Core Insights - The G20 GPU financial AI ecosystem addresses challenges in traditional risk control systems, such as insufficient computing power and data fragmentation, by integrating hardware, software, and data collaboration for enhanced security in digital finance [1][2] - The ecosystem enables real-time risk identification, achieving risk assessment within 0.3 seconds for each transaction, significantly improving the efficiency and accuracy of fraud detection [1][2] Group 1: Risk Control System Enhancements - The G20 ecosystem allows for real-time sharing of risk characteristics among algorithm vendors, reducing the model update cycle from 1-2 weeks to 24 hours, resulting in a 22% increase in fraud interception rates and an 18% decrease in false positives [2] - The system incorporates 18 detection measures, including transaction behavior analysis and device security checks, to generate risk scores and determine transaction approval [1] Group 2: Data Sharing and Collaboration - The ecosystem has established a cross-institution risk data sharing mechanism with banks and insurance companies, utilizing federated learning to ensure data privacy while optimizing risk control models [2] - A participating bank reported a 15% improvement in credit card default risk prediction accuracy and a 0.8 percentage point reduction in non-performing loan rates after joining the data sharing initiative [2] Group 3: Ecosystem Impact - The G20 financial AI ecosystem has served over 20 financial institutions across various sectors, intercepting suspicious transactions worth over 1.5 billion and handling more than 300,000 risk events, thereby supporting the stable operation of digital finance [3]