Nowadays, tech companies have entered our lives in nearly every possible area of application, from smart coffee machines to algorithmic-based music recommendations. Logically, it is not a far stretch that the financial sector will also experience disruption through technology-oriented startups. The so-called FinTech’s, short for financial technology, can be independent, newly found startups, or can be implemented by existing financial institutions as a complementary sales channel and span a wide ar-ray of functions, including peer-to-peer lending and crowdfunding, cryptocurrencies and blockchain, and also, robotic investment advice. It is no surprise that this development will affect traditional financial advisory.
Mainly robo advisors are seen as one of the most disruptive technologies in the financial sector. What used to be a people’s business and strived through human connections and relationships turned digital: a robo advisor can replace all functions of traditional financial advisors at a lower cost point and while being available 24/7. Based on financial theory, the offer investors personalized portfolios – all through pressing buttons on a phone screen. Whilst promising to streamline financial investment and to make it accessible to everybody, regardless of wealth, customer adoption compared to the global financial service market has been low.
Disruptive technologies offer a lot innovative and smart features, but customers might be hesitant to try the solutions. People rely on the experience of others to build trust, and the little experience of early adopters might not be enough to influence trust to a large extent. Trust is an important factor for all services or technologies, but especially in unprecedent areas such as fully automated financial advice.
The thesis will be based on a literature review methodology and will assess the theoretical background of trust through analyzing and comparing previously done research on the matter. Additionally, a quantitative study focusing on trust-building factors in robo advisors has been used as a basis to form conclusions regarding the increase of trust. Industry insights, journal articles and conference papers build the foundation of this thesis. They were identified through the usage of scientific search engines, but also through backward and forward referencing searches. This approach provided a multitude of applicable literature from the fields of artificial intelligence and trust.
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Background Information
- The History of Investment
- The Development of Artificial Intelligence
- Robo Advisors
- The Rise of Robo Advisors
- Functions of Robo Advisors
- Configuration Phase
- Matching Phase
- Maintenance Phase
- Customer Structure
- Robo Advisors Compared to Traditional Financial Advisory
- The Meaning of Trust
- Influences on Trust
- Trust in Financial Services
- Trust in Technology
- Trust in Automation and Artificial Intelligence
- Algorithm Aversion and Algorithm Appreciation
- Trust in Robo Advisors
- Trust-influencing Mechanisms of Cheng et. al
- Humanized Product Design
- Undistrust
- Building Initial Trust
- Reputation and Trust
- User Experience and Trust
- Developing Continuous Trust
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This bachelor thesis examines the factors influencing trust in robo advisors compared to traditional financial advisors. The primary objective is to understand how trust in AI-based financial services is established and maintained. The research delves into the mechanisms that influence trust and investigates potential solutions to build trust in robo advisors. Key themes explored in this study include:- The rise and development of robo advisors within the financial technology landscape
- The role of trust in financial services and its implications for AI-based solutions
- Trust in automation and artificial intelligence, including algorithm aversion and appreciation
- Mechanisms influencing trust in robo advisors and strategies to build initial and continuous trust
- Comparisons between robo advisors and traditional financial advisors, highlighting key differences and potential advantages of each approach
Zusammenfassung der Kapitel (Chapter Summaries)
This chapter provides an overview of the history of investment and the evolution of artificial intelligence, setting the stage for the discussion of robo advisors. This chapter delves into the functions of robo advisors, including the configuration, matching, and maintenance phases, as well as the customer structure and comparison to traditional financial advisory services. This chapter explores the concept of trust, examining its various influences, particularly in the context of financial services and technology. It investigates trust in automation and AI, including factors like algorithm aversion and algorithm appreciation. This chapter focuses on trust in robo advisors, exploring trust-influencing mechanisms, humanized product design, and the role of undistrust in building trust. It also delves into strategies for developing both initial and continuous trust in robo advisors.Schlüsselwörter (Keywords)
This thesis focuses on key terms such as robo advisors, trust, artificial intelligence, financial technology, algorithm aversion, algorithm appreciation, user experience, reputation, and traditional financial advisory. The study examines the interplay between these concepts to explore the challenges and opportunities associated with building trust in AI-powered financial services.- Quote paper
- Alina Riecker (Author), 2020, Robo Advisors. How to increase trust in Artificial Intelligence compared to traditional financial advisory, Munich, GRIN Verlag, https://www.grin.com/document/978317
