Fit4AI Compact

The two-day in-person seminar offers actuaries a structured entry into the broad field of artificial intelligence. It teaches the key terms of data science and AI, the essential concepts of machine learning, and current developments in generative AI, along with the principles of trustworthy AI and the requirements of the EU AI Act. The techniques are built up step by step, from decision trees, random forests, and neural networks, through clustering and dimension reduction, to the tokenisation, embeddings, and transformer architectures behind today’s large language models. Beyond the methodological and mathematical background, the seminar concentrates on practical knowledge, suggestions, and assistance for participants‘ own work: a hands-on block introduces the working environment of a data scientist and follows a complete analysis in Python, from preparing the data to training and evaluating a model. Actuarial use cases from various sectors of the insurance industry illustrate and motivate the procedures and concepts throughout. Equal attention goes to the limits of these methods, such as overfitting, bias, and the black-box problem, and to the judgement that their responsible use requires.

Developed by actuaries of the German Association of Actuaries (DAV), the seminar format has already been delivered very successfully in Germany, where it has attracted more than 350 participants to date. Its strong reception underlines both the relevance of the topic for actuarial practice and the practical value of the programme for actuaries seeking to build AI literacy and apply AI methods in their day-to-day work.

Participants will gain a practical introduction to key concepts and methods in artificial intelligence, data science, machine learning, and generative artificial intelligence, with a particular focus on actuarial use cases in insurance.

The practical parts of the seminar are demonstrated live in Jupyter notebooks (Python), covering the basic data science workflow as well as selected machine learning and generative artificial intelligence case studies. Participants receive these notebooks afterwards as supplementary material and can explore and adapt them at their own pace.

Note: According to Article 4 of the European Union’s AI Regulation (AI Act), all persons working with AI must have the necessary level of AI literacy. Participants in the seminar will receive confirmation of their AI literacy for actuarial use cases in insurance.