Abstract
An organizational financial management framework based on data mining utilizes data mining (DM) techniques to uncover latent and valuable insights within unstructured risk data. This empowers informed risk management decision-making. By utilizing business intelligence and data mining techniques to identify, assess, and mitigate various types of supply chain risks, and to develop a comprehensive supply chain risk management (SCRM) framework, it seeks to address the increasing complexity and variety of risks in supply chains. The framework's validity is established via a case study conducted in the heavy machinery sector, thereby making a valuable contribution to the domains of supply chain risk management research and practice. An exhaustive examination of the intelligent financial management system's design is conducted initially, followed by the construction of a support system based on data mining. The second section defines and organizes data mining and data warehouses, as well as the financial management applications of data mining strategy and technology. Further research is being conducted on intelligent data mining and data mining algorithms for technology.
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