Modeling cyber risks poses some challenges which are unusual, complicate the modeling and make it appear complex. The DAV's Non-Life Insurance Committee has produced a report on the results of modeling cyber risks, in which two modeling approaches are presented, the results are presented, a conclusion is drawn, and next steps are suggested. In addition, the approaches explained are programmed in an R script.
The German Association of Actuaries (Deutsche Aktuarvereinigunge.V., DAV) is the professional representation of all actuaries in Germany. It was founded in 1993 and has more than 5,400 members today. More than 700 members are involved in thirteen committees and in over 60 working groups as a voluntary commitment.
The given repositories have been created by committees and working groups and serve as an aid for our members and interested persons to support them in their work with machine learning methods and data science issues in an actuarial context.
Please note that the repositories provided on GitHub are published by the DAV. The content of linked websites is the sole responsibility of their operators. The DAV is not responsible for the code and data linked to Kaggle.com and referred to in the repositories. These reflect the individual opinion of each user on Kaggle.