国泰海通｜计算机：行业拐点已至，金融是AI应用落地的绝佳“试验田”

Core Insights - The financial industry's demand for digital transformation aligns closely with the characteristics of large model technology, making it an ideal "testing ground" for AI applications [1] - The release of DeepSeek R1 in 2025 is expected to be a pivotal moment for financial institutions to localize AI deployment, enhancing general model reasoning capabilities and significantly reducing costs [1] - AI applications are rapidly penetrating core business areas and back-office scenarios within various financial institutions, potentially restructuring financial business processes and organizational frameworks [1] Industry Drivers - The combination of internal industry drivers and external policy support has led to a critical point for the implementation of AI in finance [2] - Since the introduction of the first version of the GPT model by OpenAI in 2018, general large model technology has transitioned from "technical validation" to "industry adaptation," indicating that large-scale applications in vertical fields are on the verge of acceleration [2] - Financial institutions are experiencing a significant increase in IT spending, which supports the implementation of AI technologies [2] Technical Pathways - There are two main technical pathways for integrating AI with finance: one involves training general models with financial data, while the other focuses on developing specialized financial models that better address specific industry needs and compliance requirements [2] - The release of the DeepSeek R1 reasoning model marks a significant advancement in the ability of AI to solve complex financial problems [2] - AI agents, particularly multi-agent collaboration, are becoming a key area of future development, with current large models primarily applied in short-thinking financial scenarios such as understanding, Q&A, and information extraction [2]