Consultation outcome

National Fraud Initiative 2024 to 2025 Proposed Work Programme and Scale of Fees (HTML)

Updated 29 August 2024

Executive Summary

Consultation purpose

1. This consultation sets out proposals for the National Fraud Initiative (NFI) 2024/25 work programme and associated scale of fees.

2. The NFI work programme includes data that we intend to collect and match as part of the NFI 2024/25 data matching exercise, to help detect and prevent fraud. The proposed fee scale sets out the cost to NFI participants for matching this data. 

3. The purpose of this consultation is to seek views from organisations required under legislation to submit data to the NFI, and other relevant organisations, on the proposed data requirements and fees for the NFI 2024/25 exercise.

NFI 2024/25 work programme and fees proposals

4. The proposals outlined in this document set out some specific changes to consider for the forthcoming NFI 2024/25 exercise. These include:

• a proposal to re-introduce adult social care datasets into the NFI work programme, subject to the completion of a Legislative Reform Order (LRO) to amend the Local Audit and Accountability Act (LAAA) 2014 and enable a legal gateway for sharing this data;
• a proposal to uplift participant fees by 6%, equivalent to 3% per annum over a two-year period, to help cover the cost of the NFI exercise.

5. There are also proposals to retain existing aspects of the work programme and fee scale which include to:

• retain all existing NFI datasets as part of the NFI 2024/25 work programme;
• retain the existing fee model which determines fees based on average dataset submissions and the number of high risk NFI matches by organisation type;
• retain the penalty for late or poor quality data submissions at 5% of the standard NFI fee for each organisation.

Relevant legislation

6. The consultation is undertaken to fulfil the requirements of statutory data matching powers set out in Schedule 9 to the LAAA 2014. Specifically, paragraph 6 (1,4) which states that:

(1) A relevant minister must prescribe a scale or scales of fees in respect of data matching exercises.

(4) Before prescribing a scale of fees under this paragraph, a relevant minister must consult

(a) the persons within paragraph 2(2),

(b) such representatives of persons within paragraph 2(2) as the minister thinks appropriate, and

(c) such other bodies or persons as the minister thinks appropriate.

7. The consultation is primarily for public sector bodies in England that have a requirement to submit data to the NFI, as defined in paragraph 2(1,2) of schedule 9 to the LAAA 2014. These include:

(a) A relevant authority

(b) A best value authority which is not a relevant authority

(c) An NHS Foundation Trust

8. Data matching is also bound by statutory guidance through a Code of Data Matching Practice, which explains the process and gives guidance to persons and bodies involved in data matching exercises.

How will proposals be implemented?

9. Subject to the outcome of the consultation, we will implement the proposed changes outlined in this consultation for the NFI 2024/25 exercise. We will formally request data in summer 2024.

Consultation process

10. The consultation includes all NFI mandatory participants in England set out in Appendix 1. It is also open to organisations that have an interest in either the NFI, or the bodies required to take part in the NFI, such as some government departments, non-departmental public bodies and audit administrations in the devolved governments of Scotland, Wales and Northern Ireland.

Timing and duration of this consultation

11. The consultation period will commence on 2nd April 2024 and will be open to responses for four weeks.

12. The consultation will close on 30th April 2024.

13. A summary of consultation feedback and our formal response will be published in July 2024, along with the confirmed work programme and fees for the NFI 2024/25 exercise.

How to respond

14. Responses can be sent to the NFI team at [email protected]. In your response you may wish to consider the list of questions at the end of this document, to ensure you address the specific proposals set out in this consultation.

Confidentiality

15. Please indicate in your response whether you are content for your comments to be published, with or without attributing them to you or your organisation. 

Alternative formats

16.  Alternative formats of this publication can be requested from [email protected]

Background

NFI and the Public Sector Fraud Authority

17. The NFI is a data matching exercise that helps to detect and prevent fraud. It uses legislative powers set out in the LAAA 2014 to collect, process and compare data to see to what extent they match. It identifies and discloses inconsistencies within data that may indicate fraud and require further investigation by NFI participants.

18. The NFI is part of the data and intelligence service within the Public Sector Fraud Authority (PSFA). Launched in August 2022, the PSFA’s role is to work with departments and public bodies to understand and reduce the risk of fraud. The scope of the PSFA data and intelligence service is to aid public bodies’ access to data and counter-fraud technologies to enhance the use of data and intelligence across the public sector to find and reduce fraud.

Context

20. Fraud is the most commonly experienced crime in the UK, accounting for around 41% of all crime^{[footnote 1]}. In the public sector, it is estimated that at least £33.2 billion of taxpayer money is lost to fraud and error each year. This is equivalent to 15p lost to fraud for every £1 raised by income tax^{[footnote 2]}. With increased economic uncertainty, there is a risk that the motivation to commit fraud will increase.

21. The effect of fraud against the public sector is more than financial; it damages trust in government, compromises public services and is recognised as a national security threat.

22. Digital advancement has revolutionised the way public sector organisations work, but has also provided fraudsters with new methods and opportunities to undertake sophisticated fraudulent activity.

23. Using its data matching capabilities, the NFI targets both existing and emerging fraud risks, helping to detect fraud and recover public funds that are fraudulently obtained.

NFI achievements

24. The NFI continues to enhance data matching capabilities and broaden data sharing opportunities across the public and private sector. Working with around 1,000 organisations from across the UK, we aim to find innovative solutions to complex fraud problems, achieving effective, measurable outcomes in response to emerging fraud risks. Achievements include:

• Detecting and preventing financial loss, including £443 million in fraud, error and overpayments from the NFI 2020/21 National Exercise^{[footnote 3]}. A further £171 million of audited savings have been identified from the first year of the NFI 2022/23 National Exercise.
• Continuous innovation, including maintaining a pipeline of data matching pilots targeted towards both the public and private sectors, to maximise access to a wider range of data for counter fraud purposes. An example includes a tenancy fraud pilot, launched in Autumn 2022 which combines public and private sector data to help detect subletting of social housing and unlawful succession. With the launch of a second phase in spring 2024, this pilot is bringing in data such as AirBnB and Universal Credit to help councils detect anomalies that may lead to recovery of social housing properties.
• Continuing to develop public and private sector partnerships, including matching private sector data against public sector data held within the NFI environment, to highlight misrepresentation of identity or residency by service applicants. This area of work aligns with the recommendations set out in the Economic Crime Plan 2023-2026. It has expanded from utility companies to car hire and insurance, increasing financial outcomes from £3.2 million in 2020 to £20.8 million in 2023.
• Work to develop the FraudHub tool which allows organisations to submit data to target local fraud risks at any point in time. FraudHub membership has more than doubled since 2020, with 45 organisations now regularly accessing targeted data matching activity to support their local area fraud strategies.
• Developing a new NFI strategy for 2024-2028, setting out our vision and objectives for the next 4 years. This is due for publication in summer 2024.

Proposed Work Programme

25. We have reviewed the existing NFI work programme to consider the datasets included in the NFI. Our proposals are to:

• re-introduce adult social care datasets into the NFI work programme, subject to the completion of a Legislative Reform Order (LRO) to amend the Local Audit and Accountability Act (LAAA) 2014 and enable a legal gateway for sharing this data;
• retain all existing NFI datasets as part of the NFI 2024/25 work programme.

26. Appendix 1 sets out the proposed data requirements for all mandatory participants, by organisation type, for the NFI 2024/25 exercise.

Mandatory dataset requirements

Adult social care data

27. Since the NFI 2020/21 Exercise, we have postponed the inclusion of data matching that targets fraud in the social care sector. This is in response to amendments to the National Health Service (NHS) Act 2006, which reclassified social care data as data for “medical purposes”^{[footnote 4]}.

28. Data that is held for “medical purposes” and where individuals can be identified, meets the definition of “patient data” and is subject to restrictions on disclosure under the LAAA 2014. One such restriction is that patient data can only be shared with “relevant NHS bodies”. Subsequently, current legislation does not permit the sharing of social care data match results with local authorities as part of the NFI programme.

29. Social care datasets for NFI purposes include residential care homes data and personal budget data. Prior to the legislative amendment to the NHS Act 2006, we matched these datasets against deceased person data to identify cases where the local authority may continue to make payments after a death has occurred. Personal budget data was also matched between local authorities to identify duplicate payments across one or more councils.

30. In the previous NFI work programme and fees consultation, we highlighted our intention to explore options to recommence the matching of social care data through the NFI. Recent engagement suggests support for this approach, for example, 93% of respondents^{[footnote 5]} from the 2022 NFI survey agreed that there is a strong need for the NFI to provide a social care data matching service to help identify fraud, and protect adult social care funding. Similarly, the CIPFA Fraud and Corruption Tracker Survey 2020 highlighted that local authorities across the UK identified adult social care as one of their highest risk areas^{[footnote 6]}.

31. The NFI is currently working on a Legislative Reform Order (LRO) to secure a legislative change to the restrictions on the use of patient data within the LAAA 2014, and reverse the unintended consequences of amendments to the NHS Act 2006. Once enacted, the LRO will allow local authorities to resume social care data matching in the NFI for the purposes of identifying and preventing fraud.

32. To ensure we can act as quickly as possible, we are simultaneously planning for the return of social care data during the NFI 2024/25 exercise, alongside work to secure parliamentary enactment of the LRO. We believe this approach is the most efficient in enabling us to resume social care matching at the earliest possible opportunity.

33. We are therefore proposing to mandate the submission of both residential care homes and personal budget data in the NFI 2024/25 work programme, but we will only request, collect and match this data once we have the legal gateway to share the resulting matches back to local authorities.

34. Operationally, if the LRO is not enacted before we request and secure other NFI datasets in line with the NFI 2024/25 timetable, we may collect and match social care data separately at a later date, sharing the results in a supplementary match release. Should this occur, we will ensure that we communicate data requirements, including data submission dates as early as possible, to enable local authorities to prepare for and benefit from its inclusion.

Existing datasets

35. We have reviewed the existing mandatory datasets in the NFI work programme to determine the benefits, financial or otherwise, they have the potential to yield from their inclusion in the NFI. Our aim is to ensure that the data we collect and match is beneficial to participants and proportionate under data protection legislation to merit its inclusion in the exercise.

36. Our review highlighted that the majority of datasets continue to show significant financial savings for participants in the form of recovered overpayments, or preventative forward savings, justifying the need to continue with further NFI matching.

37. As identified in the last NFI consultation, the financial savings from Right to Buy (RTB) data remain low in comparison to other data areas and to previous NFI exercises. Despite this, we know that RTB annual sales remain consistent^{[footnote 7]}, and that local authorities must continue to manage the risk of fraudulent claims through preventing or detecting individuals that are ineligible to acquire council property under the RTB scheme. Some local authorities are voluntarily matching RTB data through the NFI FraudHub tool, indicating there is still value in using data matching to address fraud risks in this area.

38. Through engagement with local authorities, we will continue to review this data to better understand how well it addresses RTB fraud risks as a match in its own right, or as supplementary data to support the identification of wider housing or benefit fraud risks. We will use feedback to explore whether there is the potential to develop and enhance the matching through either the main NFI exercise, or pilot work, to increase the potential for better results.

39. It is worth noting that RTB data continues to be beneficial when used as a match against other datasets, in particular for means tested benefits and discounts such as housing benefit and council tax reduction, to help identify capital savings which may exceed thresholds for benefit entitlement.

40. Therefore, following our dataset review, we are proposing to retain all existing datasets for the NFI 2024/25 exercise.

Pilots and new data

41. As well as reviewing the datasets included in our existing work programme, we have also assessed whether or not we are in a position to add any additional data into the work programme based on results from pilot data matches.

42. Pilot data matching involves finding innovative solutions to new fraud risks through new data, match combinations and matching techniques. We have an ongoing pipeline of pilot work areas, which are under continuous development and evaluation. Pilots are usually funded from within the NFI budget which means that organisations volunteering to take part in a pilot are not charged for participation. However, should the NFI incur increased costs when a pilot is rolled out nationally, this is considered as part of the scale of fees consultation.

43. Transition of pilot data matches into the core NFI work programme is based on evidence that the pilot adequately addresses fraud risks and will continue to do so when extended to a national level. Only when we are satisfied that this is the case will we introduce them into the NFI work programme. For example in the current NFI 2022/23 exercise, following a successful pilot, we introduced an additional match using existing residents parking permit data to identify individuals with multiple parking permits across council boundaries.

44. We currently have a number of ongoing pilots at varying stages, targeting a range of fraud risk areas recommended to us by participants. These pilots use either new data, or existing data already collected as part of the NFI work programme. Increasingly, we are supplementing pilot data collected from mandatory participants, with private sector data provided on a voluntary basis to add further scope to the matching. For example, our current tenancy fraud pilot to help identify illegal subletting and unlawful property succession incorporated several private sector datasets, providing additional intelligence to support the matches.

45. We are also in the early stages of two further pilots:

a. a pilot to collate and match employment agency data, to enhance our existing payroll data matches and help identify individuals fraudulently working multiple jobs simultaneously;

b. a pilot that matches existing council tax data to Disclosure of Death Registration Information (DDRI) data. This will enable councils to review or remove discounts or exemptions for council tax addresses that are potentially being claimed fraudulently.

46. Once complete, we will evaluate and assess whether the level of fraud these pilots detect and prevent is sufficient to warrant replicating them at a national level in future NFI exercises.

47. Therefore, considering the position of our existing pilots, we are not proposing to mandate any additional data for the NFI 2024/25 work programme.

Questions to consider:

A. Do you agree with the proposal to mandate the social care datasets of residential care homes and personal budgets in the NFI 2024/25 exercise, once the Legislative Reform Order to amend the LAAA 2014 is complete? Please provide your reasons why.

B. Do you have any comments on the proposed data requirements for the 2024/25 work programme, set out in Appendix 1?

Proposed Scale of Fees

48. The NFI fee scale sets out the fees chargeable to NFI participants for taking part in the NFI exercise. The fees help to cover the cost of the NFI exercise including the collation, processing and matching of participant data.

49. We have reviewed the existing NFI fee scale in respect of the NFI 2024/25 exercise. Proposals include to:

• retain the existing fee model which determines fees based on average dataset submissions and the number of high risk NFI matches by organisation type;
• subsidise the cost of any social care data matching following its reintroduction into the NFI work programme, through unspent funds from the NFI 2020/21 exercise;
• keep National Exercise fees, and fees for FraudHub users independent from one another;
• increase National Exercise fees by 6% (3% per annum) linked to our programme cost increases between 2021 and 2023, with the aim to minimise cost pressures for participants;
• retain the penalty for late or poor quality data submissions at 5% of the standard NFI fee for each organisation.

50. Table 1 sets out the proposed NFI 2024/25 fees by organisation type. It shows:

• NFI 2024/25 standard fee – including a 6% uplift;
• NFI 2024/25 penalty fee – 5% increase on the standard fee;
• NFI 2024/25 uplifted fee – the sum of the standard fee, plus the penalty fee, applicable to organisations that do not comply with data submission requirements;
• NFI 2022/23 standard fee – for comparison to the previous NFI fee scale;
• Standard fee change - showing the monetary uplift from the previous fee scale.

51. Fees are rounded to the nearest £5 following the application of uplifts and penalties.

Table 1 – Proposed Fees for NFI 2024/25

Organisation	NFI 2024/25 Standard Fee £	NFI 2024/25 Penalty Fee £	NFI 2024/25 Uplifted Fee £	NFI 2022/23 Standard Fee £	Standard Fee change £
London Borough Council	4370	220	4590	4,120	250
Metropolitan Borough Council	4370	220	4590	4,120	250
Unitary Authority	4040	200	4240	3,810	230
County Council	3930	195	4125	3,705	225
County Council (with fire)	4560	230	4790	4,300	260
District Council	2690	135	2825	2,535	155
Pension Authority	2635	135	2825	2,485	150
Combined Authority	1315	65	1380	1,240	75
Passenger Transport Executive	1315	65	1380	1,240	75
Transport for London	1315	65	1380	1,240	75
Police	1315	65	1380	1,240	75
Fire and Rescue Authority	1260	65	1325	1,190	70
Waste Regulation or Disposal Authority	1260	65	1325	1,190	70
Greater London Authority	1260	65	1325	1,190	70
NHS Trust	1260	65	1325	1,190	70
Integrated Care Board	1260	65	1325	1,190	70
Foundation Trust	1260	65	1325	1,190	70

Fee model

Fee model review

52. The existing model to determine participant fees uses the number of datasets each organisation typically submits to the NFI, along with the number of high risk (HR) data matches that are returned to different organisations. We use this data to generate an average score for each organisation type, with higher fees applied to organisations with higher scores, weighted 3:1 in favour of HR matches. For example, an organisation that submits a low number of datasets, but where those datasets typically generate a number of HR scored matches, may pay more than an organisation that submits more data, but receives on average a lower number of HR scored matches from those datasets.

53. The dataset aspect of the model reflects the costs we incur to process and match NFI data, where a greater number of datasets means higher data processing charges. The inclusion of HR matches gives an indication of the potential benefits participants could gain from NFI data matching. Greater numbers of HR matches increase the likelihood that an organisation will identify more fraud and error, and subsequently benefit more from recovery of overpayments and preventative savings. The inclusion of these matches also reflects the type and volume of data submitted by organisations to the NFI, where high data record counts and prominent fraud risk areas are more likely to yield a greater number of HR matches for investigation.

54. We have undertaken a reasonableness check on the existing fee model by recalculating organisation scores using the most recent data from the NFI 2022/23 exercise. This did not result in any anomalies or changes to the fee scale. In addition, data from the last two NFI exercises indicate that average savings for each organisation type are broadly in line with their position on the fee scale. Organisations at the top and bottom of the fee scale received the highest and lowest average savings respectively.

55. Our review indicates that the data and rationale that underpins the fee model sufficiently meets the aim of levying fees in a way that considers actual data processing costs, whilst ensuring the cost-benefit of taking part is fair across different organisations. Subsequently, we propose to retain the existing fee model for the NFI 2024/25 exercise.

FraudHub users

56. FraudHub is a voluntary NFI product which enables subscribed users to access regular data matching targeted at local fraud risks, supplementary to the two-yearly NFI exercise. The benefits of this service include flexibility over what data to match and when, and the potential for reduced overpayments due to early detection and recovery of fraudulent activity.

57. Regular FraudHub data matching undertaken between the main NFI exercise helps strengthen an organisation’s counter-fraud response to fraud risks. Where data matching is consistent, increased fraud detection may reduce fraud and financial outcomes identified through the two-yearly NFI exercise. As potential benefits are a core part of the NFI fee scale, we considered whether it is appropriate to reflect supplementary FraudHub matching in the NFI 2024/25 fee scale, through potential discounts for FraudHub users.

58. In response to feedback from the previous consultation, we undertook some analysis to assess to what extent FraudHub matching affects the match returns and potential benefits available from the two-yearly NFI exercise. For the analysis, we identified the datasets submitted for matching in FraudHub between 2021 and 2023. For these datasets we identified the corresponding data match report and compared average match numbers from the NFI 2020/21 and NFI 2022/23 exercises to measure any significant reduction in returns between FraudHub participants and non FraudHub participants.

59\/ Findings show that across dataset areas where supplementary FraudHub matching had taken place, organisations within a FraudHub received on average 4% less matches than organisations not in a FraudHub in the subsequent National Exercise. However, when analysing results across different data reports and fraud risk areas, significant reductions in average match returns were confined to only two data reports (housing waiting list to deceased data and blue badge to deceased data), with minimal change in other data areas.

60. Our analysis indicates that whilst regular FraudHub matching has the potential to reduce match returns in the two-yearly NFI exercise, its use is not currently broad enough to diminish the value of the main NFI exercise. The main NFI exercise benefits from multiple national datasets and data match reports, matched widely both within and between organisations.

61. Based on our review, we do not think it is appropriate to adjust the NFI 2024/25 exercise fees for FraudHub users, to account for supplementary FraudHub matching. We will review this position for future consultations as FraudHub membership continues to grow.

62. We therefore propose to keep fees for the two-yearly NFI exercise and the FraudHub product independent of one another and look separately at FraudHub fees to ensure we maintain value for money (outside of the remit of this consultation).

Social care data

63. Social care data was incorporated in the NFI 2020/21 work programme and scale of fees, however we were unable to collect and match data during that exercise. We therefore did not incur data processing charges for social care datasets during that time.

64. In the following NFI 2022/23 exercise, we adjusted NFI fees to reflect our reduced data processing costs from removing social care data from the NFI work programme. Participants responsible for social care data received a fee reduction of £220 (£110 per dataset) linked to reduced data submission requirements.

65. Our 2024/25 work programme proposes to collect and match social care data as part of the NFI 2024/25 exercise, subject to enactment of the LRO. As the timing of the LRO is not certain, we have excluded this data from the fee calculations. Should we subsequently incur data processing charges from our IT supplier to process and match this data, these costs will be covered through unspent funds from the NFI 2020/21 exercise, resulting in no additional charges to organisations responsible for social care data in NFI 2024/25. Subject to enactment of the LRO, social care data will be incorporated back into the NFI fee scale for the NFI 2026/27 exercise onwards.

Questions to Consider

C. Do you have any comments on the proposal to retain the existing fee model for the NFI 2024/25 exercise? Please consider:

i) the fee model used to generate the NFI 2024/25 fee scale;

ii) the review of FraudHub use and its effect on match returns for the two-yearly NFI exercise;

iii) the continued exclusion of social care data from the fee model and the proposal to supplement the cost of social care data matching through unspent funds from the NFI 2020/21 exercise.

Fees

Fee uplift

66. Our approach in the last NFI fees consultation was to uplift fees in line with inflation. This was in response to feedback that incremental inflationary fee increases are easier for participants to manage. The risk of this approach is that fees are susceptible to significant increases in periods of rapid inflationary growth.

67. For the NFI 2024/25 exercise, we have looked at inflation rates since fees were last calculated in 2021 and note a growth in inflation over the past two years of around 14.5%. Applying this rate would levy increases between £170 and £625 per organisation on existing fees, and put increased pressure on participant budgets.

68. Our financial aim for the NFI exercise is to levy manageable fees for participants, balanced against NFI operating costs, development costs and sustainability of the NFI programme. Therefore, for the NFI 2024/25 exercise we are proposing to uplift fees below inflation, in line with our operational cost increases over the past two years, which are currently at 3% per annum (6% overall). This uplift will apply to all mandatory fees.

Penalty fee

1. After successful implementation of our penalty fee policy aimed at encouraging timely and good quality data submissions, we propose to retain the additional fee for participants that fail to comply with data submission requirements for the NFI 2024/25 exercise. The penalty fee will remain at 5% of the standard NFI 2024/25 fee, levied to organisations that submit late data, or data that does not meet data quality thresholds.

2. Social care data will be exempt from any penalty charges.

Questions to Consider

D. Do you agree with proposals to uplift fees by 6% (equivalent to 3% per annum), linked to our operational cost increases between 2021 and 2023? Please provide your reasons why.

E. Do you have any comments on the proposal to retain the penalty fee at 5% for late or poor quality data submissions?

Billing

Invoicing arrangements

72. The NFI 2024/25 work programme and scale of fees covers the financial years 2024/25 and 2025/26. Participants will be billed in one instalment between January and March 2025.

73. The NFI web application includes a dedicated billing page, which enables participants to provide billing information and purchase order numbers for inclusion on the invoices. We will request these details prior to raising invoices.

Questions to consider

74. A full list of the questions included within this consultation are set out in Table 2. You may wish to consider these questions in your consultation response, along with any other comments you may have about the proposals on the NFI 2024/25 work programme and scale of fees.

Table 2 – Summary of Consultation Questions

Ref	Consultation Question
A	Do you agree with the proposal to mandate the social care datasets of residential care homes and personal budgets in the NFI 2024/25 exercise, once the Legislative Reform Order is complete? Please provide your reasons why
B	Do you have any additional comments on the proposed data requirements for the 2024/25 work programme, set out in Appendix 1?
C	Do you have any comments on the proposal to retain the existing fee model for the NFI 2024/25 exercise? Please consider: i) the fee model used to generate the NFI 2024/25 fee scale ii) the review of FraudHub use and its effect on match returns for the two-yearly NFI exercise; iii) the continued exclusion of social care data from the fee model and the proposal to supplement the cost of social care data matching through unspent funds from the NFI 2020/21 exercise
D	Do you agree with the proposal to uplift fees by 6% (equivalent to 3% per annum), linked to our operational cost increases between 2021 and 2023? Please provide your reasons why
E	Do you have any comments on the proposal to retain the penalty fee at 5% for late or poor quality data submissions?	z

Appendix 1

Organisation

• London Borough Council
• Metropolitan Borough Council
• County Council
• County Council with Fire
• Unitary Authority
• District Council
• Combined Authorities^{[footnote 8]}

Mandatory Dataset Requirement
(where data is held by the organisation)	Notes
Blue badges	Supplied by Blue Badge Digital Service
Concessionary travel permits
Council tax	Annual data submission
Council tax reduction scheme
Electoral register	Annual data submission.
Housing benefits	Supplied by DWP
Housing tenants
Housing waiting list
Payroll
Pensions
Personal budgets Residential care homes	Subject to completion of a Legislative amendment to the LAAA 2014
Resident parking permits
Right to buy
Students eligible for a loan	Supplied by Student Loans Company
Taxi driver licences
Trade creditors’ payment history
Trade creditors’ standing

Organisation

• Passenger Transport Executive
• Transport for London
• Greater London Authority

Mandatory Dataset Requirement
(where data is held by the organisation)	Notes
Concessionary travel permits
Payroll
Pensions
Residents parking permits
Trade creditors’ payment history
Trade creditors’ standing

Organisation

• Police
• Fire and Rescue Authority
• Waste Authority

Mandatory Dataset Requirement
(where data is held by the organisation)	Notes
Payroll
Pensions
Trade creditors’ payment history
Trade creditors’ standing

Organisation

• Pension Authority

Mandatory Dataset Requirement
(where data is held by the organisation)	Notes
Pensions

Organisation

• Integrated Care Board
• NHS Trust
• Foundation Trust

Mandatory Dataset Requirement
(where data is held by the organisation)	Notes
Payroll
Trade creditors’ payment history
Trade creditors’ standing

1. Office for National Statistics, Crime in England and Wales ending September 2022 ↩

2. Cross government fraud landscape annual report 2022 ↩

3. Savings reported between 1st April 2020 and 31st March 2022 ↩

4. Section 251 (12A) of the NHS Act 2006 ↩

5. From a total of 84 respondents ↩

6.   Fraud and corruption tracker, p. 11. ↩

7. Live tables on social housing sales ↩

8. Only payroll and trade creditor data is mandatory for Combined Authorities, however any other data held can be submitted on an optional basis. ↩