Research and analysis

UK public experiences, perceptions and understanding of money muling

Updated 28 July 2026

Authors

Amy Scoffham and Jessica Kelly

Acknowledgements

Home Office Analysis and Insight commissioned Ipsos UK to deliver these surveys. We would like to thank Dorothee Stellmacher, Maddy Pickles, Hannah Shrimpton and Anita Jeffreson at Ipsos UK for their support in delivering this research, along with Samantha Dowling, Martin Robinson, Abi Skraga, Andrew Kent and Iona Woodbridge from the Home Office.

Executive summary

As part of scoping work undertaken between 2022 and 2024 to explore the feasibility of primary research with ‘money mules’, the Home Office commissioned 2 separate surveys through Ipsos UK to gather baseline evidence on public experiences, perceptions and understanding of ‘money muling’. ‘Money muling’ is the process of moving the proceeds of crime through one’s financial accounts on behalf of criminals, sometimes in exchange for payment or other benefit. This report brings together findings from these 2 online surveys.

The first survey, conducted via the Ipsos UK KnowledgePanel in February 2024 among 2,114 people aged 16 to 75 years in Great Britain, explored the prevalence of money mule recruitment encounters and willingness to engage in hypothetical scenarios. It also served to identify potential participants for subsequent qualitative research, as described in the accompanying publication: Lived experiences of money muling.

The second set of questions, fielded as part of Ipsos UK’s i:omnibus in March 2024 among 2,233 people aged 16 to 75 years in the UK, concentrated on public understanding of the illegality of money muling.

While these surveys were conducted separately and for slightly different purposes and audiences, together they provide a useful baseline understanding of public encounters with, and perceptions of, money muling in the UK.

This one-off report, written by Home Office analysts, brings together findings from these 2 separate surveys.

Key findings

Encounters with money mule recruitment

Fourteen percent of British respondents in the KnowledgePanel survey said they have seen online adverts or postings (referred to throughout the report as ‘broadcasted opportunities’) to engage in money muling, while 6% were directly contacted by someone asking them to engage in this activity (referred to throughout the report as ‘direct requests’).

The likelihood of encountering money mule recruitment varied notably across demographic groups. Those aged 65 to 74 were the least likely to have encountered a broadcasted opportunity, with 6% reporting this type of encounter compared with between 9% and 25% among younger age groups. They were also less likely to have been directly contacted (2%; compared with 6% to 8% among those aged 16 to 54). In contrast, those aged 16 to 24 were substantially more likely to have encountered a broadcasted opportunity (25%) than those aged 45 to 75 (between 6% and 12%). Also, previous victims of cybercrime or fraud were more likely to have encountered money mule recruitment than non-victims. A possible reason for this is that criminals may share victims’ personal details within their networks for money mule recruitment.

The methods through which respondents encountered money mule recruitment varied considerably. For direct requests, email was the most common method reported by respondents who had experienced money muling recruitment encounters (54%). For broadcasted opportunities, social media was the most common method (52%), followed closely by emails (48%), making this the most common method overall.

These findings refer solely to the occurrence of a recruitment attempt; the data does not indicate whether these attempts were ultimately successful.

Willingness to engage

Respondents’ overall willingness to engage in money muling was extremely low. Hypothetical scenarios were presented to respondents in the KnowledgePanel survey, with the vast majority (97%) saying they would not be willing to accept a request to engage in money muling, regardless of being offered £50, £150 or £300.

Understanding of illegality

UK respondents’ understanding of the illegality of money muling was limited. Respondents in the i:omnibus survey were presented with 10 fictitious scenarios, 3 of which depicted illegal money muling. Fewer than one-in-five respondents (18%) correctly identified all fictitious money muling scenarios as illegal.

Those who had previous encounters with money muling were also less able to identify these scenarios as illegal compared to those who had not – two-thirds (67%) of those that had encountered money mule recruitment misclassified at least one scenario as legal, compared to 52% of those with no prior encounters. This suggests possible broader susceptibility or normalisation of these encounters amongst certain groups.

1. Introduction

‘Money muling’ is the process of moving the proceeds of crime through one’s financial accounts on behalf of criminals, sometimes in exchange for payment or other benefit. Some individuals move funds complicitly, whereas others may feel compelled to do so or be unaware that it is illegal. The Economic Crime Plan 2 and Money Mule and Financial Exploitation Action Plan acknowledges that money muling facilitates many crime types, particularly fraud, yet there is limited in-depth research on the topic.

Improving this understanding is critical to disrupting money laundering networks, preventing criminals from profiting from the proceeds of crime and protecting vulnerable individuals from exploitation. Tackling money mules is therefore set out as a system priority by the NCA (2025) and wider public and private sector partners. The Fraud Strategy 2026 to 2029 also outlines government priorities for combatting financial exploitation linked to ‘exploitative money laundering’.

As part of scoping work undertaken between 2022 and 2024 to explore the feasibility of primary research with money mules, the Home Office commissioned 2 separate surveys through Ipsos UK to gather baseline evidence on public experiences and perceptions of money muling. This report brings together findings from these 2 surveys.

This research is among the first few attempts to use surveys to acquire more evidence about hidden activities such as money muling, and represents an effort to test how viable particular survey questions may be in supporting the development of the evidence base in this area.

2. Methodology

2.1 Surveys and sampling approach

On behalf of the Home Office, Ipsos UK undertook 2 surveys drawn on in this report, each using a different survey panel to recruit respondents. The first recruited respondents from the Ipsos UK KnowledgePanel, and the second from the Ipsos UK i:omnibus panel.

As outlined above, these surveys were conducted separately and explored different aspects of money muling: the KnowledgePanel survey concentrated on encounters with recruitment and willingness to engage, while the i:omnibus questions examined understanding of the illegality of money muling. Further details on findings from each survey are provided in Section 3.

2.1.1 KnowledgePanel survey

The KnowledgePanel is a random probability online panel with offline recruitment, comprising of over 15,000 panellists. As a probability sample, it does not use a quota approach when conducting surveys – instead, invited samples are stratified when conducting waves to account for any profile skews within the panel. Panellists are recruited via a random probability un-clustered address-based sampling method, meaning every UK household has a chance of being selected to join the panel. Adult members of the public who are digitally excluded can register for the KnowledgePanel by post or telephone, and are given a tablet, an email address and basic internet access so they can complete surveys online. Data is post weighted by age, gender, region, Index of Multiple Deprivation quintile, education, ethnicity and number of adults in the household in order to reflect the profile of the UK population.

The survey was carried out between 15 and 21 February 2024, with a sample of 2,114 respondents aged 16 to 75 across Great Britain. As is common with this kind of survey, the questions on money mulling were asked alongside questions from a range of other topics.

2.1.2 i:omnibus survey

Ipsos UK i:omnibus panel members opt-in to join the panel themselves, rather than being randomly recruited. Quotas were set on age, gender, working status and standard geographical regions. The data were then post weighted to the profile of the UK population aged 16 to 75 (including non-telephone owning households) to account for any shortfalls in quotas using key demographic variables: gender by age, region, social grade, education and working status. Quotas and post weighting were used to produce a nationally representative sample.

As the survey uses non-probability sampling, it may be subject to different forms of bias that can limit generalisation to the wider population. Furthermore, as it is an online panel survey, it does not include digitally excluded individuals and may attract more digitally engaged individuals compared to the general population. While quotas and post-weighting are applied to produce a sample that is nationally representative on key demographic variables such as age, gender, region and education, these corrections cannot fully address all potential biases inherent in non-probability sampling. The questions on money laundering were asked alongside questions from a range of other topics.

This survey was carried out between 22 and 28 March 2024 with 2,233 respondents across the UK.

2.2 Survey design

The questions used to gather the insights presented in this report were developed collaboratively by Home Office analysts and policy teams, and Ipsos UK.

The KnowledgePanel survey explored 2 key areas:

• the prevalence and nature of respondents’ encounters with money mule recruitment (explored in Section 3.1)
• respondents’ willingness to engage in hypothetical money muling scenarios (explored in Section 3.3)

The i:omnibus survey concentrated on respondents’ understanding of the illegality of money muling (explored in Section 3.2). It also included questions on the prevalence of encounters with money mule recruitment, which allows for some comparison with KnowledgePanel findings. Any references to encounters in Section 3.2 relate specifically to the i:omnibus survey.

As these surveys were conducted separately, this report primarily draws on KnowledgePanel data for findings on encounters (Section 3.1) and willingness to engage (Section 3.3), due to its stronger methodological underpinnings as a random probability sample. i:omnibus data is used for indicative findings on the understanding of illegality (Section 3.2).

2.3 Interpreting this report

Results were tested for statistical significance. Any differences discussed in this report are statistically significant unless otherwise stated.

This is a one-off report to summarise findings from these surveys. The survey results presented in this report are based on samples of the British and UK populations, and as such are subject to margins of error which are linked to sample size.

This report examines findings across various demographics, including working status. It should be noted that the 2 surveys categorised working status differently – KnowledgePanel categorised respondents as working full-time or not working full-time (including part-time workers and those not currently in employment for any reason), whereas i:omnibus categorised respondents as working (including both full-time and part-time workers) or not working (meaning those not currently in employment for any reason).

Both surveys were commissioned to cover adults aged 16 to 75. However, the KnowledgePanel data tables use standard age breaks that include a ‘75+’ category. In this survey, this category contains only respondents aged exactly 75 (n=43), as no one aged 75 and over was included in the sample. Due to this small base size, results for this group are not shown in charts presenting age-specific analyses, though full data tables are published separately for transparency. The i:omnibus survey includes 75-year-olds within the broader 55 to 75 category (n=704).

Please note that the KnowledgePanel survey was conducted across Great Britain, while the i:omnibus survey covered the whole of the United Kingdom. Results at total level are therefore not directly comparable, as they cover different regions.

Due to rounding, percentages in this report may not always sum to 100%. Similarly, combined percentages may not precisely match the sum of their constituent parts.

3. Key findings

3.1 Encounters with money mule recruitment

This section draws only on the KnowledgePanel survey, which offers the strongest methodological foundation for understanding encounter prevalence. Findings refer solely to the occurrence of a recruitment attempt; the data does not indicate whether these attempts were ultimately successful.

A notable proportion of respondents had encountered some form of money mule recruitment in the previous 12 months, with 14% of respondents coming across a broadcasted opportunity and 6% receiving a direct request. The methods used by criminals trying to reach them were diverse and primarily digital.

3.1.1 Prevalence of encounters

Respondents were asked about their experiences with 2 types of money mule recruitment in the previous 12 months: (1) encountering online adverts or posts offering opportunities to receive money into their financial account and transfer it to an unknown third party (referred to as “broadcasted opportunities”); and (2) receiving a direct request from someone to use their financial account for the same purpose (referred to as “direct requests”).

Fourteen per cent of respondents reported coming across a broadcasted opportunity, while 6% had received a direct request. This imbalance is expected, as broadcasted opportunities are publicly accessible and therefore are likely to reach a much wider audience than targeted, direct requests.

It is important to note that the data does not allow us to determine whether any of these individuals subsequently became money mules.

3.1.2 Demographic patterns

The likelihood of encountering money mule recruitment varied notably across demographic groups, with younger adults and victims of cybercrime or fraud being particularly exposed to money mule recruitment:

Age

The likelihood of encountering money mule recruitment in the 12 months prior to the survey generally decreased with age though not uniformly across all age groups (see Figure 1). Those aged 65 to 74 were the least likely to have encountered a broadcasted opportunity, with 6% reporting this type of encounter compared with between 9% and 25% among younger age groups. They were also less likely to have been directly contacted (2%, compared with 6% to 8% among those aged 16 to 54). In contrast, 16 to 24-year-olds were substantially more likely to have encountered a broadcasted opportunity (25%) than those aged 45 to 75 (between 6% and 12%).

This may reflect differences in respondents’ online behaviours. For example, a 2024 Ofcom report found that younger adults are more likely to use a wider range of online communication platforms (such as social media and messaging apps). This may provide more opportunities to be reached by criminals trying to recruit money mules.

Victims of cybercrime or fraud

Previous victims of cybercrime or fraud were twice as likely to have encountered a broadcasted opportunity than non-victims (22% versus 11%) and more than twice as likely to have been directly contacted (10% versus 4% respectively).

Bekkers et al. (2024) found evidence of criminal networks sharing or selling victims’ details for money mule recruitment on platforms such as Telegram. This could be one potential route for previous cybercrime or fraud victims being more at risk.

Gender

Men were more likely than women to encounter broadcasted opportunities (17% versus 11% respectively), though the reasons for this remain unclear. There were no significant gender differences in direct requests, suggesting direct targeting may rely less on gender than broadcasted content does.

Ethnicity

Those from ethnic minorities were more likely than white respondents to have received a direct request (10% versus 5% respectively). Conversely, encountering broadcasted opportunities was similar across groups. The reasons for this again remain unclear.

Figure 1: Proportion of respondents from each age group who had encountered money mule recruitment in the previous 12 months

Age of respondent	Direct requests	Broadcasted opportunities
16 to 24	8%	25%
25 to 34	8%	15%
35 to 44	8%	17%
45 to 54	6%	12%
55 to 64	3%	9%
65 to 74	2%	6%

Base: All adults aged 16 to 74 in Great Britain (n= 2,071). Due to a small base size and to minimise statistical disclosure risk, results for the ‘75+’ age group are not included in this chart.

3.1.3 Reported methods through which respondents encountered money mule recruitment

Recruitment messages reached respondents through a wide range of digital and interpersonal channels.

Among those who have experienced direct requests:

• email was the most common method reported by respondents (54%) (as shown in Figure 2 below)
• messaging apps were reported as a method of contact more heavily among those who had been victims of cybercrime or fraud (38% of victims versus 16% of non-victims)

Figure 2: Methods through which respondents said they received a direct request to engage in money muling

Method of contact	Proportion of respondents
Emails	54%
SMS text message	32%
A messaging app (for example, WhatsApp or Messenger)	29%
Social media (for example, Facebook or X)	28%
Dating app	8%
In person	6%
Gaming platforms	5%

Base: Respondents who had been directly asked to receive and transfer money to an unknown third party (n=107). Due to a small base size and to minimise statistical disclosure risk, results for the ‘Other’ and “Don’t know” responses are not included in this chart.

For broadcasted opportunities:

• social media was the most common channel (52%), followed closely by emails (48%) and pop-up ads (38%) (as seen below in Figure 3)
• men were more likely than women to report seeing opportunities through pop-up ads (46% versus 27%)

Figure 3: Methods through which respondents said they saw a broadcasted money muling opportunity

Method of contact	Proportion of respondents
Social media	52%
Emails	48%
Pop-up ads	38%
Online forums	12%
Job adverts on job sites	8%
Other	4%
Don’t know	4%

Base: Respondents who had seen online postings/adverts to receive and transfer money to an unknown third party (n=234).

3.2 Understanding of the illegality of money muling

This section draws exclusively on the i:omnibus survey.

Respondents’ understanding of the illegality of money muling was limited. Respondents were presented with 10 fictitious scenarios, 3 of which depicted illegal money muling. Among the 3 money muling scenarios:

• between 37% and 61% of respondents correctly identified each individual scenario as illegal
• only 18% correctly identified all 3 scenarios as illegal; most respondents either said they were not illegal or were not sure
• 55% misclassified at least one scenario as not illegal
• 7% thought all scenarios were not illegal

There was considerable variation in how different demographic groups assessed the illegality of the scenarios, with judgements differing by age, ethnic minorities, and workers.

3.2.1 Variation across scenarios

The 3 fictitious scenarios were as follows:

Harry’s scenario:

Harry has been getting to know someone online over the last few weeks. They ask Harry if he can receive money into his personal bank account and transfer it to an unknown third party. Harry agrees and makes the transaction.

Aisha’s scenario:

After applying online, Aisha has been offered a role as a money transfer agent. On the instruction of her new employer, Aisha opens a new personal bank account to manage her business transactions through.

Olivia’s scenario:

Olivia sees an opportunity on social media to make money through her bank account. She provides her bank details and access to her bank account to an organisation and in return receives £500 plus ongoing commission.

Figure 4: Proportion of i:omnibus respondents’ legal classification of each fictitious money muling scenario

Scenario	Illegal	Legal	Don’t know	Prefer not to say	Total
Olivia’s scenario	37%	36%	27%	1%	100%
Aisha’s scenario	41%	30%	28%	1%	100%
Harry’s scenario	61%	22%	17%	1%	100%

Base: All UK adults aged 16 to 75 (n=2,233).

As shown in Figure 4, responses differed across scenarios:

Harry’s scenario

Harry’s scenario, which involved a direct request to move money through his personal account, was the most widely recognised as illegal (61%). It is unclear why this is. One possible explanation is that respondents may find it easier to identify money muling when the recruitment happens through direct, personal interaction between the potential money mule and the criminal trying to recruit them. Alternatively, respondents may have been more attuned to the criminal nature of this scenario because Harry receives no financial or other benefit in return, which could suggest he is being exploited. As such, respondents may not necessarily be identifying the money muling in this scenario, but could have more of an idea that something illegal is going on.

Olivia and Aisha’s scenarios

In contrast, Olivia and Aisha’s scenarios, both framed as broadcasted opportunities, were less likely to be classified as illegal (37% and 41% respectively). The majority of respondents either believed these situations were not illegal or expressed uncertainty. This may reflect a challenge for identification of money mule situations when they are presented as money-making opportunities, particularly when they resemble job adverts or financial ‘side-hustles. As a result, individuals may confuse them with legitimate income-earning ventures. This highlights a key vulnerability – when money muling is disguised as employment or a money-making opportunity, limited public awareness may make it more difficult for people to recognise the underlying criminality.

3.2.2 Demographic patterns

Several demographic factors were linked to better or poorer understanding of the illegality of scenarios:

Age

Respondents aged 55 to 75 were more likely to classify all 3 scenarios as illegal (27%) than all other age groups (between 12% and 16%).

Ethnicity

White respondents were more likely than respondents from ethnic minorities to classify all 3 scenarios as illegal (19% versus 13%).

Employment status

Non-workers were more likely than workers to correctly classify all 3 scenarios as illegal (21% versus 16%).

Figure 5: Proportion of respondents within each age group who correctly identified each money muling scenario as illegal

Scenario	Harry’s scenario	Aisha’s scenario	Olivia’s scenario
16-24	47%	28%	32%
25-34	47%	39%	34%
35-44	55%	40%	31%
45-54	60%	38%	35%
55-75	77%	50%	44%

Base: All UK adults aged 16 to 75 (n=2,233).

3.2.3 Relationship between encounters and understanding

Note on data source: This section draws on i:omnibus data only. The i:omnibus survey included questions on both encounters with money mule recruitment and understanding of illegality, allowing us to examine relationships between these themes within the same sample of respondents.

The data suggest a correlation between encountering money mule recruitment and having a poorer understanding of the illegality of money muling.

Those who had previously encountered money mule recruitment were significantly less likely to correctly identify scenarios as illegal. Two-thirds (67%) of those who had encountered money mule recruitment misclassified at least one scenario as legal, compared to 52% of those with no prior encounters. This may potentially suggest some normalisation of these encounters amongst certain groups.

Furthermore, respondents who had previously received a direct request were more likely to perceive scenarios as legal when they resembled their own experiences. They were significantly more likely to classify Harry’s scenario (a direct request) as legal compared to those with no previous encounters, though there were no significant differences between these groups for Aisha and Olivia’s scenarios.

Those who had encountered broadcasted opportunities were significantly more likely to misclassify all 3 scenarios as legal, compared to those with no encounters.

A poor understanding of money muling’s illegality may restrict individuals’ capability to make informed decisions about involvement. Based on findings in Sections 3.2.1 and 3.2.2, certain groups – including younger adults, respondents from ethnic minorities, workers – were significantly less likely to correctly identify scenarios as illegal, and may therefore be more susceptible to perceiving money muling opportunities as legitimate.

3.3 Willingness to engage in money muling

This section contains findings from the KnowledgePanel survey. These findings are based on respondents’ answers to hypothetical scenarios. Actual behaviours in real-life situations may differ due to factors such as perceived risk, emotional responses, and contextual influences. Answers were also given in the context of a wider survey asking about questions on other topics. Therefore, results should be interpreted as indicative rather than predictive of real-world actions.

Respondents were asked if they would, hypothetically, agree to receive £1,000 into their bank account and transfer it to an unknown third party in exchange for £50, £150 or £300. The findings relate specifically to these tested transaction and commission amounts. Determining whether similar patterns would apply to other sums or commission levels would require more detailed research, beyond what can be reliably explored through a surveying format.

Respondents’ overall willingness to engage in money muling was extremely low. The vast majority of respondents (97%) reported that they would probably not or definitely not accept such a request, regardless of the payment amount offered.

While acceptance remained very rare, payments of £300 resulted in slightly fewer ‘definitely not’ responses and small increases in ‘probably not’ and ‘probably yes’ responses, although these differences were not statistically significant. This suggests a modest shift in certainty rather than in actual acceptance, with some respondents becoming slightly more open-minded as incentives increased, though this pattern should be interpreted with caution given the lack of statistical significance.

No demographic breakdowns can be reported for this section due to extremely small base sizes of those who showed a willingness to accept.