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題名 人工智慧於臺灣壽險業之應用探討 - 以C公司為個案研究
An Investigation into the Application of Artificial Intelligence in Taiwan's Life Insurance Industry: A Case Study of C Company作者 吳思穎
Wu, Szu-Ying貢獻者 周冠男<br>梁嘉紋
吳思穎
Wu, Szu-Ying關鍵詞 人工智慧
金融保險
壽險業
數位轉型
數位競爭策略
資料導向轉型
Artificial Intelligence
Financial and Insurance Sectors
Life Insurance Industry
Digital Transformation
Digital Competitive Strategy
Data-Driven Transformation日期 2025 上傳時間 4-Aug-2025 13:03:57 (UTC+8) 摘要 人工智慧（Artificial Intelligence, AI）近年快速崛起於金融保險領域，為壽險業數位轉型注入關鍵動能，AI技術有望大幅提升營運效率與服務品質。C公司率先導入並逐步擴大AI應用於風控、行銷等領域的應用，成效卓著，促使本研究深入探討C公司AI應用。 本研究旨在系統剖析AI在壽險業導入的過程、現況與影響，聚焦於C公司導入AI的動機與歷程、應用項目、導入後效益，並比較C公司與各國同業的AI應用差異，歸納成功要素。C公司已將AI應用於核保理賠、行銷、客服、風控、培訓等，形成從前端銷售至後端理賠的數位化營運。AI導入帶來顯著效益，包括作業效率大幅提升，並提升用戶體驗。 C公司藉AI優化營運與服務創新，取得競爭優勢。相較之下，其他業者雖開始導入AI，但 C公司在資源投入與AI部署上領先，具專責數據團隊、集團級AI平台及自上而下創新文化，使其AI應用更全面、效益更突出。 理論上，本研究以數位競爭策略與資料導向轉型框架解析C公司經驗，發現C公司將資料資產視為核心，具備良好資料基建、分析能力和組織支持文化等條件，成功將AI導入轉化為營運價值。實務上，該案例印證AI可為傳統保險業帶來效率提升與模式創新，建議壽險業者制定長遠AI轉型策略，投入資源推動AI創新，培育AI人才、建立跨部門協作團隊，營造全民學習AI的學習型組織，在鼓勵AI創新應用之文化同時，將AI倫理風險控管納入公司治理，嚴謹驗證與監控模型以確保決策公平透明，並符合資安與隱私規範。此外，應以客戶價值為導向推出AI創新服務，在創新與風控間取得平衡，建立永續競爭優勢。
In recent years, Artificial Intelligence (AI) has rapidly emerged in the financial and insurance sectors, serving as a key driver of digital transformation in the life insurance industry. AI technologies promise to significantly improve operational efficiency and service quality. Company C was an early adopter of AI, gradually expanding its use across risk management, marketing, and other functions with notable success, prompting this study to investigate Company C’s AI initiatives in depth. The study aims to systematically examine the process, current status, and impacts of AI deployment in the life insurance sector, focusing on Company C’s motivations and trajectory of AI implementation, areas of application, and post-adoption benefits. It also includes a comparative analysis of Company C’s AI utilization versus global industry peers to identify key success factors. Employing digital competitive strategy and data-driven transformation frameworks, the analysis finds that Company C integrated AI across multiple operations—including underwriting, claims processing, marketing, customer service, risk control, and training—creating a fully digitized workflow from front-end sales to back-end claims handling. This deployment has yielded significant benefits, notably substantial gains in operational efficiency and enhanced customer experience, which have translated into a competitive advantage. While other insurers have begun to adopt AI, Company C leads in both resource investment and implementation; it benefits from a dedicated data team, an enterprise-level AI platform, and a top-down innovation culture, resulting in more comprehensive integration and more pronounced performance improvements than its peers. Additionally, the study finds that treating data as a strategic asset—supported by robust data infrastructure, strong analytical capabilities, and a supportive organizational culture—was critical for Company C to translate AI adoption into tangible operational value. The case of Company C demonstrates that AI can drive efficiency improvements and business model innovation in the traditional insurance industry. The findings suggest that life insurers should develop long-term AI transformation strategies and invest in AI-driven innovation while cultivating skilled AI talent, establishing cross-departmental teams, and fostering an organization-wide AI learning culture. At the same time, companies must integrate AI ethics and risk management into corporate governance by rigorously validating and monitoring AI models to ensure fair, transparent decision-making and compliance with security and privacy regulations. Finally, insurers should pursue AI-enabled services with a customer-centric approach, balancing innovation with risk control to achieve sustainable competitive advantage.參考文獻 <英文文獻> 1.Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. 2.McCurry, J. (2017, January 5). Japanese company replaces office workers with artificial intelligence. The Guardian. Retrieved from https://www.theguardian.com 3.Pahuja, R. (2023, April 10). Artificial Intelligence at MetLife – Three Use Cases. Emerj Artificial Intelligence Research. Retrieved from https://www.emerj.com 4.Ahmed, N., et al. (2016). Pattern and anomaly detection for fraud mitigation. Springer. Retrieved from https://link.springer.com 5.Allam, Z., & Dhunny, Z. A. (2019). Big data and computing power enabling AI development. Springer. Retrieved from https://link.springer.com 6.Catlin, T., et al. (2018). 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MIS Quarterly, 37(2), 471–482. https://doi.org/10.25300/MISQ/2013/37:2.3 34.Matt, C., Hess, T., & Benlian, A. (2015). Digital transformation strategies. Business & Information Systems Engineering, 57(5), 339–343. https://doi.org/10.1007/s12599-015-0401-5 35.Yeow, A., Soh, C., & Hansen, R. (2018). Aligning with new digital strategy: A dynamic capabilities approach. The Journal of Strategic Information Systems, 27(1), 43–58. https://doi.org/10.1016/j.jsis.2017.09.001 36.Subramaniam, M. (2022). The future of competitive strategy: Unleashing the power of data and digital ecosystems. MIT Press. 37.Subramaniam, M. (2020). Digital ecosystems and their implications for competitive strategy. Journal of Organization Design, 9(1), Article 12. https://doi.org/10.1186/s41469-020-00073-0 38.Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64–88. 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Insurance Business Magazine. https://www.insurancebusinessmag.com/ca/news/technology/ai-roadmap--how-insurance-firms-can-prime-themselves-for-the-future-448034.aspx 43.Dennis Noordhoek, D. (2023, September). Regulation of artificial intelligence in insurance: Balancing consumer protection and innovation. The Geneva Association. https://www.genevaassociation.org 44.Hilton, J. (2023). State insurance regulator on pace of AI rules: “We must go faster”. InsuranceNewsNet. https://insurancenewsnet.com 45.Filabi, A., & Duffy, S. (2021, March). AI, ethics and life insurance: Balancing innovation with access [White paper]. The American College of Financial Services. https://www.theamericancollege.edu 46.Munich Re. (2024, August). New EU Act regulates AI in insurance. Munich Re Automation Solutions. https://www.munichre.com 47.Sapiens. (2024, July 13). The EU AI regulation: A game changer for insurers? https://www.sapiens.com 48.Malcolm, T., Fogle, M., & Zarkadakis, G. (2023, August 3). How AI is changing what work looks like in the insurance industry. WTW Insights. https://www.wtwco.com 49.Swiss Re. (2024, April 3). The power of AI upskilling in insurance: Skills we need to develop. Swiss Re. https://www.swissre.com 50.Kelly, T. (2024, January 9). The benefits and risks for insurers of using generative AI. ANZIIF. https://anziif.com 51.Society of Actuaries, & PwC. (2022). Avoiding unfair bias in insurance applications of AI models [Research report]. Society of Actuaries Research Institute. https://www.soa.org <中文文獻> 1.銀行公會.（2020）。對於金融機構運用人工智慧技術作業規範。金融監督管理委員會。https://www.fsc.gov.tw 2.SAS Taiwan, & 陳愷新.（2021）。AI如何改寫保險業機遇？迎向2030年保險業未來趨勢。SAS Taiwan。https://www.sas.com 3.Fioneer & 鄭宜芬. (2024). 從資料分析到風險評估：AI激起保險業變革. CIO Taiwan. Retrieved from https://cio.com.tw 4.Chen, L. Y. (2024). 論現行國際間對AI應用之政策及規範—以保險業為例 (碩士論文). 政治大學金融學系。Retrieved from https://ah.lib.nccu.edu.tw 5.余宗翰.（2023）。AI在金融產業發展的應用及潛在衝擊。台北外匯市場發展基金會。https://www.tpefx.com.tw 6.勤業眾信風險管理諮詢.（2024）。駕馭多重挑戰 構築保險市場新篇章。《2025年全球保險業展望》新聞稿。Deloitte. Retrieved from https://www.deloitte.com 7.Cathay Financial Holdings. (2024, November 8). 國泰生成式 AI 技術發展框架「GAIA」重磅發布！三大布局實現 AI 即服務戰略. Cathay Financial Holdings [公開網頁]。https://www.cathayholdings.com 8.Cathay Life Insurance. (2025, April 29). 國泰人壽致力數位轉型、客戶體驗創新 獲 Digital CX Award 雙獎肯定. Cathay Life Insurance [公開網頁]。https://www.cathaylife.com.tw 9.Dai, J. Y.（戴瑞瑤）. (2024, May 11). 壽險業國泰人壽 AI、客服力、專注細節三大策略讀懂客戶需求. Yahoo奇摩財經 [公開網頁]。https://tw.stock.yahoo.com 10.IBM（Tim Mucci & Cole Stryker）. (2024, October 10). 什麼是 AI 治理？IBM [公開網頁]。https://www.ibm.com 11.Li, Y.（李昀璇）. (2024, October 18). 金融 GAI 先行者經驗：國泰金控全集團統一 GAI 戰略與技術框架，加速子公司多元發展 AI 創新. iThome [公開網頁]。https://www.ithome.com.tw 12.Prudential plc. (2024, November 19). 保誠於新加坡正式啟動全球人工智能實驗室. Prudential plc [公開網頁]。https://www.prudentialplc.com 13.今周刊編輯團隊. (2025, March 19). 國泰大王子蔡宗翰親自領軍，AI助攻百萬級CUBE App收益增8倍、產險理賠評估240分鐘縮短至15分鐘. 今周刊 [公開網頁]。https://www.businesstoday.com.tw 14.Market Intelligence & Consulting Institute. (2024, April 17). 2024五大行業有兩成比例有意願或相關行動導入生成式AI AI資安威脅、監管發展 驅動GRC防護方案蓬勃發展.資策會產業情報研究所（MIC）[公開網頁] https://mic.iii.org.tw/news.aspx?id=675 15.國泰人壽新聞稿, 國泰人壽勇奪首屆 IIC Asia Awards 2025 數位轉型先鋒獎 台灣金融業唯一獲獎, 2025/03/28cathaylife.com.twcathaylife.com.tw. 16.國泰人壽新聞稿, 國泰人壽致力數位轉型、客戶體驗創新 獲 Digital CX Award 雙獎肯定, 2025/04/29cathaylife.com.twcathaylife.com.tw. 17.李錦奇, 國泰金首公開 AI 框架「GAIA」！國壽 AI 可預測保戶住院機率 產險提升3倍估損力, 品觀點財經, 2024/09/26pinview.com.tw. 18.李昀璇, Fintech周報第220期：國泰人壽首揭新代核心系統核保理賠智能工作臺…, iThome, 2023/11/03ithome.com.tw. 19.專家傳真, AIoT 重塑保險：智慧核保、理賠與詐欺防範新時代, Yahoo奇摩財經, 2023/07/24tw.stock.yahoo.com. 20.專家傳真, 壽險業國泰人壽 AI、客服力、專注細節三大策略讀懂客戶需求, Yahoo奇摩財經, 2023/04/10tw.stock.yahoo.com. 描述 碩士
國立政治大學
經營管理碩士學程(EMBA)
112932113資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112932113 資料類型 thesis dc.contributor.advisor 周冠男<br>梁嘉紋 zh_TW dc.contributor.author (Authors) 吳思穎 zh_TW dc.contributor.author (Authors) Wu, Szu-Ying en_US dc.creator (作者) 吳思穎 zh_TW dc.creator (作者) Wu, Szu-Ying en_US dc.date (日期) 2025 en_US dc.date.accessioned 4-Aug-2025 13:03:57 (UTC+8) - dc.date.available 4-Aug-2025 13:03:57 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2025 13:03:57 (UTC+8) - dc.identifier (Other Identifiers) G0112932113 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158343 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經營管理碩士學程(EMBA) zh_TW dc.description (描述) 112932113 zh_TW dc.description.abstract (摘要) 人工智慧（Artificial Intelligence, AI）近年快速崛起於金融保險領域，為壽險業數位轉型注入關鍵動能，AI技術有望大幅提升營運效率與服務品質。C公司率先導入並逐步擴大AI應用於風控、行銷等領域的應用，成效卓著，促使本研究深入探討C公司AI應用。 本研究旨在系統剖析AI在壽險業導入的過程、現況與影響，聚焦於C公司導入AI的動機與歷程、應用項目、導入後效益，並比較C公司與各國同業的AI應用差異，歸納成功要素。C公司已將AI應用於核保理賠、行銷、客服、風控、培訓等，形成從前端銷售至後端理賠的數位化營運。AI導入帶來顯著效益，包括作業效率大幅提升，並提升用戶體驗。 C公司藉AI優化營運與服務創新，取得競爭優勢。相較之下，其他業者雖開始導入AI，但 C公司在資源投入與AI部署上領先，具專責數據團隊、集團級AI平台及自上而下創新文化，使其AI應用更全面、效益更突出。 理論上，本研究以數位競爭策略與資料導向轉型框架解析C公司經驗，發現C公司將資料資產視為核心，具備良好資料基建、分析能力和組織支持文化等條件，成功將AI導入轉化為營運價值。實務上，該案例印證AI可為傳統保險業帶來效率提升與模式創新，建議壽險業者制定長遠AI轉型策略，投入資源推動AI創新，培育AI人才、建立跨部門協作團隊，營造全民學習AI的學習型組織，在鼓勵AI創新應用之文化同時，將AI倫理風險控管納入公司治理，嚴謹驗證與監控模型以確保決策公平透明，並符合資安與隱私規範。此外，應以客戶價值為導向推出AI創新服務，在創新與風控間取得平衡，建立永續競爭優勢。 zh_TW dc.description.abstract (摘要) In recent years, Artificial Intelligence (AI) has rapidly emerged in the financial and insurance sectors, serving as a key driver of digital transformation in the life insurance industry. AI technologies promise to significantly improve operational efficiency and service quality. Company C was an early adopter of AI, gradually expanding its use across risk management, marketing, and other functions with notable success, prompting this study to investigate Company C’s AI initiatives in depth. The study aims to systematically examine the process, current status, and impacts of AI deployment in the life insurance sector, focusing on Company C’s motivations and trajectory of AI implementation, areas of application, and post-adoption benefits. It also includes a comparative analysis of Company C’s AI utilization versus global industry peers to identify key success factors. Employing digital competitive strategy and data-driven transformation frameworks, the analysis finds that Company C integrated AI across multiple operations—including underwriting, claims processing, marketing, customer service, risk control, and training—creating a fully digitized workflow from front-end sales to back-end claims handling. This deployment has yielded significant benefits, notably substantial gains in operational efficiency and enhanced customer experience, which have translated into a competitive advantage. While other insurers have begun to adopt AI, Company C leads in both resource investment and implementation; it benefits from a dedicated data team, an enterprise-level AI platform, and a top-down innovation culture, resulting in more comprehensive integration and more pronounced performance improvements than its peers. Additionally, the study finds that treating data as a strategic asset—supported by robust data infrastructure, strong analytical capabilities, and a supportive organizational culture—was critical for Company C to translate AI adoption into tangible operational value. The case of Company C demonstrates that AI can drive efficiency improvements and business model innovation in the traditional insurance industry. The findings suggest that life insurers should develop long-term AI transformation strategies and invest in AI-driven innovation while cultivating skilled AI talent, establishing cross-departmental teams, and fostering an organization-wide AI learning culture. At the same time, companies must integrate AI ethics and risk management into corporate governance by rigorously validating and monitoring AI models to ensure fair, transparent decision-making and compliance with security and privacy regulations. Finally, insurers should pursue AI-enabled services with a customer-centric approach, balancing innovation with risk control to achieve sustainable competitive advantage. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究背景 2 第二節 研究目的 2 第三節 研究問題 2 第四節 研究範圍與限制 3 第二章 文獻探討 6 第一節 企業導入資訊科技的理論架構 6 第二節 人工智慧於全球壽險業的應用研究(2019–2024) 18 第三節 人工智慧於全球壽險產業的重要議題(2019–2024) 21 第三章 研究方法 26 第一節 質性研究法 26 第二節 數位競爭策略分析 26 第三節 MOHAN SUBRAMANIAM數位轉型四層級分析 28 第四章 研究分析 31 第一節 個案公司AI應用現況分析 31 第二節 國內外壽險業AI應用比較 35 第三節 C公司AI 應用之數位競爭策略分析 38 第四節 C公司AI 應用之資料導向競爭策略轉型分析 44 第五章 結論 48 參考文獻 51 zh_TW dc.format.extent 1463599 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112932113 en_US dc.subject (關鍵詞) 人工智慧 zh_TW dc.subject (關鍵詞) 金融保險 zh_TW dc.subject (關鍵詞) 壽險業 zh_TW dc.subject (關鍵詞) 數位轉型 zh_TW dc.subject (關鍵詞) 數位競爭策略 zh_TW dc.subject (關鍵詞) 資料導向轉型 zh_TW dc.subject (關鍵詞) Artificial Intelligence en_US dc.subject (關鍵詞) Financial and Insurance Sectors en_US dc.subject (關鍵詞) Life Insurance Industry en_US dc.subject (關鍵詞) Digital Transformation en_US dc.subject (關鍵詞) Digital Competitive Strategy en_US dc.subject (關鍵詞) Data-Driven Transformation en_US dc.title (題名) 人工智慧於臺灣壽險業之應用探討 - 以C公司為個案研究 zh_TW dc.title (題名) An Investigation into the Application of Artificial Intelligence in Taiwan's Life Insurance Industry: A Case Study of C Company en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) <英文文獻> 1.Davis, F. 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