Research and analysis

Survey of public perceptions of fraud, error and debt: technical report

Published 31 October 2023

DWP research report no. 1045

A report of research carried out by Ipsos on behalf of the Department for Work and Pensions.

Crown copyright 2023

You may re-use this information (not including logos) free of charge in any format or medium, under the terms of the Open Government Licence.

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If you would like to know more about DWP research or you’d like a copy of this report in Welsh, email: [email protected]

First published October 2023

ISBN 978-1-78659-587-4

Views expressed in this report are not necessarily those of the Department for Work and Pensions or any other government department.

Voluntary statement of compliance with the Code of Practice for Statistics

If your research relies heavily on the use of statistics, consider including a voluntary statement explaining how the research complies with the 3 pillars of the UK Statistics Authority Code of Practice for Statistics. If your research doesn’t rely heavily on statistics, you may still consider how these pillars have been addressed.

Read the DWP research report guidance for more information on what to include in this section.

The Code of Practice for Statistics (the Code) is built around 3 main concepts, or pillars, trustworthiness, quality and value:

• trustworthiness – is about having confidence in the people and organisations that publish statistics
• quality – is about using data and methods that produce assured statistics
• value – is about publishing statistics that support society’s needs for information

The following explains how we have applied the pillars of the Code in a proportionate way.

Trustworthiness

This research was carried out by Ipsos, who worked with DWP to understand the aims of the research. The design, delivery and analysis were carried out impartially and in compliance with the Market Research Society Code of Conduct, the Government Social Research code of practice and the international quality standard for market research, ISO20252.

Although research findings are shared with ministers and other officials before publication, this is done to promote the value of the research to the department. Ministers have no editorial role.

Quality

The survey was carried out using established quantitative research methodology and statistical methods, described below. The research has been quality-assured using Ipsos’s internal quality checking processes, which have been shared with the Department for Work and Pensions. The analysis of findings and report writing has been quality-assured by analysts at the Department for Work and Pensions.

Value

This survey provides insight into the public’s views on fraud and error in the welfare benefits system and on proposed new measures to tackle this. Findings from the survey will inform the development of these new measures, how they are brought forward and the way they are communicated.

Technical report: quantitative research

This report provides the technical and methodological details for survey research carried out by Ipsos on behalf of the Department for Work and Pensions (DWP) to understand perceptions of fraud, error and debt in the benefits system. This report provides more detail on the sampling, recruitment and fieldwork materials (copies of these materials are appended).

The survey was carried out using KnowledgePanel, Ipsos’ random probability online panel. This is the UK’s largest random probability online panel with around 25,000 panellists. The panel is highly representative, and the profile of panellists is similar to national statistics on key demographics.

Fieldwork took place between 15 and 21 June 2023.

Recruitment to the panel

Panellists are recruited via a random probability unclustered address-based sampling method. This means that every household in the UK has a known chance of being selected to join the panel. Letters are sent to selected addresses in the UK (using the Postcode Address File), inviting them to become members of the panel. Households receive three mailings and can sign up to the panel by completing a short online questionnaire or by returning a paper form. Up to two members of the household are able to sign up to the panel. Members of the public who are digitally excluded are given a personal phone call back, a free tablet, an email address, basic internet access and tech support. This allows them to complete surveys online. Panellists complete a registration survey providing valuable demographic and geodemographic information.

Questionnaire development

Questionnaire development

The questionnaire was designed to be 15 minutes long^{[footnote 1]}. Ipsos developed the survey questionnaire based on an initial draft supplied by DWP. Ipsos then held a stakeholder workshop to feed into questionnaire development as well as attending meetings with DWP policy and strategy teams.

As a general principle, the questionnaire was worded to provide only the information essential to understanding the proposed powers and to describe the powers in a neutral, factual way. Some powers were also described in the form of an example scenario, to check whether this alternative method of presentation affected respondents’ views.

However, it was also of interest to test alternative wording to understand whether this would affect attitudes towards the powers. To do this, three of the questions had alternative versions which were presented to half of the sample, selected at random. One half of respondents (sample A) saw neutrally-worded versions of these questions, while the other half (sample B) saw versions with wording intended to elicit a more favourable response.

Following cognitive testing (see below), the questionnaire was reviewed for best practice standards by a member of Ipsos’ internal panel of polling experts.

Cognitive testing

The questionnaire was cognitively tested with ten individuals between the 1 May and 5 May 2023. Cognitive testing is a technique used to test and improve survey questions. During a cognitive interview, survey questions are administered and participants are asked about the cognitive processes they go through in answering the questions. This helps to uncover problems with the questions and identify improvements. In particular, the purpose of these interviews was to test comprehension, recall, and suitability of the draft survey questions.

The interviews were conducted with 10 members of the public, including 5 DWP benefit claimants, recruited by a research recruitment agency. There was a mix of age and gender. As a thank-you for participating in these interviews, participants received a £30 Love2Shop voucher.

Cognitive interviews took place over video call so that participants could read the questions displayed on screen, to mimic the online mode of the survey.  

Table 1.1 A breakdown of participants in the cognitive interviews

Criteria	Interviews achieved
Benefit claimant	5
Non-benefit claimant	5
18-44	5
45-64	5
65+	0
Male	6
Female	4
Total interviews completed	10

This testing resulted in changes to the questionnaire to improve understanding and reduce cognitive effort for participants. This included removing some of the more complex questions altogether, as participants in testing consistently struggled to answer these. The questions that were removed related to changes to penalties for fraud and error, and questions around safeguards for the powers.

Sampling

The KnowledgePanel is a random probability survey panel. Therefore, the KnowledgePanel 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. Two samples were drawn. In sample 1, 3234 panellists were selected, and all responding panellists could complete the full survey. In sample 2, 4544 panellists were selected and, if they indicated in an initial screening question that they were a benefit claimant, they could complete the full survey; otherwise, the panellists were screened-out and were not able to continue. Both initial samples were stratified by country and education.

Mainstage fieldwork

Ultimately, 2,127 people completed the survey, comprising a nationally representative sample of 1,782 people and the boost of 345 additional DWP benefit claimants. Overall, including the boost sample and those in the nationally representative sample, 618 respondents were DWP benefit claimants, in terms of the definition used for this research. This was defined as people claiming at least one of the following benefits:

• Universal Credit
• Jobseeker’s Allowance/New Style Jobseeker’s Allowance
• Income Support
• Employment and Support Allowance (ESA)/New Style Employment and Support Allowance
• Pension Credit
• Carer’s Allowance
• Attendance Allowance
• Personal Independence Payment
• Disability Living Allowance (adult or child)

People claiming Tax Credits, Housing Benefit or the State Pension were not counted as DWP benefits claimants unless they also claimed one of the benefits listed above. This definition was discussed and agreed with DWP at the outset of the research.

Outcomes and response rate

Figure 1.2 Sample and response rate

Sample 1	Sample 2
Total sample	3234	4544
Completes	1,782	345

Total completes: 2127
Combined response rate: 57%

Data processing and weighting

In order to ensure the survey results are as representative of the target population as possible, the following approach was applied separately to sample 1 and sample 2 (pre-screened).

Two members per household are allowed to register on the KnowledgePanel. Therefore, we employed a design weight to correct for unequal probabilities of selection of household members in each pre-screened sample.

Calibration weights were also applied using the latest population statistics relevant to the surveyed population to correct for imbalances in the achieved pre-screened samples. England, Wales, Scotland, and Northern Ireland were weighted together as the UK.

The calibration weights were applied in two stages:

• the first set of variables were (using ONS 2019 mid-year population estimates as the weighting targets): An interlocked variable of Gender by Age, and region
• the second set were (using ONS 2019 mid-year population estimates and the ONS Annual Population Survey as the weighting targets): Education, Ethnicity, Index of Multiple Deprivation (quintiles), and number of adults in the household

Once this initial weighting was completed, benefits claimants from sample 2 were merged with sample 1, and then the overall bases of benefits claimants and non-benefits claimants (see definition above) were rescaled to match their proportions in the target population 24.5% and 75.5%.

This figure of 24.5% of the adult population being a DWP benefit claimant was calculated using DWP StatXplore figures from November 2022 from England, Scotland and Wales. The number of adults (18+) claiming at least one of the DWP benefits listed in footnote 1 was obtained from StatXplore as 12,684,403 (22,441,259 DWP claimants overall minus 9,756,856 not claiming any of the benefits in scope). This is 24.5% of a GB 18+ population of 51,718,632 (ONS figures from 2021, the most recent available).

The below table presents the weighting profile targets for sample 1:

Sample 1

Age	Male	Female	In another way	PNTS
18-24	5.5%	5.2%	0.03%	0.18%
25-34	8.6%	8.4%	0.06%	0.00%
35-44	7.9%	8.0%	0.03%	0.00%
45-54	8.4%	8.7%	0.00%	0.00%
55-64	7.6%	7.8%	0.03%	0.09%
65-74	6.1%	6.5%	0.12%	0.06%
75+	4.6%	6.1%	0.00%	0.00%

Ethnicity	Percentsage
White (including white minorities)	86.5%
All other ethnic minorities	12.0%
Don’t know/Prefer not to say	1.5%

Number of adults in the household	Percentage
One adult	18.5%
Two or more adults	81.5%

IMD Quintiles	Percentage
1	20%
2	20%
3	20%
4	20%
5	20%

Region	Percentage
North East	4.1%
North West	11.0%
Yorkshire And The Humber	8.2%
East Midlands	7.3%
West Midlands	8.8%
East Of England	9.3%
London	13.2%
South East	13.7%
South West	8.6%
Wales	4.8%
Scotland	8.4%
Northern Ireland	2.8%

Education	Percentage
Degree level or above	30.5%
Below degree level	68.7%
Prefer not to say/Not stated	0.8%

Notes on interpretation of data

In the findings report, the survey data are rounded up to whole percentages. Therefore, in some cases, charts will appear to add to slightly more than 100%. For example, if the calculated estimates for a question are 20.6%, 40.7% and 38.7%, they will show as 21%, 41% and 39%.

When reporting on sub-groups, we note whether or not results from sub-groups differ from the overall sample in a statistically significant way, with statistic testing relying on an assumption that the weighted sample achieved was as good as a random probability sample. Statistical significance testing is used to determine whether differences in results are likely to be due to a genuine difference between groups, as opposed to chance variation. The threshold used in this research is the 0.05 level, meaning there is less than a 5% chance that results deemed significantly different differ due to chance. This is a standard level of significance used in social sciences.

Appendix: Questionnaire

Notes

Respondents were randomly allocated to sample A or sample B (half of overall sample in each)

S1: code 1 could not be combined with 2, 4, OR 6; codes 14 and 999 could not be combined with any other codes.

The introductory statements (indicated with Intro_0 and similar) appeared on separate screens to the questions.

Q100, Q105: statements S1-S8 and S1-3 (respectively) were rotated

Q100, Q101, Q103, Q105, Q106, Q202, Q203, Q204, Q205, Q301, Q302, Q401, Q404, Q502, Q503, Q701: scales were reversed for half of respondents with “Don’t know” fixed in last position

Q104, Q107: order of statements 1 and 2 was reversed for half of respondents.

Modules 2 to 6 were rotated.

Q300: codes 7 and 998 could not be combined with any other codes.

Q303: codes 6 and 998 could not be combined with any other codes.

There is no question 405: it was removed after testing.

Q406: respondents could select one option only.

Q501: code 998 could not be combined with any other codes.

There is no question 601: it was removed after testing.

Module 0. Screener

S1

Which, if any, of the following benefits or tax credits are you currently claiming?

Please select all that apply.

1. Universal Credit
2. Tax Credits – either Working Tax Credits or Child Tax Credits
3. Jobseekers Allowance/New Style Jobseekers Allowance
4. Income Support
5. Employment and Support Allowance (ESA)/New Style Employment and Support Allowance
6. Housing Benefit
7. Pension Credit
16. State Pension
8. Carer’s Allowance
9\ Attendance Allowance
10. Personal Independence Payment
11. Disability Living Allowance for yourself
12. Disability Living Allowance for a child
13. Another benefit
14. None of these
999. Prefer not to say

Screenedout if needed:

Thank you for your time. You do not qualify for this survey, but as a thank you for taking the time to respond, you will receive [50/100] points. You can now close your browser to exit the survey, or check your balance on the KnowledgePanel portal.

Module 1. Overall perceptions

Intro_0

These first questions are about your views on the government.

Q100

Do you think the government is doing a good job or a bad job at each of these?

Please select one option only.

S1. Managing the economy
S2. Dealing with the cost of living

S3. Handling taxation and public expenditure

S4. Reducing inequalities between different regions
S5. Reducing levels of fraud and error in the welfare benefits system
S6. Reducing the level of crime and anti-social behaviour
S7. Managing immigration
S8. Improving the National Health Service

1. Very good job
2. Fairly good job
3. Bad job
4. Very bad job
998. Don’t know

Intro_1

The next questions are about fraud, error, and debt in the welfare benefits system in the UK.

Fraud and error in the benefit system is when someone is paid too much, or not enough benefits. This may be because of intentionally claiming benefits they are not entitled to, or because of a mistake. This might be their mistake or the government’s mistake. If someone has been paid too much benefit, they may have a debt to the government.

Q101

In general, how big a problem, if at all, do you think fraud and error in the welfare benefits system is in the UK?

Please select one option only.

1. Very big problem
2. Fairly big problem
3. Not very big problem
4. Not a problem at all
998. Don’t know

Q102

Do you think that levels of fraud and error in the welfare benefits system are generally going up, going down or staying about the same?

Please select one option only.

1. Levels of fraud and error are going up
2. Levels of fraud and error are going down
3. Levels are staying about the same
998. Don’t know

Q103

Suppose someone knowingly gave false information to support their benefit claim. What would your view about this be?

Please select one option only.

1. This is always wrong
2. This is usually wrong
3. This is sometimes wrong
4. This is rarely wrong
5. This is never wrong
998. Don’t know

Q104

Which of the following statements is closest to your view?

Please select one option only.

1. Most incorrect benefit claims are a result of dishonesty
2. Most incorrect benefit claims are a result of mistakes
3. About half of incorrect benefit claims are a result of dishonesty, and about half are a result of mistakes
998. Don’t know

Q105

The Department for Work and Pensions (DWP) is the Government department responsible for welfare benefits.

To what extent do you agree or disagree with the following statement?

Please select one option only.

S1. If someone is paid too much in benefits as a result of them deliberately giving false information, DWP should make them pay it back
S2. If someone is paid too much in benefits as a result of them mistakenly giving false information, DWP should make them pay it back
S3. If someone is paid too much in benefits as a result of a DWP mistake, DWP should make them pay it back

1. Strongly disagree
2. Tend to disagree
3. Neither agree nor disagree
4. Tend to agree
5. Strongly agree
998. Don’t know

Q106

How likely or unlikely do you think it is that people who falsely claim benefits will be caught?

Please select one option only.

1. Very likely
2. Fairly likely
3. Not very likely
4. Not at all likely
998. Don’t know

Q107

Do you think the government is doing too much, not enough, or about the right amount to reduce levels of fraud and error in the welfare benefits system?

Please select one option only.

1. Too much
2. Not enough
3. About right amount
998. Don’t know

Intro_1.1

The government is considering introducing new powers regarding fraud and error in the welfare benefits system. We are interested in getting your views on the proposed new powers.

Module 2 2: Information gathering powers

Intro_2

The next questions are about the information DWP can collect about benefit claimants.

Q201

Before taking part in this survey, were you aware that DWP can ask for information about individuals from organisations such as banks, as part of a criminal investigation into benefit fraud?

Please select one option only.

1. Yes, I knew DWP could do this
2. I wouldn’t have been certain but had assumed DWP could do this
3. I wouldn’t have been certain but had assumed DWP could not do this
4. No, I did not know DWP could do this
998. Don’t know

Q202

The Government is looking at options for increasing DWP’s powers to collect information about its claimants. “Claimants” here means people who have received payments from DWP.

The new powers would mean that DWP investigators could collect a wider range of information about claimants.

How acceptable do you think it would be for DWP to be able to collect information about where claimants are spending money, to help investigate claimants suspected of benefit fraud?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q203

The new powers would also mean that DWP investigators could get information as soon as they suspect fraud, rather than waiting for a full criminal investigation.

How acceptable do you think it would be for DWP to be able to collect banking information (such as childcare payments information) about its claimants, as soon as fraud is suspected, rather than needing to wait for a full criminal investigation?

Show to sample B only: This would mean DWP could identify fraud or error more quickly, put claims right, and reduce overpayments and debt.

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q204

Version A: How acceptable do you think it would be for other government organisations to share data with DWP about people who are DWP claimants, to prevent benefit fraud or error?
Version B: How acceptable do you think it would be for other government organisations to share data with DWP about people who are DWP claimants, to make sure claimants receive the amount of money they are entitled to?

Please select one option only

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q205

When you are claiming benefits, you are not allowed to live abroad for more than 1 month.

Imagine someone claims pension credit and decides to go on holiday for 3 months. They don’t tell DWP. If DWP had increased access to information-gathering, for example information from an airline about that person’s travel, it could detect they were abroad, and the fraud could be prevented.

In this example, how acceptable do you think it would be for DWP to collect information from the person’s airline to see where they are travelling?

Please select one option only.

1. Completely unacceptable 2. Unacceptable 3. Neither acceptable nor unacceptable 4. Acceptable 5. Completely acceptable 998. Don’t know

Module 3. Third-party data

Intro_3

The next questions are about who DWP can collect information about benefit claimants from.

Q300

Before taking part in this survey, which types of information did you think DWP could access about its claimants when they apply for benefits, to check whether they are eligible?

Please select all that apply

1. Information from their bank accounts
2. Information from their employer about their pay
3. Information from other government departments
4. Location data from their phone
5. Social media post
6. Other (please specify:)
7. None of the above
998. Don’t know

Q301

The government is looking at giving DWP the power to ask banks to tell them about account holders who look like they may be breaking DWP’s rules. For example, people who are having benefits paid into their account but also have high levels of savings.

Show to sample B only: This would mean DWP could detect fraud and error more easily, stop fraud more quickly and prevent people from being overpaid and building up debt.

How acceptable do you think it would be for DWP to ask banks to share information about accounts which look like someone may be committing benefit fraud?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q302

If you have more than £16,000 in ‘capital’ (broadly referring to savings), you aren’t entitled to claim Universal Credit.

Imagine someone has savings worth £18,000 and did not declare it when they claimed Universal Credit. If their bank could flag their savings to DWP, then cases such as this could be spotted, and the overpayment could be stopped.

In this example, how acceptable do you think it would be for this person’s bank to flag their savings to DWP?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q303

In which of these circumstances, if any, do you think DWP should be allowed to access someone’s personal data, including data from their bank accounts?

Please select all that apply.

1. As part of a criminal investigation into benefit fraud
2. When DWP have reason to suspect that person of fraud, but have not started a criminal investigation
3. When that person’s bank identifies they may be breaking DWP’s rules
4. When they first apply for benefits, to check if they are eligible
5. Whenever they are receiving benefits
6. None of the above
998. Don’t know

Module 4. Penalties

Intro_4

The next questions are about the way DWP punishes people for committing fraud and error in the welfare benefits system.

Q401

In general, to what extent do you agree or disagree that people who commit benefit fraud should be punished?

Please select one option only.

1. Completely disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Completely agree
998. Don’t know

Q402

Before taking part in this survey, were you aware that DWP criminally prosecutes some fraudulent cases?

Please select one option only.

1. Yes, I knew DWP could do this
2. I wouldn’t have been certain but had assumed DWP could do this
3. I wouldn’t have been certain but had assumed DWP could not do this
4. No, I did not know DWP could do this
998. Don’t know

Q403

Before taking part in this survey, were you aware that DWP can fine claimants for fraud?

Please select one option only

1. Yes, I knew DWP could do this
2. I wouldn’t have been certain but had assumed DWP could do this
3. I wouldn’t have been certain but had assumed DWP could not do this
4. No, I did not know DWP could do this
998. Don’t know

Q404

In some circumstances, DWP has the power to stop or reduce certain benefits, such as Universal Credit, Income Support or Pension Credit, from people who have deliberately given false information in their benefit claim.

How acceptable do you think it is for DWP to remove some benefits from someone who has deliberately given false information when claiming benefits?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q406

Sometimes, people who have knowingly given false information to claim benefits are given a chance to correct this, and provide the right information, when DWP discover the fraud.

If someone admits they have committed fraud and corrects the information they provided, to what extent, if at all, do you think they should still be punished for giving the false information?

1. They should have the same punishment whether or not they correct the information
2. They should have a lesser punishment if they correct the information
3. They should not be punished at all
998. Don’t know

Module 5. Law enforcement powers

Intro_5

Sometimes DWP conducts serious criminal investigations into benefit fraud. These investigations are about complex and sophisticated attacks on DWP’s benefits and grants payments – usually by organised crime groups. It may also investigate individuals who have committed fraud serious enough that they may face going to prison.

These next questions are about who is able to search for and seize evidence and make arrests as part of these investigations.

Q501

As far as you know, at the moment, when DWP is conducting a criminal investigation, who is able to conduct arrests and search and seize evidence as part of the investigation?

Please select all that apply.

1. Specially trained DWP investigators
2. The Police
998. Don’t know

At present, DWP is reliant on the police to conduct arrests and search and seize evidence in serious criminal investigations.

New proposed measures would enable specially trained DWP investigators to apply for a warrant to search and seize evidence (such as fake ID) and to undertake arrests in these investigations. This would mean that DWP may be less reliant on the police, which may save police time and mean searches or arrests may happen more quickly.

Q502

How acceptable do you think it would be for trained DWP investigators to have the power to arrest people suspected of serious and organised benefit fraud, rather than only using the police?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q503

And how acceptable do you think it would be for trained DWP investigators to have the power to search for and seize evidence from people suspected of serious and organised benefit fraud, rather than only using the police?

Please select one option only.

1. Completely unacceptable
2. Unacceptable
3. Neither acceptable nor unacceptable
4. Acceptable
5. Completely acceptable
998. Don’t know

Q504

Imagine a situation where an organised crime group has been producing false identities to make bogus universal credit claims.

Which of these statements comes closest to your view?

Please select one option only.

1. Either trained DWP investigators or the police should be able to seize evidence from members of this group about this fraud
2. Only the police should be able to seize evidence from members of this group about this fraud
3. No-one should be able to seize evidence from members of this group about this fraud
998. Don’t know

Q505

Imagine a situation where someone has committed benefit fraud. The fraud was so large that they may face going to prison. They are invited to an interview with DWP to talk about their benefit claim, but do not attend.

Which of these statements comes closest to your view?

Please select one option only.

1. Either trained DWP investigators or the police should be able to arrest this person for not attending their benefit claim interview
2. Only the police should be able to arrest this person for not attending their benefit claim interview
3. No-one should be able to arrest this person for not attending their benefit claim interview
998. Don’t know

Module 6: Debt recovery

Intro_6

The next questions are about DWP recovering debt that former benefit claimants owe DWP because they were paid too much in benefits. This may be because they intentionally claimed benefits they were not entitled to, or because of a mistake.

Q602

Before taking part in this survey, were you aware that DWP can recover debt that former benefit claimants owe DWP by taking money from their salaries?

Please select one option only

1. Yes, I knew DWP could do this
2. I wouldn’t have been certain but had assumed DWP could do this
3. I wouldn’t have been certain but had assumed DWP could not do this
4. No, I did not know DWP could do this
998. Don’t know

Q603

And before taking part in this survey, were you aware that DWP requires a court order to recover debt in any other way apart from salaries and benefit payments (for example, directly from bank accounts)?

Please select one option only

1. Yes, I knew DWP requires this
2. I wouldn’t have been certain but had assumed DWP would require this
3. I wouldn’t have been certain but had assumed DWP would not require this
4. No, I did not know DWP requires this
998. Don’t know

Module 7: General response to the powers

Q701

Having now answered questions around the proposed new powers regarding fraud and error in the welfare benefits system, on balance how do you feel about these potential new powers?

Please select one option only.

1. Very positive
2. Fairly positive
3. Neutral
4. Fairly negative
5. Very negative
998. Don’t know

Outro_1

The survey is now finished.

Thank you for taking part. Please have a look out for your next survey, soon!

You can now close your browser to exit the survey, or check your balance on the KnowledgePanel portal.

1. The median completion time was in fact 12 minutes and 39 seconds. ↩