Benefit fraud investigators will reportedly be given the power to take money directly from wages as part of new Department for Work and Pensions (DWP) plans to crack down on fraudsters. The measure is one of several far-reaching powers set to be included in the UK Government’s forthcoming Fraud, Error and Debt Bill, according to the Sunday Telegraph.

The Bill, announced by the Prime Minister during the Labour Party conference in September, is intended to target benefit fraud by ‘modernising’ the DWP in an effort to save £1.6billion over the next five years. At present, DWP investigators must secure a court order before deducting money from someone’s wages or bank accounts.

Writing in the Sunday Telegraph, Work and Pensions Secretary Liz Kendall said it was “absurd” that investigators’ powers had not been updated in the last 20 years.

She said: “My team are still, in 2024, sending letters to gather evidence for those suspected of welfare fraud, slowing them down to a snail’s pace when they could be shutting down serious fraud cases.

“Our bill will give them similar powers as HMRC to investigate fraudsters – it’s time we give them the tools they need for the fight.”

As well as the power to deduct money directly from the wages of people who have over-claimed on benefits, the Bill is reported to give investigators the ability to compel information about suspected fraudsters from all private companies, not just banks, utilities and employers.

The DWP pays benefits to around 22.7m people across Great Britain, including 12.7m pensioners, however, the new powers will not extend to the State Pension, which Ms Kendall said would not have been “proportionate”.

She said the enhanced information-gathering powers would allow the state to “stop serious fraud in its tracks by making sure people really are who they say they are”.

But the plans have sparked alarm among privacy campaigners, with Big Brother Watch describing them as “Orwellian” and “a major expansion of government power” that threatened the presumption of innocence.

Ms Kendall dismissed claims that the UK Government would be “snooping” on people’s bank accounts as “nonsense” and insisted there would be human oversight of automated alerts flagging potential fraud.

Similar proposals put forward by the previous government passed the House of Commons but were unable to pass the Lords before Parliament was dissolved for the General Election.

The Government claims fraud and error in the welfare system costs the taxpayer £10 billion a year, while the Chancellor is reported to be considering tax rises and spending cuts worth £40 billion at this month’s Budget in order to avoid a return to austerity.

The expected savings delivered by the Government’s latest proposals amount to an average of £320million per year.

Liberal Democrat MP Steve Darling recently asked DWP “what data banks will have to share under the Fraud, Error and Debt Bill”.

In a written response on October 17 to the shadow spokesperson for work and pensions, DWP Minister Andrew Western, said: “The Fraud, Error and Debt Bill will introduce a range of measures that will interact with banks and Financial Institutions. Information shared will vary by each measure but will always be proportionate, and include strong safeguards being put in place for each.

“Further details will be set out when the Bill is introduced to Parliament shortly.”

New DWP fraud measures

The measures in the Bill will remedy that, giving DWP powers to:

  • Better investigate suspected fraud and new powers of search and seizure, so DWP can take greater control of investigations into criminal gangs defrauding the taxpayer.
  • Make changes to the penalties system, so no one found to have committed fraud against the social security system avoids punishment, bringing increased fairness for claimants who do the right thing.
  • Allow DWP to recover debts from individuals who can pay money back but have avoided doing so, bringing greater fairness to debt recoveries.
  • Eligibility Verification – require banks and financial institutions to examine their own data sets to highlight where someone may not be eligible for the benefits they are being paid.

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