Fraud Risk Identification Based on Machine Learning

In recent years, the situation of external fraud such as cross-border gambling, telecommunication and network fraud, and illegal production has become increasingly serious, showing the characteristics of online, industrialization, and gangs. The national level attaches great importance to anti-fraud governance, and law enforcement and regulatory agencies have increasingly strict anti-fraud management requirements. In this context, Industrial Bank has gradually established and improved the monitoring mechanism for abnormal accounts and suspicious transactions that conform to the characteristics of telecommunications and network fraud activities. The data warehouse application R&D team starts from the business scenario, performs data preprocessing and modeling analysis based on the Intel oneAPI tool, and builds an algorithm identification model for gambling-related and fraudulent accounts to help troubleshoot stock risks.

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