Select committee: Public Accounts Committee
Conclusion 7
6th Report - DWP Customer Service and Accounts 2023-24
Published 31 Jan 2025
Addressed to HM Treasury
Public Accounts Committee DWP Customer Service and Accounts 2023-24 All items in this report Report on parliament.uk ↗ Inquiry on parliament.uk ↗
Conclusion (the committee's words)
We remain concerned about the potential negative impact on protected groups and vulnerable customers of DWP’s use of machine learning to identify potential fraud. The previous Public Accounts Committee repeatedly raised concerns about the impact of data analytics and machine learning on legitimate benefit claims being delayed or reduced, the number of people affected, and whether this is affecting specific groups of people. Written evidence from the Public Law Project raises a series of risks around DWP’s use of machine learning to tackle fraud. In particular, it notes the risk of machine learning taking on human biases when it is trained on historical data and the potential for wide–scale detrimental impacts on claimants if there is a system–error. DWP has undertaken a fairness impact assessment on its use of data analytics, which it says raised no concerns about the impact on customers. However, it has not published the results because it says it wants to avoid releasing information that could assist fraudsters. recommendation DWP should share with us – in confidence if necessary – the results of its 2024 fairness impact assessment in order to provide reassurance that its use of machine learning is not resulting in claimants being treated unfairly. 6 1 Customer service Introduction
From: Public Accounts Committee, 6th Report - DWP Customer Service and Accounts 2023-24 (HC 354), 31 January 2025
Government response
The government responded to the whole report on 6 May 2025.
Summary written by Accountability Index from the government's response. It is not the government's own words.The government agrees with most of the Committee's recommendations in this response, but disagrees with the recommendation that it set out when it expects to meet its PIP processing target.
- On PIP claim times, the government disagrees with the recommendation, stating the department "has to balance speed against the risk of inaccuracy". It says the Health Transformation Programme will modernise PIP "in the longer-term".
- On ESA calls, the government agrees and says it is recruiting 160 colleagues by March 2025. It states that customer wait times for ESA enquiries "will be improved by September 2025".
- On counter fraud, the government agrees and says that from April 2025 the department "will begin progressive deployment of an additional 3,000 staff", expecting the full number to be in role by 2027-28.
- On machine learning, the government agrees and gives a target implementation date of summer 2025. It says the department "will support an in-confidence session" on the 2024 fairness analysis assessment.