Example matches
See below some practical examples of what NFI flexible matching can be used for. We are also looking at ways of expanding the service to address emerging risk areas.
If you have additional risk areas that you think the flexible matching service could address, either based on existing NFI datasets or new datasets, please contact us.
Example 1: More frequent mortality screening
“The NFI Helped identify 2,910 cases where pensioners had died but payments were continuing identified by pension schemes. The average pension overpayment, actual plus estimated, was £33,677″
Source: NFI report May 2012
Submit data relating to pensions, blue badges and concessionary travel for mortality screening matching to DDRI1data in September and DWP data the following June.
This provides a flexible and affordable solution for schemes of all sizes enabling monthly screening, if preferred.
DWP deceased records include National Insurance numbers and records of deaths of UK citizens abroad. This enables the NFI to give an accurate and comprehensive match.
Cost per matching run per body
| Pensions data file (7,500 records) |
£350
|
| Blue badges data file (3,500 records) |
£350
|
| Concessionary travel passes data file (9,000 records) |
£350
|
| Total for DDRI |
£1,050
|
| Cost for repeating again through DWP |
£1,050
|
| Total cost for two matching runs |
£2,100
|
Example 2: Council Tax Single Person Discount (SPD) data match to identify incorrectly awarded discounts
“Local authorities identified £50 million SPD awarded incorrectly. The cumulative total since the NFI started this match is £114 million. Councils have stopped discounts in over 99,000 cases”
Source: NFI report May 2012
Submit council tax and electoral register data in the NFI off-year 2 to detect council tax SPD fraud.
Cost per matching run per body
| Council tax data file |
£300
|
| Electoral register |
£300
|
| Total cost |
£600
|
Example 3: Housing benefit to payroll data match to identify undeclared income
“The NFI helped councils in England to uncover benefit frauds and overpayments worth £31 million. Action taken against benefit fraudsters included 636 prosecutions, 564 administrative penalties and 689 cautions. The average housing benefit overpayment in England was £4,038″
Source: NFI report May 2012
A group of neighbouring organisations (local authorities, housing associations, NHS bodies), as a syndicate, can submit current housing benefit claimants and payroll data for cross matching across the syndicate.
Cost per matching run per body
| Housing benefit data file |
£300
|
| Payroll data file |
£300
|
| Total cost |
£600
|
| Cost for repeating twice |
£1,200
|
| Cost of repeating four times |
£2,400
|
Example 4: Payroll to trade creditor to identify instances where an employee and trade creditor are linked by the same bank account or the same address
“The NFI payroll to creditor payments matching was strengthened in 2010/11 to include bank account and address matches. Outcomes now total £123,000″
Source: NFI report May 2012
Submit data relating employees to identify interests in companies that your organisation is trading with, possible procurement corruption or where a member of staff has set up a creditor with their own bank details to receive payments they are not entitled to.
Cost per matching run per body
| Payroll data file |
£300
|
| Trade creditors standing data file3 |
£300
|
| Trade creditors payment history data file | |
| Total cost |
£600
|
| Cost for repeating twice |
£1,200
|
Example 5 : Social housing data matching identifying individuals that are not eligible for social housing before offering a tenancy
The frequency of the match can be timed to suit your risk assessment (for example every quarter, half year or yearly)
“321 false applications were removed from housing waiting lists following a pilot with London borough councils”
Source: NFI report May 2012
A social housing provider can submit data relating to individuals near or at the top of the housing waiting list for matching against the NFI national datasets (such as other housing tenancy data and UK Border Agency Immigration data).
Cost per matching run per body
| Housing waiting list data file |
£300
|
| Total cost |
£300
|
| Cost for repeating twice |
£600
|
| Cost for repeating four times |
£1,200
|
Example 6: Regional social housing data matching to identify potential sub-letting or multiple tenancies
“321 false applications were removed from housing waiting lists following a pilot with London borough councils”
Source: NFI report May 2012
A group of neighbouring organisations (local authorities and housing associations), as a syndicate, can each submit current housing tenants, current housing waiting list and housing benefits data for cross matching across the syndicate.
Cost per matching run per body
| Housing tenants data file |
£300
|
| Housing waiting list data file |
£300
|
| Housing benefits data file |
£300
|
| Total cost |
£900
|
| Cost for repeating twice |
£1,800
|
Example 7: Preventing illegal working
“164 employees were dismissed or asked to resign because they had no right to work in the UK. Employers are liable for a penalty of up to £10,000 if they employ an illegal worker”
Source: NFI report May 2012
An employer can submit payroll data for matching against the NFI national datasets (such as other payroll data and UK Border Agency Immigration data).
Cost per matching run per body
| Applications for employment data file |
£300
|
| Total cost |
£300
|
| Cost for repeating twice |
£600
|
1 General Registrars Office DDRI matching attracts the same fee as DWP matching. This data is refreshed monthly. Department for Work and Pensions matching will be available every six months (November and June). The fee is based on the number of records submitted (see Appendix 2). In the NFI 2010/11 cycle only 3.6 per cent of participants submitted more than 50,001 records.
2 The NFI mandatory SPD match is every two years (the last exercise was October 2011).
3 The trade creditor payment history and standing data are for the most part both required for matching and so attract a single dataset charge.