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English(EN) A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

人工智能治理框架整合美国银行业法规以进行欺诈检测

研究人员开发了一个新框架,以帮助美国金融机构应对人工智能驱动的欺诈检测的复杂监管环境。该框架名为RGF-AFFD,整合了四个关键监管机构的要求:OCCSR 11-7、CFPB和FinCEN。它为模型开发、验证和监控提供了一种结构化方法,旨在确保持续合规。 AI

影响 为银行业的人工智能合规提供了蓝图,可能减少人工智能在欺诈检测中应用的监管阻力。

排序理由 这是一篇研究论文,提出了一个特定领域人工智能治理的新框架。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

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人工智能治理框架整合美国银行业法规以进行欺诈检测

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这是一篇研究论文,提出了一个特定领域人工智能治理的新框架。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mohammad Nasir Uddin ·

    美国银行业人工智能驱动的金融欺诈检测的监管治理框架:整合OCC、SR 11-7、CFPB和FinCEN关于模型开发、验证和监控生命周期的合规要求

    arXiv:2605.04076v1 Announce Type: new Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulletin 2011-12, SR 11-7, the CFPB AI circular, and FinCEN BSA/SAR requirements -- wit…