大数据、机器学习和人工智能在风险评估中的作用:监管视角

S. Bauguess
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引用次数: 27

摘要

几十年来,人工智能(Artificial Intelligence)一直是科幻小说的素材,它的两个字母的首字母缩写“AI”或许更为人所知。但是,人工智能研究背后的技术最近在金融领域得到了应用,这是一场打着“金融科技”旗号的运动。同样的基础技术(机器学习和人工智能)正在推动“监管科技”的衍生领域,使合规和监管相关活动更容易、更快、更高效。与许多金融机构和其他市场参与者一样,委员会最近在利用大数据(又名“SupTech”)力量的分析项目方面取得了快速进展。他们正在推动美国证券交易委员会的监督计划,并允许在许多市场风险评估计划中进行创新。我的评论旨在强调机器学习、大数据和人工智能在市场监管中的许多承诺——但也有局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Big Data, Machine Learning, and AI in Assessing Risks: A Regulatory Perspective
Artificial Intelligence, perhaps better known by its two-letter acronym “AI,” has been the fodder of science fiction writing for decades. But the technology underlying AI research has recently found applications in the financial sector – in a movement that falls under the banner of “Fintech.” And the same underlying technology (machine learning and AI) is fueling the spinoff field of “RegTech,” to make compliance and regulatory-related activities easier, faster, and more efficient. Like many financial institutions and other market participants, the Commission has made recent and rapid advancements with analytic programs that harness the power of big data (a.k.a "SupTech"). They are driving SEC surveillance programs and allowing innovations in many market risk assessment initiatives. My remarks are intended to highlight many of the promises – but also the limitations – of machine learning, big data, and AI in market regulation.
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