Use of insurance loss data in Municipalities : a case study on the possibilities and challenges of implementing insurance loss data in the work on surface water measures
Abstract
Climate change has several consequences for modern societies. One example is increasing and
more severe precipitation which can lead to an increase in surface water damage. In 2013,
Norwegian insurance companies shared insurance loss data to a selection of Norwegian
municipalities as part of a pilot project initiated by Finance Norway. The aim was to strengthen
municipalities ability to prepare for increased uncertainty represented by climate change. This
thesis aims to gain a richer understanding of municipalities climate preventive work
concerning surface water, with the use of insurance loss data. Following research question will
be addressed:
How have two municipalities in Norway implemented insurance loss data in their
municipal work concerning measures on surface water, and what surrounding
circumstances might explain this utilization?
By interviewing respondents from two municipalities that took part in the pilot project, we
have identified 12 findings, arranged into four themes. The first theme consists of four findings
concerning municipal factors that influence how municipalities have to work with insurance
loss data. The second theme involves two findings about the challenge’s municipalities face
in order to fully make use of insurance loss data. These are low data quality and unclear
allocation of responsibility concerning management of surface water. The third theme
concerns where insurance loss data can be implemented. We find that there are few conducted
projects with insurance loss data. Nevertheless, the respondents identify potential projects
where it can be beneficial to include this data. In the fourth theme, we identified four findings
concerning how the challenges with insurance loss data can be faced. These are associated
with a standardization of processes within a municipality and a standard format of reporting
insurance loss data. The insurance loss data must also contain more detailed localization and
dating for when a damage occurred, as well as better information about the reason for a
damage.