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| 題名: | 替代性信用評分模型之歧視性風險與法規因應
Discriminatory Risks and Regulatory Responses in AI-Based Alternative Credit Scoring |
| 作者: | 陳沐恩
Chen, Mu-En |
| 貢獻者: | 莊弘鈺
Chuang, Hung-Yu
陳沐恩
Chen, Mu-En |
| 關鍵詞: | 替代性信用評分模型
人工智慧
信用評分
信貸歧視
金融消費者保護
人工智慧治理
Alternative Credit Scoring Model
Artificial Intelligence
Credit Scoring
Credit Discrimination
Financial Consumer Protection
Artificial Intelligence Governance |
| 日期: | 2025 |
| 上傳時間: | 2025-09-01 16:05:18 (UTC+8) |
| 摘要: | 近年來人工智慧和機器學習迅速發展，其應用已遍及各產業領域。於金融領域中，替代性信用評分模型即為其重要應用場景。藉由採用替代數據與新興技術進行信用評估，替代性信用評分模型得以促進普惠金融的實現，然同時也帶來偏誤與歧視之隱憂。美國和歐盟近來已對此陸續做出法規或監管政策上的回應，我國則因整體產業起步較晚，相關法規因應尚付闕如。
有鑑於此，本文擬從消費者保護、人工智慧治理及資料保護等面向，梳理美國與歐盟相關法規、近期主管機關解釋及實務判決，進而分析其監理重點與監管趨勢，期能透過比較法研究汲取可供我國借鏡之處。研究結果發現，儘管美歐在規制手段上有所差異，惟於監管目標上仍有諸多相似之處，兩地皆展現出擴大監管範圍、強化資訊揭露之趨勢，藉以增進數位金融時代下的消費者保護。
我國尚欠缺針對信貸歧視之有效法規與人工智慧監管法案，目前反歧視法與人工智慧基本法皆未通過。本文認為，我國反歧視法草案應將適用範圍擴及信貸交易，俾使潛在受歧視者得獲適當救濟。另參酌美歐監管趨勢，宜先於《金融業運用人工智慧（AI）指引》新增資料限制與透明度要求。由於該指引係屬行政指導，且規範對象僅限傳統金融機構，本文認為中長程而言應提升相關規範位階以強化其拘束力，並將新興金融科技業者納入規範對象，以充分保障我國消費者於借貸市場之權益。
In recent years, the rapid advancement of artificial intelligence (AI) and machine learning has led to wide-ranging applications across various industries. In the financial sector, one significant application is AI-based alternative credit scoring models. By leveraging alternative data and emerging technologies in creditworthiness assessments, these models have the potential to promote financial inclusion. However, they also raise concerns about bias and discrimination. The U.S. and the EU have developed policy and regulatory responses to address these issues, whereas Taiwan still lacks corresponding legal frameworks.
Therefore, this thesis examines relevant laws, regulations, agency responses, and judicial decisions in the U.S. and EU from the perspectives of consumer protection, AI governance, and data protection. Through comparative legal analysis, this research identifies key regulatory priorities and emerging trends in both jurisdictions, aiming to provide concrete guidance for the enhancement of Taiwan’s legal framework. The research findings suggest that while the U.S. and EU adopt divergent regulatory approaches, they share similarities in their goals and effects. Both jurisdictions are extending the regulatory scope and strengthening disclosure requirements to enhance consumer protection in the digital finance era.
Taiwan’s current legal framework lacks effective regulatory tools to address credit discrimination and govern the use of AI. The proposed Anti-Discrimination Act and AI Basic Act have not yet been passed. This paper argues that the scope of the draft Anti-Discrimination Act should be expanded to cover credit transactions, thereby ensuring appropriate remedies for individuals potentially subject to discriminatory lending practices. Drawing on regulatory trends in the U.S. and EU, this paper also recommends amending the “Guidelines for Artificial Intelligence (AI) Applications in the Financial Industry” to incorporate transparency requirements and data limitations. Given that the current Guidelines are administrative in nature, non-binding, and apply only to traditional financial institutions, this paper advocates that, in the medium to long term, their legal hierarchy should be elevated and their scope expanded to encompass emerging fintech companies, thereby ensuring robust consumer protection in Taiwan’s lending market. |
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其他
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| 描述: | 碩士
國立政治大學
科技管理與智慧財產研究所
109364215 |
| 資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0109364215 |
| 資料類型: | thesis |
| 顯示於類別: | [科技管理與智慧財產研究所] 學位論文
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