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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19961
標題: | 台灣推行虛擬銀行相關業務之可行性探討 A Study of the Feasibility of Virtual Banking Related Business in Taiwan |
作者: | Yun-An Chen 陳韻安 |
指導教授: | 陳文華 |
關鍵字: | 金融科技,虛擬銀行,行動支付,Peer to Peer網路借貸,機器人投資顧問, Financial Technology,Virtual Banking,Mobile payment,Peer to Peer Lending,Robo-Advisor, |
出版年 : | 2018 |
學位: | 碩士 |
摘要: | 近年來由於金融業整體環境的變化、行動裝置的高普及率及新興科技的創新發展,全球興起金融科技的創新浪潮。不僅各國大型金融機構相繼投入高額資金成立相關部門,相關新創業者亦不斷成立。龐大的商機與全新的市場機會,使金融科技相關投資創下全新紀錄,全球金融業儼然進入金融科技的新時代。
本研究以行動支付、Peer to Peer網路借貸、機器人投資顧問為三大主軸,分析三者崛起原因、核心技術、營運模式及發展現況,藉以了解目前虛擬銀行相關業務發展之概況。 接者以PEST分析模型與商業生態系統理論為基礎,分析各國成功案例具備的發展條件,檢視目前台灣的產業環境是否具備這樣的條件。最後綜合以上資料,探討在目前台灣的外部環境下,業者若欲發展虛擬銀行相關業務,該從何項業務切入,並提出短、中、長期的策略規劃及目標。 研究結果發現,業者應以機器人投資顧問為發展主軸,在短期策略規劃中,新創業者應將目標族群鎖定在20~35歲的年輕族群,並致力於發展自身的電腦演算法,隨時精進自身財務計算模型,以求為平台使用者制定出最佳的投資組合。在中期策略規劃中,應致力於提高自身的市場規模,迅速拓展年輕族群客戶的數量,成為市場中機器人理財顧問的行業領導者,並擊敗市場中其餘提供類似服務的競爭者。在長期策略規劃中,應開始與商業銀行洽談合作事宜,創造雙方雙贏局面。在新創公司面,可藉由合作案幫助自身大幅度提升其市場佔有率,從而進入商業生態系統的「領導」階段;在商業銀行面,則透過合作關係,取得年輕族群相關投資數據,並藉由取得發展成熟的理財機器人顧問,與傳統商業銀行提供之財管理業務做出市場差異化。 In recent years, financial technology (FinTech) has gained much attention from both financial institutions and high-tech startups over the world. Up to date, venture capital funds have invested tens of billion dollars in FinTech startups globally, and the funding is expected to continue on the same pace in the near future. Facing the threat from FinTech startups. banks and other traditional financial institutions have two viable options to choose from, either partnering with FinTech companies to gain competitive advantage or setting up an in-house FinTech unit that can speed up and enhance service delivery to customers. The main objective of this thesis is to investigate the potential FinTech innovations for virtual banks in Taiwan. Based on some key banking statistics and the current FinTech developments in Taiwan, we identified mobile payment, peer to peer lending and robo-advisor as the most promising areas to pursue. For each innovation, we addressed its market needs, core technology, and business models in detailed. We then applied the PEST model and business ecosystem to analyze the feasibility of these innovations. Finally, we concluded with some strategic plans for virtual banks. Our study also showed that robo-advisor could be the most promising business area for Fintech startups. Those startups should target on 20-35 years old young generation, and harness their wealth management capability by developing machine learning models. They then should find some innovative ways to increase their market share, hoping to become the market leader. Finally, they should seek to partner with some traditional financial institutions to gain win-win results for both parties. Fintech startups can rapidly grow their customer base, while commercial banks can access to younger generations customers and acquire robo-advisor capability. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19961 |
DOI: | 10.6342/NTU201801927 |
全文授權: | 未授權 |
顯示於系所單位: | 商學研究所 |
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