Federated Learning Working Party


  1. Broaden knowledge of Privacy Preserving ML methods and their application in insurance industry
  2. Popularize Federated Learning Machine Learning techniques
  3. Increase awareness of the industry on how the technology might change the way insurance works
  4. Understand potential difficulties and risks in adopting FL technology in insurance and attempt to address those issues
  5. Understand when it is worth to collaborate and when companies should rely on their own data


  1. Małgorzata Śmietanka (Chair)
  2. Claudio Giancaterino
  3. Dylan Liew
  4. Arshad Khan
  5. John Ng
  6. Jonathan Bowden
  7. Steven Perkins
  8. Zack Chan

What is Federated Learning?

Federated Learning is a new Machine Learning Model, allowing local machines to build a model together while holding training data on device. This removes the need to store sensitive training data on a central server.

How does Federated Learning work?