Nan Fang Du Shi Bao·2025-10-22 10:02Core 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, as evidenced by the inclusion of PAObank's anti-fraud strategy platform in the Hong Kong Monetary Authority's GenA.I. sandbox [1][3] - The disconnect between AI technology and actual business needs has created a "value gap," necessitating a reevaluation of how AI is integrated into financial services [3][4] Group 1: Value Disconnection - The narrative surrounding AI is expanding globally, with many financial institutions adopting "AI First" strategies, yet a significant number of these initiatives fail to deliver tangible value [3] - McKinsey's research indicates that while 80% of companies are utilizing next-generation AI, 80% of these companies report no significant value enhancement from their AI projects [3][4] - The phenomenon of "crossing the Darwinian sea" highlights the challenges faced by tech innovation firms in transitioning from R&D to successful commercialization, particularly in the AI sector [4] Group 2: Addressing Public Pain Points - The successful realization of AI's value in the financial sector is marked by its ability to address public pain points and generate social value [4][5] - PAObank's collaboration with Financial One Account to create an anti-fraud platform exemplifies the application of AI technology in banking, with over 90 million calls made to the technology and over 20,000 black market attacks intercepted [5] - The integration of AI into business processes is emphasized, with AI being viewed as a business partner rather than a standalone tool [5][6] Group 3: Empowering Core Business - The transformation of AI into a valuable asset for core business operations is crucial, with a focus on ensuring that every AI project has a clear value proposition [7] - In the auto insurance sector, AI-driven pricing models have improved risk control capabilities by 0.3 percentage points, translating to significant financial benefits given the scale of claims [7][8] - AI applications have led to substantial cost optimizations across various functions, including marketing, service, and risk management, with notable savings reported [8]