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
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- Master Thesis 
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.