Core Insights - The application of AI in the financial industry is transitioning from digital transformation to high-quality development, with AI becoming a core driver of operational logic and service model reconstruction [4][5] - The new generation of AI is characterized by its ability to learn, think critically, and apply knowledge across different domains, marking a significant advancement in its capabilities [5] Group 1: AI's Impact on Financial Operations - AI is expected to drive a dual enhancement of efficiency and intelligence, transforming traditional high-consumption production models into efficient, automated processes [5] - The shift from reactive to proactive decision-making is facilitated by AI, moving from "experience-based" to "data-driven" decision-making [5] Group 2: Changes in Customer Dynamics - Customer trust in AI models is increasing, leading to a broader customer base as the gap in understanding narrows between experts and the general public [6] - The service model is anticipated to evolve, with fewer experts managing a larger number of AI-driven services [6] Group 3: Ecosystem Development - The deep application of AI is creating a "chain reaction" in the financial ecosystem, with companies like Ping An developing integrated smart ecosystems across finance, healthcare, and elder care [6] - Ping An has launched numerous AI applications, including AI medical consultations and intelligent claims processing, enhancing operational efficiency [6] Group 4: Practical Applications of AI - The "Ping An Brain" intelligent engine exemplifies how AI can be integrated into core business areas, supporting decision-making and model training through a robust data platform [6] - Nearly 60,000 intelligent agents have been developed, with 90% created by employees, demonstrating widespread AI application across various sectors [6] Group 5: AI in Customer Service and Risk Management - AI has significantly reduced labor costs in customer service, with 80% of tasks handled by robots, serving over 2 billion customers [7] - In risk management, technologies like voiceprint recognition are being utilized for rapid identity verification and fraud detection, with applications already in over 20 cities [7]