Recommendation 5

Departments are not doing enough to be transparent or build public trust on the use of data analytics to tackle fraud. In tackling fraud, government must balance maintaining public trust by being transparent about what it is doing, with not providing so much information that it helps fraudsters. We are concerned that government is not doing enough to assure the public that its use of data analytics is appropriate and does not disadvantage sections of the population. As an example, government bodies are required to disclose publicly any use of algorithms, AI and machine learning in decision making through the Algorithmic Transparency Recording Standard. DSIT told us that, while it believes it has captured most such uses, it knows that not all the expected cases have been recorded. As of February 2026, the Algorithmic Transparency Recording Standard repository held 11 records that mentioned ‘fraud’, and none of the good practice examples of data analytics case studies the NAO reported on were present on the register. recommendation The Department for Science, Innovation and Technology should ensure that all government bodies comply with the Algorithmic Transparency Recording Standard so that the Hub captures all relevant uses of AI and machine learning. It should continuously monitor, update and ensure compliance with guidance around data analytics transparency to ensure that it maximises transparency without assisting fraudsters.