Core Viewpoint - The application of artificial intelligence (AI) in the financial sector is still in its early stages, with potential risks and regulatory issues being widely discussed. Experts emphasize the need for careful evaluation of the benefits and drawbacks associated with AI in finance [1][5]. Group 1: AI Applications in Finance - AI is deeply integrated into various financial processes, primarily focusing on optimizing business operations and customer service. Key areas of application include middle and back-office operations, customer relationship management, and the provision of financial products [2]. - The intelligentization of middle and back-office operations is already widely adopted in financial institutions, covering data collection, processing, information identification, and customer assessment [2]. - AI applications in providing financial products yield dual benefits: internally, they help reduce costs and improve efficiency; externally, they enable financial institutions to offer more personalized and precise products and services to clients [2]. Group 2: Risks Associated with AI - While AI enhances efficiency, it also introduces new systemic risks and channels for risk transmission. The potential impact of these risks is significant, necessitating careful monitoring [5]. - From a micro perspective, individual financial institutions face model stability risks and data governance risks. From a macro perspective, the industry faces concentration risks and decision convergence risks [5]. - Concentration risk arises from the reliance on a few technology providers with strong capabilities, potentially increasing market concentration. Decision convergence risk occurs when institutions use standardized models and data, leading to homogeneity in decision-making across the industry [5]. Group 3: Impact on Monetary Policy - Despite the rapid development of AI, its application in finance remains auxiliary and cannot replace human decision-making. Human expertise is still crucial in key areas such as credit, insurance pricing, and actuarial science [6]. - The influence of AI on monetary policy is not yet significant, as monetary policy adjustments are slow variables that respond to economic cycles rather than immediate changes [7]. - Further observation and research are required to understand the long-term effects of AI on monetary policy, as AI's impact on data collection and processing may not translate into immediate policy changes [7].
“AI+金融”尚处早期 提效同时应关注风险
Zheng Quan Shi Bao·2025-10-23 22:30