Government Actuary's Department
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GAD's wide-ranging skills

GAD's wide ranging work including the use of data science and modelling, was discussed at a recent event attended by analysts from local authorities.

The wide remit of work undertaken by the Government Actuary’s Department (GAD) and the changing roles of actuaries were discussed at a recent local government webinar.

Actuaries from GAD joined members of the Local Government Advanced and Predictive Analytics Network (APAN) at its 10th webinar. This virtual event was attended by analysts from local authorities across England and Wales.

Current challenges

GAD presenters explored examples of how we use data science, insurance mechanisms and quality assurance processes as part of projects. We also considered how this work could be relevant to the current challenges being faced by local government.

The session included case studies on:

  • COVID-19 – covering our work with the Department of Health and Social Care, to identify and prioritise vulnerable people during the pandemic
  • data science – we shared information about models and predictive data analytics when it comes to modelling potential drought outcomes in sub-Saharan Africa
  • quality assurance – we shared tips and examples of good quality assurance in projects, using projects relevant to local government
  • insurance – where protection is important and how we help departments address deficiencies in insurance cover
  • contingent liabilities – we shared expertise on the complex area of contingent liability in projects, including commercial insurance and indemnities

Three people sat in a meeting. All three look to be discussing an item on the a notepad, which the person in the centre is holding. The image is overlaid by several icons which include small graphs, a pie chart and the words 'data analysis'.

Sharing expertise

GAD actuary Jon Day recently said:

“As an advocate for the use of data science and predictive analytics across the public sector, we were able to share our case studies with the APAN members.

“We help the network consider how predictive analytics, model quality assurance and insurance principles could help provide solutions to the challenges facing local authorities.”


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