Collection

Fraud, Error, Debt and Grants Function

The role of the Fraud, Error, Debt and Grants Function, the services and standards it is responsible for and how it builds professional skills in the Civil Service.

Estimates show government could be losing between £22 and £49 billion per year to fraud and error. Debt owed to government currently stands at over £22 billion. Grant spending accounts for £139 billion, which is around 20% of government expenditure.

The Function provides strategic leadership and sets cross-government standards for fraud, error grant and debt initiatives.

We work with departments to:

  • identify and reduce financial losses through fraud and error
  • improve overdue debt management
  • improve the effectiveness of grants whilst reducing the costs of their administration through the Grants Efficiency Programme
  • identify more fraud and error and make sure changes are made to prevent it.
  • provide counter-fraud remedies and common solutions to cross-cutting issues.

Career opportunities and professional development

The Counter-Fraud Standards and Profession lead the professionalisation of government counter-fraud activity.

Our network of experts set standards and improve the capability of organisations and their people across a range of specialisms.

Contact us

FED@cabinetoffice.gov.uk

Standards

Initiatives

The National Fraud Initiative is a data-matching project across a large number of government organisations, which flags up inconsistencies that might indicate fraud, error or overpayment.

The Debt Market Integrator is an initiative to support government departments to improve debt recovery through shared capacity and multi-agency data analytics.

The Grants Efficiency Programme is working collaboratively with departments to reduce the costs of grants administration; reduce losses from fraud and error in grants, and; increase the effectiveness of grant funding for the tax-payer.

  1. National Fraud Initiative reports

    • Corporate report
  2. Government grants register

    • Transparency data
Published 19 February 2016