Introduction This Data folder accompanies the code supporting the paper "Dynamic Financial Analysis (DFA) of General Insurers under Climate Change". The corresponding code can be downloaded from the following GitHub repository: link. In this paper, we introduce a climate-dependent DFA framework that integrates climate risk into DFA, providing a comprehensive assessment of its long-term impact on the general insurance industry. After downloading the Data folder, unzip it and place it in the same directory as the code downloaded from the GitHub repository. Once this setup is complete, users can run the RMarkdown file without any additional configuration. The main data folders used are outlined below: Economic: Contains historical data on macroeconomic variables (e.g., GDP, interest rates, and inflation rates) and projections of GDP, population, and oil and gas production under each SSP scenario. Equity return: Contains the pseudo All-Ordinaries Shares total returns series and the financial statements of a representative oil and gas producer. Due to licensing restrictions, we are unable to provide the actual Total Returns series of the All-Ordinaries Shares Index and the financial statements of Woodside Energy Limited from FactSet. Users are encouraged to obtain this data directly from FactSet. Hazards loss: Includes the ICA and EM-DAT datasets on catastrophe insurance losses in Australia. Precipitations, FWI, SST and MSLP, Near-surface temperature, and Air temperature: Contain historical observations of precipitation, fire weather index, sea-surface temperature, mean sea-level pressure, near-surface temperature, and air temperature at the grid cell level across Australia (or nearby ocean areas). CMIP6_ensemble_precipitation, CMIP6_ensemble_SST, CMIP6_ensemble_MSLP, CMIP6_ensemble_near_surface_temperature, and CMIP6_ensemble_air_temperature: Contain CMIP6 ensemble projections of the corresponding climate variables. Details of the dataset download sources can be found on the GitHub page linked above.