pretends to be someone else.

• Identity fraud: When criminals pretend to be someone else to use their bank details or identity.

• Cyber-frauds: Scams using email, the internet, and social media.

The COVID-19 pandemic also made more older adults use online services, which created new ways for them to be targeted by fraud. Many older adults have savings, pensions, and investments, making them good targets for criminals. Some older adults are more at risk if they have memory issues, health problems, live alone, feel lonely, or do not have many friends.

Fraud Prevention Literature

This paper lists many ways to stop fraud against older adults. It was found that most of these ways do not have strong proof that they work well. Some only have indirect proof, meaning they might help, but it is not certain if they actually stop people from becoming victims. Good studies cost money, and fraud prevention often does not get enough funds. Even weak proof is better than none. It is important to keep checking if these methods work and change them as needed.

Awareness training is a common way to stop fraud. These programs teach people how to spot scams. One such program helped older adults feel safer and more likely to report scams. But it did not check if fewer people became victims. Some studies show that more educated people or those with more money benefit more from these programs. It is also important to give advice that fits specific groups of older adults and to share this advice where they already gather. Experts say that sharing real stories of fraud victims can help. Studies also show that people should not rush big money decisions. Being stressed can make a person more likely to be tricked.

Some programs offer deeper training. In one program, people who got training were less likely to listen to fake sales calls. This was a good sign, but it did not prove fewer people became victims. Some programs use "reverse scams." This is where officials make fake scam calls or send fake emails to see if people would fall for them. After training, people were much less likely to respond to these fake scams. In Australia, police found people sending money to West Africa for scams. They sent letters to these people. After the first letter, 73% stopped sending money, and 87% stopped after the second.

Call blockers help stop unwanted calls. One system blocked 99% of scam calls. People using it also felt happier. While it does not prove fewer people were tricked, it likely helps by stopping the calls. Training people who work with older adults, like bankers or social workers, is another idea. They learn to spot signs of fraud or money abuse and then report it. One study trained bank staff. These trained staff reported more abuse and helped save a lot more money for older adults than untrained staff. Being alone or having mental health issues can make people more likely to be fraud victims. "Social prescribing" helps people join groups like art classes or sports. This helps their well-being, but there is no proof it stops fraud directly.

Aims, Methods, and Gap

This study was supported by a research fund. It aimed to improve ties between the UK and South Korea, focusing on older people and technology. Both countries have many older people and are good places to study how to stop fraud. The main goals of this paper were to:

• List the tools and ways used to stop fraud against older adults.

• Find out if there is any proof they work.

• See how much new technology they use.

To meet these goals, several steps were taken. First, a study was done of what has already been written about stopping fraud, especially for older adults. This helped to list many ways to stop fraud. It also showed that not many studies have truly checked if these methods work. The researchers also looked at websites of groups that help older adults or stop fraud. They searched online for terms like "fraud prevention" and "call blockers." Each time a new plan or product was found, it was added to a list. The study started by looking at the UK and South Korea but also found plans from other countries, like the USA. In total, 106 plans and products were found that aim to stop fraud against older adults.

Before showing the results, it is good to understand the idea of the "Fourth Industrial Revolution," or 4IR. The researchers wanted to see how much new technology from 4IR is used to stop fraud. The First Industrial Revolution was about steam power. The Second was about electricity. The Third was about computers and automation. The Fourth Industrial Revolution is happening now, with big changes in technology like:

• Physical things: Self-driving cars, 3D printing, advanced robots.

• Digital things: Smart devices, big data, computer brains (AI).

• Life sciences: Changing genes.

The researchers especially looked at which of these new technologies are being used to stop fraud, especially for older adults. South Korea is very good at using new technology. So, the study also looked at how much technology is used in the ways to stop fraud.

The Methods of Prevention

People have tried to group ways to stop crime. One well-known way lists methods like making crimes harder or less rewarding. While this works for many crimes, it does not fit all types of fraud against older adults. These frauds are often done by skilled criminals who live far away. This study also wanted to see how new technologies from the Fourth Industrial Revolution could help stop fraud. This was a key part of how the ways were grouped.

The next parts look at different plans and products used to stop fraud against older adults. These are grouped by how much technology they use. The study also checked if there was proof that these plans work. Some had no proof, while others had indirect proof. For example, stopping unwanted emails is likely to help, but it does not directly show fewer people were tricked.

Traditional Products and Solutions Rooted in Traditional Crime Prevention With Limited Use of Modern Technology

Some ways to stop fraud use very little technology. These are like older ways of stopping crime. They include things like stickers, peepholes on doors, and giving out info through letters, flyers, or meetings. It also means staff who work with older adults watch out for signs of fraud. Many of these methods are used for general crime prevention, too, like locks or neighborhood watch groups. There is not always strong proof that these physical methods work to stop fraud.

Other low-tech ways include visiting people to check their risk for fraud and giving advice. There are also lists of "trusted traders" that older adults can use to avoid bad service providers. Stopping junk mail can help, but clever scammers might still find ways to reach people. For older adults with memory problems, mail can be sent to another person to check it first. Also, helping people join social groups can make them feel less lonely, which may indirectly lower their risk of fraud. Few of these low-tech methods have strong proof they stop fraud, except for programs which warned victims by letter and training for bank staff.

One of the most common ways to stop fraud is to make people more aware and help them change their actions. Many such plans were found, and more studies have checked if these work. These plans often combine different ways to help. While helplines do not have strong proof they reduce fraud, other awareness programs have shown good results. How these programs are given is important.

Protection Using Modern Technologies to Prevent Fraud

Fraud has also led to many electronic ways to stop it. These use newer technologies. Examples include personal alarms that can call for help, call blockers that stop unwanted calls, and video doorbells. There are also tools to help people manage their private information to prevent identity theft. Some services give general warnings or watch bank accounts and cards for unusual activity.

Protections Using 4IR Technologies to Prevent Fraud

The last group of methods uses the very newest technologies, from the Fourth Industrial Revolution. Most of these use computer brains (AI) and big data to spot fraud. Some are common tools for everyone, like spam filters for email or anti-virus software. Others use data to send personal warnings. Websites like Scamadvisor use smart data tools to check if shopping websites are risky. Many of these tools also help banks and stores protect their customers from frauds like credit card fraud or identity theft.

Partnerships to Prevent Fraud

Most ways to stop crime involve groups working together. But this study found little proof of strong partnerships working to stop fraud against older adults. A few examples exist where different groups try to work together.

Towards a Holistic Prevention Model

This paper has listed many ways to stop fraud against older adults. It found that most of these ways do not have strong proof that they work well. Some only have indirect proof, meaning they might help, but it is not certain if they actually stop people from becoming victims. Good studies cost money, and fraud prevention often does not get enough funds. Even weak proof is better than none. It is important to keep checking if these methods work and change them as needed. The paper also looked at how much technology these methods use. Most methods are older and use little technology. But some newer, high-tech ways from the Fourth Industrial Revolution were found in the UK, South Korea, and other places. There is much room for more new tech to be used. Methods like "reverse scamming" could also be used to find people at high risk and help them.

Based on the study, a complete plan to stop fraud for older adults is suggested. Even without strong proof that every method works, they are all included. The plan looks at three main areas: the older adult, community groups/government, and companies. It also shows where new technologies could be used more. The plan is divided into four main parts.

The first part focuses on older adults themselves. They should learn about fraud risks and how to protect themselves. This can be done by attending training, reading materials, and getting alerts about new scams. It is also good for them to use tools like call blockers, video doorbells, and advanced spam filters. For very vulnerable older adults, trusted family or friends can help manage accounts and watch for signs of fraud. People who feel lonely should be encouraged to join social groups and talk about any unusual calls or messages they receive.

The second part of the plan is about communities, including police, charities, and the government. These groups should find out who is most at risk in their communities and work with them. They can give advice on how to spot scams and offer training. They should also provide lists of trusted businesses to help older adults make safe choices. Communities can help people get safety tools like call blockers if needed. Supporting social activities and referring people to social groups is also important. Governments should also make rules that help lower fraud risks.

The third part of the plan involves companies like banks, phone companies, and tech companies. They have a big role in stopping fraud. These companies should find customers who are at risk. Banks, for example, can train their staff to spot signs of financial abuse and act on it. Companies can use computer brains (AI) and big data to find strange money transfers or online actions. This can help them block fraud without the customer even knowing. Companies should also work on sharing information about vulnerable older adults, while still keeping privacy in mind.

The last part of the plan is about all these groups working together. Police, local authorities, social workers, healthcare providers, charities, banks, and tech companies are all doing work to prevent fraud. For the plan to work best, these different groups need to share information and work together more. They should give the same messages in their awareness campaigns. For example, if a bank finds a customer who is at high risk, they should be able to share that info with other helpful groups so that the person can get more support. Working together closely at local and national levels is key to stopping fraud.

Implications and Limitations

It is important to know this study has limits. There is not much strong proof that many fraud prevention tools actually work, especially for older adults. If only proven methods were suggested, there would be very few. So, this paper has brought together all ways to stop fraud, even if the proof is not strong. The study believes it is better to suggest all possible ways to protect older adults. This paper shows a need for more good studies to check if these methods work. It also aims to show people who work in fraud prevention all the different tools they can use, as many may not know them all. Lastly, the study found that new technologies are not used enough to fight fraud against older adults. More money and work are needed to create and test new tech ideas.

Conclusion

This paper looked at ways to stop fraud against older adults. It showed how big a problem fraud is for them. The paper also reviewed the few studies that checked if fraud prevention methods work. Then, it listed many tools and plans used to stop fraud that often target older adults, noting if there was any proof they worked and how much technology they used. All these tools and plans were put into a full plan to stop fraud for older adults. This plan has three main parts: older adults themselves, their communities, and the companies that serve them.

This plan is not final; it should change as new ways and technologies come out, especially when strong proof shows they work. Plans that work well should be used more, and those that do not should be stopped. This plan can help police, groups working with older adults, and companies like banks and phone companies. Fraud is growing, and more people are getting older. So, it is very important to have good ways to protect older adults and everyone else.