| 摘要: | 近十年來金融環境革命性的改變，使金融服務逐漸產生對消費者的便利性及服務內容的質變。未來金融科技將影響金融服務的六大核心功能，包括支付(payments)、保險(insurance)、存放款(deposit & lending)、募資(capital raising)、投資管理(investment management)和市場資訊提供(market provisioning)等。其中，「投資管理」、「市場資訊提供」核心功能，均強調財富管理、人工智慧、大數據等關鍵趨勢。理財機器人(Robo-Advisor)將是這波金融科技的高潮，積極引進理財機器人將成為銀行的顯學，促使本研究積極探索消費者對理財機器人接受意願的關鍵成功因素。
本研究採層級分析法(AHP)並採二階段研究，第一階段以詳盡地文獻回顧，找出理財機器人對消費者產生的影響因素，加以分類。邀請10位銀行資深主管參與專家訪談，得出評估之正式問卷，共有四個構面十三項評估準則。第二階段採專家問卷調查法，遴選40位專家協助問卷。
藉由層級分析法(AHP)，得出其影響因子的權重比值，結果發現理財機器人因運用人工智慧而成為消費者青睞的主因，以「人工智慧協助程度」的「機器學習」最為重要(0.2038)、其次為「人工智慧協助程度」的「表達知識」(0.1354)，位居第三為「資訊系統服務程度」的「資訊品質」(0.1031)，顯見提供快速、安全、多元的理財資訊系統平台將更有機會贏得客戶。理財機器人已在國際金融快速發酵，國內銀行應加速研擬理財機器人之可行性。並強化相關的數位平台及資訊安全，以創新思維的團隊來迎戰。
ABSTRACT
Over the past decade the revolution in the financial environment, the gradual emergence of changes in financial service has substantial influence on consumer convenience and service quality content. Future financial technology will affect the six core functions of financial services, including payments, insurance, deposit & lending, capital raising, investment management, and market information (market provisioning). Among them, the core functions of "investment management" and "market information supply" emphasize key trends such as wealth management, artificial intelligence and big data. Robo-Advisor will be the culmination of this wave of financial technology, and the active introduction of financial robots will become a manifestation to the bank, prompting this study to actively explore the key success factors that consumers are willing to accept financial robots.
To discover the characteristics of new tech banking services, this study applied analytical hierarchy process (AHP) and a 2 phase’s analysis. Also this paper has evaluated how this movement could possibly impact to current consumer practices and behavior when Robo-Advisor introduce to domestic market. During the phase one of research, 10 field specialists and senior banking managements have been interviewed to categorize the study into 4 areas and 13 evaluation standards.
In phase two of research, this paper has selected 40 field experts to participate the evaluation. Through AHP this thesis has categorized the sequence and preferences ratio in financial technology (Fin tech) implementation.
Within the feedback observed, the most favorable asset of Fin tech was the mechanism of automotive learning behavior. The degree of assistance in Artificial Intelligence to provide adequacy of knowledge expression has second favorable feature. The rapid, secured, and multifunctional investment banking service platform of information quality in newer investment banking will be as the third most favorable attribute for Fin tech services.
While Fin tech of investment banking has been spread vigorously global wide, prior to this phenomenon swept into Taiwan’s market, how could financial sectors be ready for domestic consumer usage has a crucial challenge within. |
