We want to better understand what our wide range of different claimants need and expect, and how and why this is changing, for example, in light of the continued rapid development and use of technology, artificial intelligence and digitalisation.
We want to learn how we can improve how to measure and manage operational performance and productivity across the different parts of the business and identify and exploit opportunities to make delivery more effective, efficient and economical to reduce costs and ensure value for money for the taxpayer. We also want to better understand how to minimise the opportunity for fraud and error to enter our systems, and how to improve the speed and accuracy with which we detect it if or when it does.
Send correspondence and further questions to evidence.strategyteam@dwp.gov.uk.
This question was published as part of the set of ARIs in this document:
Fraud, risk and compliance in the NHS is estimated to cost on average around £5.7 billion every year and takes away money which services could be spending on patient care. In particular, the total loss of procureme...
Funded by: Innovate UK
Lead research organisation: FISCAL TECHNOLOGIES LTD.
The project specifically addresses the use of AI and ML to reduce fraud in the NHS, aligning with the question's focus on minimizing fraud and error using new technologies.
Regardless of sector, size of business or nature of services, revenue leakage (incorrect billing and collection of revenue and expenditure) is a common challenge. Due to a combination of contract complexity often involvi...
Funded by: Innovate UK
Lead research organisation: COGNITIV+ LTD
The project addresses the question fully by using artificial intelligence to prevent revenue leakage and fraud, which is one of the ways to minimize fraud and error. The authors have the necessary expertise in this area.
The Centre for Data Ethics and Innovation (CDEI) has outlined a strategy to establish a robust and advanced AI assurance services ecosystem in the UK. According to CDEI, the main bottlenecks and initiatives aimed at prom...
Funded by: Innovate UK
Lead research organisation: CAMBRIDGE FLAIR LIMITED
The project focuses on AI assurance for financial sectors, which partially aligns with the question's broader scope of minimizing fraud and error using new technologies.