Core Insights - China UnionPay has achieved multiple key technological breakthroughs under the "14th Five-Year Plan" national key R&D project focused on financial fraud detection and payment processing market violations, enhancing risk prevention capabilities in the financial payment industry [1][2]. Group 1: Key Technological Breakthroughs - Development of a large-scale graph network construction and retrieval method, creating a financial transaction graph network with 1 billion nodes and 10 billion edges, enabling millisecond-level response queries for large-scale temporal financial graphs [2]. - Introduction of a secure query solution based on salted hashing, designed for asymmetric encryption high-performance anonymous queries, allowing efficient retrieval of large-scale data without exposing user query content or identity [2]. - Innovation in data and knowledge-driven financial fraud detection technology, effectively addressing the challenges of anomaly detection in small and unbalanced sample scenarios, laying the foundation for a new fraud detection model [2]. Group 2: New Financial Payment Risk Prevention Capabilities - Establishment of an intelligent fraud detection platform, creating a large-scale financial payment transaction graph and risk profiles for hundreds of millions of users and merchants, modeling risk in six scenarios including telecom fraud and merchant violations [3]. - Development of a financial fraud data open-sharing platform, utilizing privacy-preserving computing technologies to enable secure sharing of risk information among multiple parties while protecting institutional privacy [3]. - Leadership in constructing standards for heterogeneous platform interconnectivity in privacy computing, achieving interoperability among commercial banks, leading tech companies, and internet institutions [3]. Group 3: Industrial Application of Technological Achievements - Collaboration with nearly 40 user institutions, including financial institutions and telecom operators, to conduct demonstration applications of technological achievements, receiving positive feedback on the effectiveness of these technologies in risk detection and fraud identification [4]. - The demonstration applications span various types of banks and technology companies, confirming the value of these technologies in timely risk detection and enhancing fraud identification accuracy [4]. - Future plans include deepening technological iterations, promoting data integration, model co-construction, and product standardization to support the construction of new financial payment risk prevention infrastructure [4].