Speaker
Description
Liability risks are difficult to predict because of their long-tail nature and their susceptibility to legal, societal, economic, and technological changes. Modeling liability catastrophes is especially challenging, as there is limited experience and new risks keep emerging. The industry therefore cannot rely on historic loss data only.
By reflecting structured cause-effect chains, forward-looking models anticipate future business outcomes in light of changing operating environments, without having to wait for claims to emerge. This allows a transfer of insight into the future and to contexts where loss data is sparse.
Since centuries, physicists have developed structural modeling methods for models with potential for re-use in other areas. This has enabled Swiss Re to drive an industry-wide paradigm change to structural modeling.
