Core Insights - The rise of AI deepfake scams poses significant threats to both individual finances and the security of the financial system, with direct economic losses exceeding 1.8 billion yuan as reported by the China Internet Finance Association [1] - Hong Kong's financial sector is exploring the use of AI to combat AI-generated fraud, exemplified by the inclusion of PAObank's anti-fraud strategy platform in the Hong Kong Monetary Authority's GenA.I. sandbox [1] - The disconnect between AI technology and actual business needs has created a "value divide," necessitating a reevaluation of how AI is integrated into financial services [3][4] Group 1: Value Divide and AI Integration - The phenomenon of "value divide" arises from the prevalent "technology-first" approach in AI projects, leading to isolated implementations that do not align with real business scenarios [3][4] - McKinsey's research indicates that while 80% of companies claim to use next-generation AI, 80% of these companies have not seen significant value enhancement from their AI initiatives [3] Group 2: AI as a Business Partner - AI should not be viewed as a standalone solution but rather as a business partner that integrates deeply into financial operations, enhancing risk control, marketing, customer service, and overall operational efficiency [4][6] - The collaboration between PAObank and Financial One Account to create an anti-fraud platform demonstrates a successful application of AI technology in the banking sector, with significant operational metrics such as over 90 million calls and 20,000 intercepted attacks [6] Group 3: Empowering Core Business - The successful realization of AI's value is marked by its ability to address public pain points and enhance enterprise-level applications, as emphasized by Ping An Group's approach to integrating AI into its financial services [5][9] - AI applications in areas such as auto insurance have led to measurable improvements, including a 0.3 percentage point increase in risk control capabilities, translating to billions in value due to the scale of operations [9][10] Group 4: Long-term Value Creation - The focus on practical applications of AI rather than mere technological advancements is crucial for creating sustainable value in the financial sector, as illustrated by Ping An's strategy of leveraging extensive data and operational experience [10]