How can the use of technological solutions including machine learning, network analysis and AI be maximised to reduce fraud and error?
Background
DWP delivers services to millions of people and needs evidence on how to improve quality, efficiency, accessibility and trust while treating people with dignity and respect. This group of questions covers service design, customer understanding of DWP’s services, communications and processes, fraud and error, digital transformation, artificial intelligence, automation, staff capability, complaints, serious cases, local delivery, sustainability and experiences across DWP’s digital, telephone, video, written and face-to-face channels for interacting with our customers. DWP is interested in research that can identify what improves outcomes for different groups, including people who need additional support to access or use services. Evidence is also needed on how data, technology and automation can be used robustly and ethically to improve services and outcomes, how our staff can be supported to work effectively with new tools, and how services can learn from experience and adapt to changing demand. External research can help DWP understand what works in comparable public services, other sectors and other countries.
Next steps
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Topics
Related UKRI funded projects
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University of Southampton and The AI Corporation
To transfer and embed an innovative capability, based on advanced machine learning approaches, to automate the time consuming task of fraud risk strategy management in the finance sector....
Funded by: Innovate UK
Lead research organisation: UNIVERSITY OF SOUTHAMPTON
Why might this be relevant?
The project focuses on using advanced machine learning approaches to automate fraud risk strategy management in the finance sector.
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University of Sunderland And Performance Horizon Group Limited
To embed sophisticated intelligent systems methods leading to a commercialisation of a new fraud detection product....
Funded by: Innovate UK
Lead research organisation: UNIVERSITY OF SUNDERLAND
Why might this be relevant?
The project aims to commercialize a new fraud detection product using intelligent systems methods.
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Development of an AI and ML enabled risk assessment platform to reduce fraud in the NHS
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.
Why might this be relevant?
The project is developing an AI and ML enabled risk assessment platform to reduce fraud in the NHS, addressing the specific issue of procurement fraud and errors.