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HEFCE closed at the end of March 2018. The information on this website is historical and is no longer maintained.

Many of HEFCE's functions will be continued by the Office for Students, the new regulator of higher education in England, and Research England, the new council within UK Research and Innovation.

The HEFCE domain - - will continue to function until September 2018. At this point we will close the site entirely and all its information will only be available from the National Web Archive.


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Data reconciliations

The calculation of the grant is based on, and verified against, data supplied by institutions in statistical surveys, and against Higher Education Statistics Agency (HESA) data and Individualised Learner Record (ILR) submissions.

Approach to data reconciliations

We perform data reconciliation work primarily in the areas listed on our Funding data reconciliations page.

Re-creations - general method

Every year we generate re-creations for all institutions by applying our algorithms (see Documentation) to HESA/ILR student data to produce derived fields. These derived fields are then aggregated to produce re-creations of the original funding returns.

We then produce summaries and comparisons of the main elements of each re-creation against the original funding return and present these in an Excel workbook. The re-creation outputs can be accessed from the HEFCE extranet.

The necessarily complex process of explaining and resolving differences between data sources places a burden on institutions and HEFCE. To ensure this burden is both manageable and appropriate, we employ thresholds to select which institutions must respond to a data reconciliation.

For HESES and cost centre assignment monitoring these thresholds are set in terms of the funding differences arising from the comparisons. This is a risk based assessment, intended to identify and select those institutions whose data differences are most likely to have a material effect on their funding allocations.

Action required

Where the comparison of a re-creation and an original funding return indicates discrepancies exceeding any of the selection criteria of the funding and monitoring data exercise we require a response in the form of an action plan detailing how the institution will reconcile the two data sources.

We expect the explanations that institutions provide for discrepancies between the two data sources to fall into one or more of the following categories:

  • errors in HESA or ILR student data
  • errors or estimation discrepancies in the original funding return
  • problems of fit with the re-creation algorithms
  • errors in Learning Aims Reference Application (LARA) data (only applicable to FECs).

Explanations for discrepancies

  • Errors in HESA data: where errors are found in HESA data we require HE institutions to submit a revised, complete and valid HESA return directly to HESA, but only once these changes have been notified to us through an action plan, and we have approved the plan. For further details on this process see How to amend HESA data.
  • Errors in ILR data: where errors are found in ILR data we require colleges to submit to us amendment files, detailing the corrections to be made to the ILR return, but only once these changes have been notified to us through an action plan, and we have approved the plan.
  • Errors or estimation discrepancies in original funding return: if we find, either through data reconciliations or audit that the original funding return does not reflect the outturn position for the year, and this is due to errors or estimation discrepancies, then the re-creation will supersede the original funding return. Consequently, it will not be necessary for institutions to submit corrections to the original funding return.
  • Problems of fit with the re-creation algorithms: we do not normally expect that problems of fit with the re-creation algorithms will fully explain discrepancies that exceed the selection thresholds. However, where a problem of fit between our algorithms and the funding return definitions contribute to a discrepancy, an explanation will be required of where the problem occurs, and its impact, through the action plan. In addition, institutions will need to provide a primary derived field override file to enable us to correct the problem of fit with our algorithms for those data affected.
  • 'Errors in the LARA: These errors occur where ILR data is correct, but data for a learners' aim on the LARA are erroneous. Please contact us at for further information if this discrepancy occurs. 

Further process details

If institutions do not provide satisfactory explanations for discrepancies or do not respond within the given timescales, we may carry out further investigations. This may include visits to institutions by us or our agents, to gain assurances concerning one or more of the following:

  • the reliability of data returns
  • the understanding of methods used and technology employed to compile data returns
  • the ability to respond in a full and timely manner to this exercise. 

To gain these assurances we may need to collect or review data as part of these visits.

Where an institution fails to respond on time, or the response is not credible, we may base any subsequent allocation of funds on our own estimate of student activity. Institutions that do not respond on time are more likely to be audited. 

Funding implications

At the end of the reconciliation process we ask institutions to confirm the re-creation reasonably reflects the outturn position for the year. Consequently the re-creation supersedes the original funding return and any resulting grant adjustments are made, subject to any appeals process that may apply and the availability of our funds.

Page last updated 23 January 2015