DWP Annual Report & Accounts 2022-23

Public Accounts Committee Closed Inquiry
Opened: 24 May 2023 Closed: 29 Apr 2024 Parliament page
In November 2022 the Committee reported that the Department for Work and Pensions’ “ excuses for unprecedented and unacceptable levels of benefit fraud and error don’t stand up ”. Based on the National Audit Office’s report on DWP’s Annual Accounts for 2022-23 the Committee will question senior officials at the … Read more
11 Recommendations
22 Conclusions
1 Report
1 Oral session
3 Letters
1 Event
Activity timeline 7 events
25 Mar
2024
Correspondence
8 Mar
2024
Report published
6 Dec
2023
Report published
9 Nov
2023
Correspondence
17 Oct
2023
Correspondence
18 Sep
2023
Oral evidence
18 Sep
2023
Formal meeting (oral evidence session) · Room 15, Palace of Westminster
Oral evidence sessions 1 session
18 Sep 2023
View on parliament.uk
DWP Annual Report & Accounts 2022-23
Bozena Hillyer · Department for Work and Pensions Catherine Vaughan · Department for Work and Pensions Neil Couling · Department for Work and Pensions Peter Schofield CB · Department for Work and Pensions Richard Hawthorn · His Majesty Revenue and Customs
Title HC No. Published Items Response
Fourth Report - The Department for Work & Pensions Annual Report… HC 290 6 Dec 2023 33 Responded
Recommendations & Conclusions
11 results
Clear
6 Conclusion Rejected
Fourth Report - The Department for…
Assess impact of data analytics and machine learning on legitimate claims and specific groups.
DWP has not yet done enough to understand the impact of machine learning on customers and provide them with confidence that it will not result in unfair treatment. DWP is expanding its use of advanced data analytics to tackle fraud. … Read more
Government Response
The government disagrees with detailing specific metrics for publication, citing a need to avoid compromising fraud detection. However, it will report annually on the impact of data analytics on protected groups and vulnerable claimants, starting with the 2023-24 Annual Report.
HM Treasury
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1 Conclusion Rejected
Fourth Report - The Department for…
Committee took evidence from DWP and HMRC on fraud, error, and National Insurance records.
On the basis of a Report by the Comptroller & Auditor General (C&AG), we took evidence from the Department for Work & Pensions (DWP) on its 2022–23 Annual Report & Accounts and the level of fraud and error in the … Read more
Government Response
The government disagrees with an implied recommendation regarding a 5% assumption, stating it cannot be compared to official fraud and error statistics in isolation due to various influencing factors.
HM Treasury
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7 Conclusion Rejected
Fourth Report - The Department for…
Universal Credit overpayments remain high, with significant build-up from pandemic-era claims.
DWP estimates that it overpaid 12.8% (£5.5 billion) of all Universal Credit payments in 2022–23, which is much higher than any other benefit.10 We challenged DWP to explain why the fall in fraud and error promised in the Universal Credit … Read more
Government Response
The government rejects the committee's implied direction to explain the failure of fraud and error reduction, stating its commitment to a cost-effective control environment but highlighting external fraud trends beyond its direct control.
HM Treasury
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8 Conclusion Rejected
Fourth Report - The Department for…
Universal Credit system complexity contributes to incorrect claims despite ongoing simplification efforts.
We asked DWP to what extent the fact that 1 in 3 Universal Credit claims is incorrect is a result of the complexity of the system. DWP told us it is trying to make it easier for claimants to declare … Read more
Government Response
The government rejects the committee's implied criticism regarding system complexity, stating it is committed to reducing fraud and error but acknowledges external trends impacting fraud levels are not directly in its control.
HM Treasury
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9 Conclusion Rejected
Fourth Report - The Department for…
Universal Credit overpayment target of 6.5% now unachievable due to increased baseline fraud and error.
We challenged DWP to explain whether it still expects Universal Credit overpayments to fall to 6.5% as it had previously committed to. DWP explained that 6.5% was the level implied in the business case as a result of the expected … Read more
Government Response
The government rejects the committee's implied direction to explain how it will achieve the 6.5% overpayment target, stating it's committed to reducing fraud and error but external trends impact the level of fraud, which is outside its direct control.
HM Treasury
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13 Recommendation Rejected
Fourth Report - The Department for…
DWP's new fraud and error measures are expected to improve accountability and transparency.
We have previously found that the DWP lacks the ability to demonstrate that its counter-fraud activities are having the intended impact and are cost-effective.22 Alongside its forecast that benefit overpayments will not return to pre-pandemic levels until 2027– 28, DWP … Read more
Government Response
The government rejects the recommendation, stating that while DWP is committed to reducing fraud and error, external trends impacting the level of fraud in the benefit system are not directly within its control.
HM Treasury
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29 Conclusion Rejected
Fourth Report - The Department for…
DWP invests £70 million to expand machine learning for detecting fraudulent benefit claims.
DWP is investing some £70 million to March 2025 in expanding its use of advanced analytics to tackle fraud. This includes using machine learning algorithms to flag potentially fraudulent benefit claims. DWP has already piloted an algorithm to detect fraudulent … Read more
Government Response
The government rejects detailing specific metrics for publication on data analytics' impact, citing the need to avoid compromising fraud detection. However, it reaffirms its commitment to reporting annually on the impact of data analytics on protected groups and vulnerable claimants, with the first assessment in its 2023-24 Annual Report and Accounts.
HM Treasury
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30 Conclusion Rejected
Fourth Report - The Department for…
Concerns persist regarding machine learning's potential unfairness and bias for vulnerable claimants.
We received written evidence from the Child Poverty Action Group and from the Public Law Project expressing concern about the potential unfairness of machine learning, particularly with regard to vulnerable claimants and people with protected characteristics.70 We asked DWP whether … Read more
Government Response
The government rejects detailing specific metrics for publication on data analytics' impact, citing the need to avoid compromising fraud detection. However, it reaffirms its commitment to reporting annually on the impact of data analytics on protected groups and vulnerable claimants, with the first assessment in its 2023-24 Annual Report and Accounts.
HM Treasury
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31 Conclusion Rejected
Fourth Report - The Department for…
Algorithmic bias in DWP systems acknowledged, but evidence of unfair impacts remains inconclusive.
We challenged DWP to explain how it would address the risk that legitimate benefit claims are unfairly delayed or reduced as a result of an algorithms targeting innocent behaviour, such as frequent changes of circumstances. DWP acknowledged that some level … Read more
Government Response
The government rejects detailing specific metrics for publication on data analytics' impact, citing the need to avoid compromising fraud detection. However, it reaffirms its commitment to reporting annually on the impact of data analytics on protected groups and vulnerable claimants, with the first assessment in its 2023-24 Annual Report and Accounts.
HM Treasury
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32 Conclusion Rejected
Fourth Report - The Department for…
DWP cautiously implementing machine learning for fraud detection due to initial accuracy issues.
DWP also told us it did not want to reveal when it planned to go live with machine learning on a large scale to avoid informing potential fraudsters, but added it was 65 Qq 84–90 66 Q 90; DWP ARA … Read more
Government Response
The government rejects detailing specific metrics for publication on data analytics' impact, citing the need to avoid compromising fraud detection. However, it reaffirms its commitment to reporting annually on the impact of data analytics on protected groups and vulnerable claimants, with the first assessment in its 2023-24 Annual Report and Accounts.
HM Treasury
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33 Conclusion Rejected
Fourth Report - The Department for…
DWP committed to annual reporting on data analytics impact on protected groups.
In our November 2022 report on DWP’s 2021–22 accounts we recommended that DWP should report annually to Parliament on its assessment of the impact of data analytics on protected groups and vulnerable claimants.77 DWP told us it thought the right … Read more
Government Response
The government rejects detailing specific metrics for publication on data analytics' impact, citing the need to avoid compromising fraud detection. However, it reaffirms its commitment to reporting annually on the impact of data analytics on protected groups and vulnerable claimants, with the first assessment in its 2023-24 Annual Report and Accounts.
HM Treasury
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Government Response AI assessment · 32 of 11 classified
Accepted 20
Acknowledged 1
Rejected 11
Total 11 recs + 22 conclusions
Correspondence 3 letters
25 Mar 2024 Correspondence from Dame Meg Hillier, Chair of the Committee of Public Accounts, to Peter Schofield CB, Permanent Secretary, Department for Work & Pensions, re Treasury Minute response – DWP Annual Report & Accounts 2022-23, dated 20 March 2024
Parliament page
9 Nov 2023 Correspondence from Peter Schofield CB, Permanent Secretary, Department for Work and Pensions, re DWP Report and Accounts 2022-23 – recommendation 5, dated 24 October 2023
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17 Oct 2023 Correspondence from Richard Hawthorn, Director, Operational Excellence, HM Revenue and Customs, re update on Department for Work and Pensions’ Annual Report and Accounts, dated 28 September 2023
Parliament page