About Workshop

The workshop featured sessions on core and advanced machine learning techniques, ranging from introductory programming for neural networks to more complex architectures such as recurrent and graph-based models, as well as modern generative approaches and large language models. In addition to these technical sessions, the programme also included research presentations and plenary talks by distinguished academics and industry leaders.

Emphasis was placed on the broader societal implications of these technologies, with examples such as the role of AI in modelling climate change–related risks and improving resilience in the insurance and finance sectors. A dedicated panel discussion explored the opportunities and challenges of using AI in insurance and finance, including issues of regulation, transparency, and ethics.

The workshop was aimed at academics, practitioners, MSc and PhD students, postdoctoral researchers, and professionals from the insurance and finance industries. Its goal was to bring together experts, early-career researchers and practitioners working in data science, analytics and  machine learning to advance the application of AI in risk assessment and mitigation.