As global climate change deepens, extreme weather events, including both the frequency and severity of extreme precipitations are increasing. Currently, as a flood- prone country, Canada faces significant potential losses from flood risk. Over the past decade, the frequency and severity of natural disasters have increased, leading to a sharp rise in climate-related losses. In this thesis, we analyze the correlation between precipitation and different lines of business (personal property, commercial property, auto property) in the insurance industry. Additionally, time series regression models and ARIMA models are applied to analyze and predict the trends of the total claims count and the total incurred claims.