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題名 論理財機器人之監管架構與責任歸屬:比較法之觀點
A Legal Study on the Regulation Framework and Liability Attribution of Robo-Advisors: Comparative Law Perspective作者 李昱廷
Lee, Yu-Ting貢獻者 莊弘鈺
Chuang, Hung-Yu
李昱廷
Lee, Yu-Ting關鍵詞 理財機器人
金融科技
監管架構
資訊揭露
責任歸屬
演算法黑箱
受託義務
全權委託
投資顧問
Robo-advisor
Financial Technology
Regulatory Framework
Information Disclosure
Liability Attribution
Black-box Algorithm
Fiduciary Duty
Investment Advisory日期 2025 上傳時間 1-Jul-2025 14:31:41 (UTC+8) 摘要 隨著金融科技迅速發展,理財機器人(Robo-advisor)以其自動化、低成本與高度可擴展等特性,快速滲透資產管理市場。然而,其運作模式高度依賴演算法進行投資決策與建議,對既有的投資人保護機制與責任歸屬制度造成衝擊。在現行法規適用困難、規範尚付闕如的情況下,相關法律風險與制度空缺日益浮現。有鑑於此,本研究聚焦於中國、美國及台灣三地對理財機器人之監管架構與法律責任歸屬問題,並透過比較法分析,探討新興金融科技與既有法律體系間的衝突 與協調機制,以及各國在資訊揭露、適合度原則、投資建議過程等面向可能引發之法律爭議,以說明各國在監管邏輯、法源依據與實務作法之異同,並提供監管路徑以及法規建議。 在責任歸屬方面,本文進一步討論理財機器人引發損害事件時,應如何釐清開發者、經營業者與投資人之間的權利義務關係,特別聚焦於演算法錯誤、模型偏誤與資訊揭露不實所衍生之侵權與契約責任。研究發現,目前多數國家將最終責任歸屬於平台業者,惟在演算法黑箱效應影響下,責任界限仍具不確定性,投資人救濟權益恐受限制。 本文認為台灣現行以投信投顧法架構下之證券投資顧問規範,對理財機器人產業仍存在適用模糊之處,建議未來監管單位應引入專法或修法方向,針對演算法透明度、資訊揭露義務、投資建議品質審查與責任歸屬進行制度性調整。同時,參考美國對投資顧問忠實義務之實務發展、中國強調資訊報備與演算法審查的趨勢,建構具有前瞻性之理財機器人監理制度,以兼顧金融創新與投資人保護。
With the rapid advancement of financial technology, Robo-advisor has quickly penetrated the asset management market due to their automation, low cost, and high scalability. However, their operational model heavily relies on algorithmic decision-making and the provision of investment advice, posing challenges to existing investor protection mechanisms and legal frameworks for liability attribution. As current regulations face difficulties in application and normative gaps persist, legal risks and institutional deficiencies continue to emerge. This study focuses on the regulatory frameworks and legal responsibilities of Robo-advisors in China, the United States, and Taiwan. Through a comparative legal analysis, the research examines the conflicts and potential harmonization between emerging financial technologies and existing legal systems, especially regarding issues such as information disclosure, the suitability principle, and the investment advice process. It further outlines each country’s regulatory rationale, legal basis, and practical approaches, offering policy pathways and legislative recommendations. Regarding liability attribution, this study further explores how to delineate the rights and obligations among developers, platform operators, and investors in cases where Robo-advisors cause damages. Special attention is given to liability arising from algorithmic errors, model biases, and misrepresentation or omission in information disclosure, including both tortious and contractual dimensions. The research finds that most jurisdictions assign ultimate responsibility to platform operators. However, due to the "black box" nature of algorithms, the boundaries of liability remain uncertain, potentially undermining investors’ access to effective remedies. This paper argues that Taiwan's current legal regime—rooted in the Securities Investment Trust and Consulting Act and its associated investment advisory rules—presents ambiguity when applied to the Robo-advisory industry. It recommends that future regulatory reform introduce either a dedicated law or targeted amendments to address algorithmic transparency, disclosure obligations, the quality of investment advice, and liability allocation. 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金管會(2018),《金融科技發展與創新實驗條例》—鼓勵創新,提升金融競爭力,https://www.ey.gov.tw/Page/5A8A0CB5B41DA11E/aa4a0c9d-14be-4664-ac59-fc74a056d1fd 金管會(2023年10月17日),金管會公布金融業運用人工智慧(AI)之核心原則及政策, https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=202310170002&dtable=News 金管會(2024年10月25日),修正「證券投資顧問事業管理規則」部分條文,金管證投字第1130385193號,https://www.sfb.gov.tw/ch/home.jsp?id=88&parentpath=0,3&mcustomize=lawnews_view.jsp&dataserno=202410250003 金融監督管理委員會(2015年09月24日),金管會金融科技辦公室正式成立並揭牌運作,https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201509240002&toolsflag=Y&dtable=News 金融監督管理委員會(2024),普惠金融專區,https://www.fsc.gov.tw/ch/home.jsp?id=642&parentpath=0,7 金融監督管理委會(2020年12月8日),金管會正式啟動「資本市場藍圖」,https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=202012080001&dtable=News 徐慈薇(2018年2月6日),美股閃崩、機器人理財網站卻當機 投資人崩潰!,中時電子報,https://www.wealth.com.tw/home/articles/14343 栗小雲(2017年6月1日),監管拉緊合規紅線 券商智能投顧遭遇現場檢查,證券時報,https://if.cri.cn/20170601/c6176aab-cdf9-b456-399e-27814f48cbce.html?utm 財團法人中華民國證券暨期貨市場發展基金會網站,http://www.sfi.org.tw 張淩寒(2018年10月4日),如何用演算法解釋權應對“算法暴政”?,民商法律網,https://www.civillaw.com.cn/t/?id=34715 第一銀行e-First智能理財官網,https://efirst.firstbank.com.tw/efirstWeb/dashboard/landingPage 郭靂(2024),我國智慧投顧的問題與挑戰,https://www.sohu.com/a/769774366_121124706 陳怡潔(2024),機器人理財資產首度破百億,17家業者開辦,MoneyDJ理財網,https://www.moneydj.com/kmdj/news/newsviewer.aspx?a=e9c6bfd3-392e-451e-a219-95a4736b1db9 陳慧菱(2018年6月6日),〈國銀拚金融科技〉台新Richart推AI智能投資 上線一個月用戶理財成長1.5倍,鉅亨網,https://news.cnyes.com/news/id/4138588 喬丹(2017年4月13日),証監會嚴查銷售基金涉嫌違規 理財魔方、拿鐵理財被點名,人民網-人民創投,http://capital.people.com.cn/BIG5/n1/2017/0414/c405954-29212021.html 程丹(2024年8月26日),券商債券投顧業務規模幾何?利益衝突是否存在?合規風控到位與否?來看權威解讀,證券時報,https://www.stcn.com/article/detail/1298151.html?utm 廖和明(2023),AI+FinTech 擦出新火花!16 家金融業者已上車,還有哪些應用面向?,未來商務,https://fc.bnext.com.tw/articles/view/3243?utm 福州大學MBA教育中心(2024),智慧投顧演算法透明度對投資者決策的影響研究,怡山講壇,https://mba.fzu.edu.cn/info/1013/1026.htm?utm 線上投資百科全書,Ivestopedia,https://www.investopedia.com/terms/i/Roboadvisor=Eoboadviserasp 謝孟珊(2023),金融科技的浪潮襲來—機器人投顧的法制議題分析,法律白話文網站,https://plainlaw.me/posts/Robo-adviser 魏喬怡(2020年12月14日),業務擬鬆綁 機器人理財拚轉骨,工商時報,https://ctee.com.tw/news/finance/385930.html 魏喬怡(2024),機器人理財衝96億 年增33%,工商時報,https://www.ctee.com.tw/news/20240918700134-439901 證券投資諮詢機構名錄(2024年6月),中國證監會網站,http://www.csrc.gov.cn/pub/zjhpublic/G00306205/201510/t20151028_285725.htm?keywords=%E8%AF%81%E5%88%B8%E6%8A%95%E8%B5%84%E5%92%A8%E8%AF%A2 二、英文文獻 專書 Chopra, S., & White, L. 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Green v. Morningstar Investment Management LLC, No. 17 C 5652 (N.D. Ill. Jan. 16, 2019). King, Inc. v. Google Tech, Inc., No. 02-1457, 2003 WL 21464568 (W.D. Okla. June 24, 2003). State v. Loomis, 881 N.W.2d 749 (Wis. 2016). 新聞資料及網路資源 Abadi, M., & Andersen, D. G. (2016). Learning to protect communications with adversarial neural cryptography. arXiv preprint arXiv:1610.06918. https://arxiv.org/abs/1610.06918 Betterment. Plans for every investor. https://www.betterment.com/pricing Betterment. Understanding automatic allocation adjustment. https://www.betterment.com/help/tag/allocation-management Betterment. What’s inside a Betterment portfolio? https://www.betterment.com/recommendedportfolio-funds/ CBinsights. (2021). Robo-adviser Betterment achieves unicorn status at a valuation of $1.3B. https://www.cbinsights.com/research/betterment-series-f-funding/ Charles Schwab. 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China robo advisory market size & outlook, 2022–2030. https://www.grandviewresearch.com/horizon/outlook/Robo-advisory-market/china Jon Stein. (2016, July 20). The history of Betterment: Changing an industry. https://www.betterment.com/resources/the-history-of-betterment/ Kerber, R., & McGee, S. (2025). Financial industry grappling with AI's gifts and perils, executives say. Reuters. https://www.reuters.com/technology/artificial-intelligence/financial-industry-grappling-with-ais-gifts-perils-executives-say-2024-06-28/?utm SEC. (2011, February 3). SEC charges AXA Rosenberg entities for concealing error in quantitative investment model. https://www.sec.gov/news/press/2011/2011-37.htm SEC. (2011, March 11). General information on the regulation of investment advisers. https://www.sec.gov/divisions/investment/iaregulation/memoia.htm SEC. (2021, August 19). 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Commission guidance regarding client commission practices under Section 28(e) of the Securities Exchange Act of 1934, Exchange Act Release No. 54165. SEC. (2008, March 5). In the matter of Fidelity Management Research Company and FMR Co., Inc., Respondent, Advisers Act Release No. 2713. http://www.brightlinesolutions.com/files/Plaze/Release%20IA-2713%20Fidelity%20FMR.pdf SEC. (2011, January). Study on investment advisers and broker-dealers as required by Section 913 of the Dodd–Frank Wall Street Reform and Consumer Protection Act. SEC. (2015, September 17). Timbervest, LLC, et al., Advisers Act Release No. 4197. https://www.sec.gov/litigation/opinions/2015/ia-4197.pdf SEC. (2017, February 23). Investor bulletin: Robo-advisers. https://www.investor.gov/introduction-investing/general-resources/news-alerts/alerts-bulletins/investor-bulletins-45 SEC. (2017, February). Division of Investment Management, Guidance update: Robo-advisors, No. 2017-02. https://www.sec.gov/investment/im-guidance-2017-02.pdf SEC. (2019, June 5). Commission interpretation regarding standard of conduct for investment advisers, Advisers Act Release No. IA-5248. https://www.sec.gov/rules/interp/2019/ia-5248.pdf SEC. (2021). Investment Advisers Act of 1940: Regulatory guidance. SEC. Fintech Forum – The evolving financial marketplace. https://www.sec.gov/spotlight/fintech/transcript-111416.pdf Wealthfront. (2019, January 18). Form ADV. https://www.adviserinfo.sec.gov/IAPD/content/ViewForm/crd_iapd_stream_pdf.aspx?ORG_PK=148456 描述 碩士
國立政治大學
科技管理與智慧財產研究所
111364213資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111364213 資料類型 thesis dc.contributor.advisor 莊弘鈺 zh_TW dc.contributor.advisor Chuang, Hung-Yu en_US dc.contributor.author (Authors) 李昱廷 zh_TW dc.contributor.author (Authors) Lee, Yu-Ting en_US dc.creator (作者) 李昱廷 zh_TW dc.creator (作者) Lee, Yu-Ting en_US dc.date (日期) 2025 en_US dc.date.accessioned 1-Jul-2025 14:31:41 (UTC+8) - dc.date.available 1-Jul-2025 14:31:41 (UTC+8) - dc.date.issued (上傳時間) 1-Jul-2025 14:31:41 (UTC+8) - dc.identifier (Other Identifiers) G0111364213 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/157718 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 科技管理與智慧財產研究所 zh_TW dc.description (描述) 111364213 zh_TW dc.description.abstract (摘要) 隨著金融科技迅速發展,理財機器人(Robo-advisor)以其自動化、低成本與高度可擴展等特性,快速滲透資產管理市場。然而,其運作模式高度依賴演算法進行投資決策與建議,對既有的投資人保護機制與責任歸屬制度造成衝擊。在現行法規適用困難、規範尚付闕如的情況下,相關法律風險與制度空缺日益浮現。有鑑於此,本研究聚焦於中國、美國及台灣三地對理財機器人之監管架構與法律責任歸屬問題,並透過比較法分析,探討新興金融科技與既有法律體系間的衝突 與協調機制,以及各國在資訊揭露、適合度原則、投資建議過程等面向可能引發之法律爭議,以說明各國在監管邏輯、法源依據與實務作法之異同,並提供監管路徑以及法規建議。 在責任歸屬方面,本文進一步討論理財機器人引發損害事件時,應如何釐清開發者、經營業者與投資人之間的權利義務關係,特別聚焦於演算法錯誤、模型偏誤與資訊揭露不實所衍生之侵權與契約責任。研究發現,目前多數國家將最終責任歸屬於平台業者,惟在演算法黑箱效應影響下,責任界限仍具不確定性,投資人救濟權益恐受限制。 本文認為台灣現行以投信投顧法架構下之證券投資顧問規範,對理財機器人產業仍存在適用模糊之處,建議未來監管單位應引入專法或修法方向,針對演算法透明度、資訊揭露義務、投資建議品質審查與責任歸屬進行制度性調整。同時,參考美國對投資顧問忠實義務之實務發展、中國強調資訊報備與演算法審查的趨勢,建構具有前瞻性之理財機器人監理制度,以兼顧金融創新與投資人保護。 zh_TW dc.description.abstract (摘要) With the rapid advancement of financial technology, Robo-advisor has quickly penetrated the asset management market due to their automation, low cost, and high scalability. However, their operational model heavily relies on algorithmic decision-making and the provision of investment advice, posing challenges to existing investor protection mechanisms and legal frameworks for liability attribution. As current regulations face difficulties in application and normative gaps persist, legal risks and institutional deficiencies continue to emerge. This study focuses on the regulatory frameworks and legal responsibilities of Robo-advisors in China, the United States, and Taiwan. Through a comparative legal analysis, the research examines the conflicts and potential harmonization between emerging financial technologies and existing legal systems, especially regarding issues such as information disclosure, the suitability principle, and the investment advice process. It further outlines each country’s regulatory rationale, legal basis, and practical approaches, offering policy pathways and legislative recommendations. Regarding liability attribution, this study further explores how to delineate the rights and obligations among developers, platform operators, and investors in cases where Robo-advisors cause damages. Special attention is given to liability arising from algorithmic errors, model biases, and misrepresentation or omission in information disclosure, including both tortious and contractual dimensions. The research finds that most jurisdictions assign ultimate responsibility to platform operators. However, due to the "black box" nature of algorithms, the boundaries of liability remain uncertain, potentially undermining investors’ access to effective remedies. This paper argues that Taiwan's current legal regime—rooted in the Securities Investment Trust and Consulting Act and its associated investment advisory rules—presents ambiguity when applied to the Robo-advisory industry. It recommends that future regulatory reform introduce either a dedicated law or targeted amendments to address algorithmic transparency, disclosure obligations, the quality of investment advice, and liability allocation. Drawing upon the United States’ emphasis on fiduciary duties and China’s focus on algorithmic review and information reporting, the study proposes the development of a forward-looking regulatory framework for Robo-advisors that balances financial innovation with investor protection. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究動機與目的 1 第二節 研究方法與架構 3 第一項 研究方法 3 第二項 研究範圍與限制 3 第三項 研究問題 4 第四項 研究架構 5 第二章 理財機器人概述 6 第一節 理財機器人之涵義 6 第一項 理財機器人定義 6 第二項 理財機器人之起源 9 第二節 理財機器人之類型與運用場域 10 第一項 理財機器人服務分類 10 第二項 理財機器人之發展現況 15 第三節 理財機器人之優勢與風險 18 第一項 理財機器人與傳統投資顧問服務之差別 18 第二項 理財機器人與傳統投資顧問之比較分析 22 第四節 小結 26 第三章 美國理財機器人發展與現有法規規範 27 第一節 理財機器人之市場發展與法律適用 27 第一項 美國理財機器人歷史演變與崛起 27 第二項 市場競爭格局與傳統金融機構的參與 27 第二節 美國對理財機器人監管體系之發展與規範 34 第一項 美國證券法制架構與理財機器人監管基礎 34 第二項 美國理財機器人監管架構 35 第三項 理財機器人之投資者保護機制 48 第四項 小結 50 第三節 美國對理財機器人之司法實踐 53 第一項 SEC訴AXA Rosenberg集團案 53 第二項 Green訴晨星公司和保誠公司案 57 第四節 小結 61 第四章 中國理財機器人發展與現有法規規範 63 第一節 理財機器人之監管架構與市場發展 63 第一項 中國理財機器人市場概況 63 第二項 中國理財機器人監管體系之法律架構與發展 67 第二節 中國理財機器人之信義義務主體與責任分擔 70 第一項 傳統投資顧問模式下的主體義務與責任 70 第二項 中國理財機器人模式中之法律關係 75 第三項 中國理財機器人信義義務之法律規範 76 第三節 中國理財機器人之法制衝擊以及困境 78 第一項 演算法黑箱對投資者保護的法制困境 78 第二項 全權委託限制對理財機器人業務模式之成長困境 82 第三項 《資管新規》框架下方案之缺陷 85 第四節 小結 87 第五章 台灣理財機器人發展與現有法規規範 89 第一節 台灣主要理財機器人之業者 89 第二節 我國對理財機器人監管體系之發展 92 第一項 金融科技產業的興起與監管政策 92 第二項 理財機器人監管政策之變遷 93 第三項 監管政策之創新調整 94 第四項 監管政策影響與挑戰 94 第三節 理財機器人之適用法律 95 第一項 台灣理財機器人之相關規範 95 第二項 台灣傳統投資顧問之相關規範 98 第四節 小結 109 第六章 理財機器人之法規比較及台灣理財機器人監管方向之建議 110 第一節 綜合整理與比較 110 第二節 我國對理財機器人之法規調適與挑戰 113 第一項 理財機器人之受託義務履行 115 第二項 演算法黑箱所造成之投資者保護困境 129 第三項 全權委託之規範限縮理財機器人之發展 134 第三節 監管路徑與方案建議 138 第一項 理財機器人受託義務之履行與責任歸屬之分配 138 第二項 理財機器人演算法規制的目的導向與層次性透明機制 146 第三項 全權委託型理財機器人規制的可選路徑 153 第四節 小結 158 第七章 結論與建議 160 參考文獻 165 zh_TW dc.format.extent 4611279 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111364213 en_US dc.subject (關鍵詞) 理財機器人 zh_TW dc.subject (關鍵詞) 金融科技 zh_TW dc.subject (關鍵詞) 監管架構 zh_TW dc.subject (關鍵詞) 資訊揭露 zh_TW dc.subject (關鍵詞) 責任歸屬 zh_TW dc.subject (關鍵詞) 演算法黑箱 zh_TW dc.subject (關鍵詞) 受託義務 zh_TW dc.subject (關鍵詞) 全權委託 zh_TW dc.subject (關鍵詞) 投資顧問 zh_TW dc.subject (關鍵詞) Robo-advisor en_US dc.subject (關鍵詞) Financial Technology en_US dc.subject (關鍵詞) Regulatory Framework en_US dc.subject (關鍵詞) Information Disclosure en_US dc.subject (關鍵詞) Liability Attribution en_US dc.subject (關鍵詞) Black-box Algorithm en_US dc.subject (關鍵詞) Fiduciary Duty en_US dc.subject (關鍵詞) Investment Advisory en_US dc.title (題名) 論理財機器人之監管架構與責任歸屬:比較法之觀點 zh_TW dc.title (題名) A Legal Study on the Regulation Framework and Liability Attribution of Robo-Advisors: Comparative Law Perspective en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文文獻 專書 王文宇(2016),金融法,元照,9版。 王文宇主編(2007),金融法,台北:元照出版。 王澤鑑(1999),債法原理第一冊,增訂版,台北: 三民。 沈中華(2015),金融市場全球的觀點,台北:新陸。 谷湘儀、臧正運編審(2017年5月),金融科技發展與法律,五南。 周淳(2021),商事领域受信制度原理研究,北京大學出版社。 郭土木(2019),金融管理法規(上),台北:三民。 鄭燦堂(2022),風險管理: 理論與實務,五南圖書出版股份有限公司。 期刊論文 丁曉東(2022),基於信任的自動化決策院演算法解釋權的原理反思與制度重構,中國法學,(1),頁99-118。 于文菊(2017),我國智慧投顧的發展現狀及其法律監管,海南金融,6 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