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Author: 雷柏倫
Christoph Lorenz Reimann
Thesis Title: Robo Advice: Towards Hybrid Human-Machine Enhancement
Robo Advice: Towards Hybrid Human-Machine Enhancement
Advisor: 劉代洋
Liu Day-Yang
Committee: 陳俊男
Chun-Nan Chen
邱敬仁
Jing-Ren Chiu
Degree: 碩士
Master
Department: 管理學院 - 財務金融研究所
Graduate Institute of Finance
Thesis Publication Year: 2019
Graduation Academic Year: 107
Language: 英文
Pages: 49
Keywords (in Chinese): Robo AdviceArtificial IntelligenceFintech
Keywords (in other languages): Robo Advice, Artificial Intelligence, Fintech
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  • Fintechs are advanced IT systems, often based on mobile devices, that have been revolutionizing the processes in financial industry for about a decade. They make full use of latest technology, such as artificial intelligence, in particular machine learning. Many innovations stem from high tech companies, particularly start-ups. Some of them are trying to set up mass business of their own, whereas others are suppliers or even affiliates of traditional companies in the financial industry, e. g. credit banks. Fintech has many aspects, among them payment systems. An important one is robo advice, i. e. automated online platforms that provide private investors with financial advice and sometimes also portfolio allocation.
    By means of a literature survey, complemented by an interview with a bank professional, the development and the actual state of robo advice are presented and trends for future development are examined. The major findings of this study are the following.
    Robo advisors use web or mobile interfaces, sometimes complemented by human advice on request. They use online questionnaires to identify investor profiles. Asset allocation relies essentially on passive investment methods. The providers fall into two groups: large new players such as Betterment or Wealthfront specializing in online investment service; traditional players such as large or medium-sized banks that have entered this business, often warily.
    The benefits of robo-advice are a low client entry level in terms of both administrative work and financial means, thus making them an attractive instrument for the financial inclusion of the mass affluent; furthermore, it provides profitable asset management at low cost. An actual shortcoming is the narrowness in terms of both investment options and investor profiles. As any online service, robo advice is exposed to cyber criminality.
    The future of robo advice lies in hybrid solutions, which can be implemented in two ways. Either investors use online self-service interfaces but are guided at critical moments by human advisers. Or advisers themselves use sophisticated, AI-based tools that enhance their capabilities – similar to image diagnostic tools which do not replace radiologists but strengthen their power of cognition. Thus, the oft-quoted fear that robos displace humans is not substantiated. Another possible line of future development lies in gamified platforms for goal-based investment. By means of a serious simulation game, investors could model various scenarios comprising their entire lifetime, taking into account their goals at different stages of career, their decisions as well as stochastic influences. At any rate, the roles of both advisers and clients will be redefined towards enhanced, comprehensive client servicing.


    Fintechs are advanced IT systems, often based on mobile devices, that have been revolutionizing the processes in financial industry for about a decade. They make full use of latest technology, such as artificial intelligence, in particular machine learning. Many innovations stem from high tech companies, particularly start-ups. Some of them are trying to set up mass business of their own, whereas others are suppliers or even affiliates of traditional companies in the financial industry, e. g. credit banks. Fintech has many aspects, among them payment systems. An important one is robo advice, i. e. automated online platforms that provide private investors with financial advice and sometimes also portfolio allocation.
    By means of a literature survey, complemented by an interview with a bank professional, the development and the actual state of robo advice are presented and trends for future development are examined. The major findings of this study are the following.
    Robo advisors use web or mobile interfaces, sometimes complemented by human advice on request. They use online questionnaires to identify investor profiles. Asset allocation relies essentially on passive investment methods. The providers fall into two groups: large new players such as Betterment or Wealthfront specializing in online investment service; traditional players such as large or medium-sized banks that have entered this business, often warily.
    The benefits of robo-advice are a low client entry level in terms of both administrative work and financial means, thus making them an attractive instrument for the financial inclusion of the mass affluent; furthermore, it provides profitable asset management at low cost. An actual shortcoming is the narrowness in terms of both investment options and investor profiles. As any online service, robo advice is exposed to cyber criminality.
    The future of robo advice lies in hybrid solutions, which can be implemented in two ways. Either investors use online self-service interfaces but are guided at critical moments by human advisers. Or advisers themselves use sophisticated, AI-based tools that enhance their capabilities – similar to image diagnostic tools which do not replace radiologists but strengthen their power of cognition. Thus, the oft-quoted fear that robos displace humans is not substantiated. Another possible line of future development lies in gamified platforms for goal-based investment. By means of a serious simulation game, investors could model various scenarios comprising their entire lifetime, taking into account their goals at different stages of career, their decisions as well as stochastic influences. At any rate, the roles of both advisers and clients will be redefined towards enhanced, comprehensive client servicing.

    Abstract I Acknowledgement II Table of Contents III List of Figures V 1. Introduction 1 1.1 Motivation 1 1.2 Goal 2 1.3 Research flow chart 3 2. Literature Review 4 2.1 Fintech Revolution 4 2.2 Artificial Intelligence 4 2.3 Robo Advisors: an overview 5 2.4 Target of Robo-advisory platforms 8 2.5 SWOT-Analysis 8 2.6 Acceptance of Digitalized services by retail customers 14 3. Research Methodology 15 3.1 Research Design 15 3.2 Case Interview 16 4. Industry Analysis 19 4.1 Robo Advisory Industry 19 4.2 Cathay United Bank - Company Introduction 19 4.3 Digitalization of Financial Advisory 20 4.4 Functions of Robo-Advice 20 4.5 Clients 21 4.6 Regulation of Robo-Advice 22 5. A case in point: market entry of a Taiwanese bank 24 5.1 Motivation for engaging in robo-advisors 24 5.2 Strategy: formulation and implementation 25 IV 5.3 Customer benefit 27 5.4 Future development 28 5.5 The Future of Robo-Advisors 28 6. Summary and Recommendations 34 6.1 Summary 34 6.2 Recommendations 36 7. Bibliography 38

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