The complex configuration combinations of nuclear power plants pose challenges (e.g. equipment failure, data processing delay) for risk management, and existing manual recording and monitoring technologies are no longer sufficient to meet the informatization management requirements of nuclear power projects. The paper proposes a real-time risk data processing method based on the resolving method and the cut-set method, which uses algorithms to process large amounts of data to identify potential risks. However, the large volume of data and complex computational results affect the timeliness of risk alerts, so high computational efficiency is required. The paper constructed a risk quantification assessment model, established a standardized operational process template, and compared the resolving method and the cut-set method. Furthermore, a combined mode of the resolving method and cut-set method was designed: first, the resolving method is used to calculate the cut-set results under high-precision truncation conditions, then the status changes of the equipment are assessed, and an appropriate algorithm is selected. After improvements, the CDF calculation error was controlled within 0.85%, and computational efficiency was improved by 7 times, providing precise technical support for nuclear power plant risk management and significantly enhancing the informatization management level of nuclear power projects.