This study uses insurance claims as a proxy for property damage to analyse flood damage in Sweden between the years 1987 and 2013. The number of compensated insurance claims per year has risen rapidly during this period. As much as 70% of the claims are caused by flood damage occurring during the summer months June, July, and August, when intense rain with low predictability is common. To explore the damage trend a time series cross sectional analysis using four different fixed effect models was applied to the data set. Due to data scarcity, the time series had to be limited to 16years and contain a total of 304 damage observations. The potentially explanatory climate related factor extreme rain, defined as >6 mm/15min, and the socioeconomic factors gross regional product (GRP) per capita and housing stock were tested as explanatory factors. The GRP per capita and housing stock were found to be significant in two regression models. The estimated effect of extreme rainfall events exceeded the effects of GRP per capita and housing stock in the models. Extreme rain was robust to model specification and was found to have a highly significant impact on Swedish flood damage.