发表机构
Citigroup; Florida State University（摩根大通; 佛罗里达州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对SR 26-2未覆盖生成式AI的治理难题，本文提出兼容该监管规则的GAICF框架，将模型风险管理原则转化为分层控制结构，助力金融机构合规管控生成式AI应用。
AI 中文摘要
SR 26-2的发布标志着美国模型风险管理的重大现代化，它取代了SR 11-7，采用了更具风险导向性、对重要性更敏感的监管框架。但生成式AI与智能体AI未被纳入覆盖范围，给银行及其他金融机构带来了关键治理挑战。尽管生成式AI可能不直接估算信用风险或做出承保决策，其输出可通过监控解读、政策分析或不利操作文书起草等环节对周边控制环境产生重大影响。这类应用场景可能影响受监管金融决策的解释、质疑、记录留存与治理方式。本文提出生成式AI控制框架（GAICF），这是一套适配生成式AI赋能金融工作流的、符合SR 26-2要求的治理框架。该框架将核心模型风险管理原则转化为分层控制结构，适用于运行在正式模型边界之外、但仍嵌入受监管银行业务流程的生成式AI应用。GAICF为金融机构提供了实用路径，可将新兴的生成式AI治理实践与SR 26-2中体现的风险导向型监管要求对齐。
英文摘要
Generative artificial intelligence is moving from general-purpose experimentation toward specialized applications across banking, capital markets, insurance, payments, and wealth management. Its main contribution is not limited to conversational interfaces. Modern generative systems can synthesize large document collections, extract information from unstructured data, generate software and analytical code, create scenario narratives, support research workflows, and coordinate multi-step tasks. These capabilities make generative AI especially relevant to finance, where decisions often depend on combining quantitative data with contracts, policies,filings, news, customer communications, and expert judgment. This paper presents an application-oriented view of generative AI in finance. It organizes potential uses around five capability patterns, including knowledge synthesis, content generation, analytical assistance, interaction, and workflow orchestration, and maps them to major financia functions. Representative applications include investment research, customer service, lending support, fraud investigation, financial reporting, operations automation, software development, and personalized financial guidance. The paper also discusses common technical architectures, such as retrieval-augmented generation, tool-using assistants, multimodal models, and agentic workflows, and identifies practical factors that shape business value. The resulting landscape provides a foundation for researchers and practitioners seeking to understand where generative AI may produce the greatest operational and analytical impact in financial services
