The actuarial focus has changed significantly over the last couple of years. Computational power is increasing with exponential growth, in addition more and more data is available. This combination puts the actuarial profession into a position where a new understanding has to be developed on today‘s possibilities of actuarial science and its ethical implications. The new role of actuaries within big data and ongoing digitalisation is not yet fully defined. Best practice experience sharing and exchange of ideas is needed. The EAA is delighted to offer all interested actuaries and other experts a forum for knowledge exchange:

On 12 May 2022, the third EAA e-Conference on "Data Science & Data Ethics" will take place live and virtually. The programme will combine keynote speeches with food for thought from well-known experts and selected talks from professionals through a call for papers.

Organised by the EAA – European Actuarial Academy GmbH.

The Data Science & Data Ethics e-Conference is open to all actuaries and other interested experts.

Technical Requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom will be used for this online event). Please also make sure that you are joining the e-Conference with a stable internet connection.

As the leading provider of high-class actuarial education and CPD activities in Europe, the European Actuarial Academy (EAA) will be hosting its third e-Conference on "Data Science & Data Ethics" with the aim

• to present up-to-date solutions to technical problems,
• to share best practices and personal insights
• as well as to offer a forum for actuarial and data science experts.

Please have a look at the full programme for all details.

The best lectures have been selected from a call for papers with many high-class submissions. We are pleased to offer an excellent programme and to publish all available presentation abstracts and lecturer details below:

Keynote Speakers:

• Professor Dr Katrien Antonio, KU Leuven & University of Amsterdam
  Dynamically Updating Motor Insurance Prices with Telematics Collected Driving Behavior Data
  
• Professor Dr Mario Wüthrich, ETH Zürich
  LocalGLMnet: An Interpretable Deep Learning Architecture
  

Lecturers:

• Dr Holger Bartel, RealRate
  Using Explainable AI for Ratings of German Life Insurers
  
• Matthew Byrne, NFU Mutual
  The How and Why of Data Science Risk Management?
  
• Aurélien Couloumy, CCR Group
  Bayesian Neural Network Perspectives for Actuarial Science – Review and Motor Claims Analysis Case Study
  
• Valerie du Preez, Dupro Actuartech
  The How and Why of Data Science Risk Management?
  
• Dr Clemens Frey, Ernst & Young
  The Emergence of BDAI Regulation – Commonalities and Challenges
  
• Akli Kais, CCR Group
  Bayesian Neural Network Perspectives for Actuarial Science – Review and Motor Claims Analysis Case Study
  
• Dr Jordan Ko, SAS Institute
  Operationalizing Responsible AI in the Insurance Industry
  
• Professor Mirko Kraft, University of Applied Science Coburg
  Using Explainable AI for Ratings of German Life Insurers
  
• Gráinne McGuire, Taylor Fry
  Applying Ethical Standards in Practice – Insights from New Zealand
  
• Anthony Nelson, SAS Institute
  Operationalizing Responsible AI in the Insurance Industry
  
• Dr Jürg Schelldorfer, SwissRe
  What are the Basic Similarities and Differences between Insurance Risk Modelling and Standard Machine Learning Techniques? – An Overview
• Petr Václav, RGA
  Bancassurance Data-Driven Solutions
  
• Patricia Wang, Gen Re UK
  

  Predictive Machine Learning for Underwriting Life and Health Insurance