Source · Select Committees · Public Accounts Committee
Recommendation 29
29
Rejected
DWP invests £70 million to expand machine learning for detecting fraudulent benefit claims.
Conclusion
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 Universal Credit advances claims.68 The NAO reports that DWP is now actively developing similar tools for the four main risk areas of Universal Credit. We have reported previously that DWP could be more transparent in its use of machine learning in order to support public trust in the fairness of the benefit system.69
Government Response Summary
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.
Government Response
Rejected
HM Government
Rejected
6.1 The government disagrees with the Committee’s recommendation. 6.2 The department is committed to reporting annually to Parliament on its assessment of the impact of data analytics on protected groups and vulnerable claimants with the first assessment in the department’s 2023-24 Annual Report and Accounts. In future years the department will iterate the annual assessments to include impacts on customer service. 6.3 While the department is committed to providing information as set out, it must not compromise its ability to tackle fraud and error by revealing details about its models that could be exploited. On that basis, the department disagrees with the Committee’s recommendation detailing specific metrics for publication.