Open Loss Data, Databases and data-driven Risk Transfer: Connecting insurance, academia and governments
Co-organized as NH9.17
Convener: James Daniell | Co-conveners: Jeroen Aerts, John K. Hillier, Gero Michel, Harriette Stone
| Thu, 11 Apr, 10:45–12:30
Room N1
| Attendance Thu, 11 Apr, 14:00–15:45
Hall X3

Over the past decades, many initiatives have been produced to archive the losses and datasets associated with natural perils events (EM-DAT, MunichRe NATCATservice, SwissRe Sigma, CATDAT, Dartmouth Flood Observatory etc.). On a European scale, much research has also been undertaken on a Europe-wide, country and subcountry level either using Desinventar or through other academic and insurer data archiving. However, these loss databases provide varying levels of parameters, data completeness, quality checks, spatial integration, and spatiotemporal limits. In addition, the types of data collection and definitions of loss often differ greatly between databases.

With over 3000 Open Data Initiatives around Europe ( and the World, the amount of data freely available is increasing, but censoring and data checks are required in order to ensure that the quality is reasonable. This similarly goes for online media archives and loss reporting. Even though some initial attempts have been made to connect different databases and stimulate consistency and open access (e.g. IRDR-DATA), this is a topic that needs to be explored further.

This session aims to advance efforts on loss data collection and provide a future inventory of socioeconomic loss databases for loss and risk analysis as well as to create a community linking academia, government and insurance.

Abstracts are welcomed in the following fields:-
- Socioeconomic loss databases for natural perils
- Infrastructure and sectoral loss archiving
- Online media initiatives for collecting loss data (e.g. twitter)
- Post-disaster loss analysis
- Online analysis of loss data or loss reporting
- Parametric risk transfer products
- GIS integration of past natural hazards event data
- Open data efforts for loss modelling
- Insurance loss data and loss archives
- Government post-disaster loss analysis and loss databases
- Other relevant loss-related research