A reasonable assessment of the risk of extreme precipitation in the future and its changes relative to the past is conducive to the scientific formulation of risk prevention measures. Based on the future daily precipitation simulation data of 24 global climate models of the Shared Socioeconomic Pathways (SSP) 2-4.5 in the sixth phase of the Coupled Model Intercomparison Program (CMIP6), the reanalysis precipitation data of ERA5, and the prediction of population and gross domestic product (GDP), this study evaluated the socioeconomic risk of future global rainstorms at four return periods (5 years, 10 years, 20 years, 50 years) and their changes relative to historical periods. The main conclusions are as follows: 1) Under the future scenarios, the rainstorm intensity in Oceania is the highest and that in Europe is the lowest. With the increase of the return period, the areas where rainstorms occur continue to expand, and the intensity of rainstorms is also projected to increase. 2) At different return periods, the rainstorm risk in Europe and Oceania are the lowest, and that in Asia and Africa are the highest. 3) The regions with the most obvious increase of rainstorm risk in the future are concentrated in the southern and eastern coastal areas of Asia, the central, northern, and southeastern areas of Africa, and the eastern, western, and southern coastal areas of North America. The regions with the most obvious risk reduction are mainly distributed in central and southern Europe, northwestern and eastern Africa, and northern South America. With the increase of the return period, the proportion of the grids with increased risk is projected to increase. 4) The factors that are most related to risk changes at the four return periods differ in the 10 countries with significant changes in risk. The risk change of Russia has the greatest correlation with the change of rainstorm intensity. The risk changes of the United States, Brazil, India, Mexico, the Democratic Republic of the Congo, Argentina, and Australia have the greatest correlation with the change of population. The risk changes of Canada and China have the greatest correlation with the change of GDP. The study can provide a certain theoretical support for disaster prevention and mitigation in areas affected by extreme precipitation.