Robo Advisors. How to increase trust in Artificial Intelligence compared to traditional financial advisory

Table of Contents

1. Introduction

2. Background Information

2.1 The History of Investment

2.2 The Development of Artificial Intelligence

3. Robo Advisors

3.1 The Rise of Robo Advisors

3.2 Functions of Robo Advisors

3.2.1 Configuration Phase

3.2.2 Matching Phase

3.2.3 Maintenance Phase

3.3 Customer Structure

3.4 Robo Advisors Compared to Traditional Financial Advisory

4. The Meaning of Trust

4.1 Influences on Trust

4.2 Trust in Financial Services

4.3 Trust in Technology

4.3.1 Trust in Automation and Artificial Intelligence

4.3.2 Algorithm Aversion and Algorithm Appreciation

5. Trust in Robo Advisors

5.1 Trust-influencing Mechanisms of Cheng et. al

5.2 Humanized Product Design

5.3 Undistrust

5.4 Building Initial Trust

5.4.1 Reputation and Trust

5.4.2 User Experience and Trust

5.5 Developing Continuous Trust

6. Conclusion

Objectives & Research Focus

This thesis examines how trust-building factors influence customer adoption and usage of robo advisors, specifically comparing them to traditional financial advisory services. The study focuses on identifying mechanisms that enhance trust in fully automated financial platforms by analyzing the interplay between product design, reputation, and the investor's perspective.

• Theoretical analysis of trust within financial services and automated technology.
• Assessment of the "Trust Cycle" in the context of robo advisory services.
• Comparison of features and trust-influencing factors between human advisors and algorithms.
• Evaluation of user experience and product design as catalysts for initial trust.
• Exploration of how algorithm aversion can be mitigated to increase adoption.

Excerpt from the Book

Summary of Chapters

1. Introduction: Outlines the rise of robo advisors as a disruptive technology in the financial sector and establishes the research goal of identifying trust-building factors.

2. Background Information: Covers the historical evolution of investment methods and the technological development of Artificial Intelligence that enabled modern advisory tools.

3. Robo Advisors: Provides a comprehensive overview of robo advisor functions, their evolutionary stages, and a detailed comparison against traditional human financial advisors.

4. The Meaning of Trust: Analyzes the multidisciplinary nature of trust, focusing specifically on trust in financial services and the unique dynamics of trusting technology and AI.

5. Trust in Robo Advisors: Evaluates specific mechanisms that influence trust in robo advisors, exploring reputation, user experience, and strategies to overcome algorithm aversion.

6. Conclusion: Synthesizes findings to demonstrate how robo advisors can leverage their inherent advantages in accessibility and transparency to strengthen trust-worthiness.

Keywords

Robo Advisors, Financial Technology, Artificial Intelligence, Initial Trust, Continuous Trust, Algorithm Aversion, Algorithm Appreciation, Financial Services, Customer Adoption, User Experience, Reputation, Portfolio Management, Information Quality, Asset Allocation, Trust-Building.

Frequently Asked Questions

What is the primary focus of this research?

The thesis explores how trust-building factors, such as reputation and user experience, can increase investor trust and customer adoption of automated robo advisor platforms.

What are the central themes discussed in this work?

The work focuses on the intersection of finance, technology, and psychology, specifically examining trust in AI, the differences between human and algorithmic advice, and the stages of trust formation.

What is the core objective of the thesis?

The primary objective is to analyze how robo advisors can improve their product offerings and communication strategies to build trust and compete effectively with traditional financial advisors.

Which scientific methodology is applied here?

The thesis utilizes a literature review methodology to synthesize existing research, complemented by a quantitative assessment of trust-influencing factors derived from industry insights and prior studies.

What topics are covered in the main body?

The main body covers the history of investment, the technological functions of robo advisors, the multidisciplinary definition of trust, and the factors affecting trust in AI-driven financial advice.

Which keywords best characterize this work?

Key terms include Robo Advisors, trust, customer adoption, algorithm aversion, financial services, and user experience.

What is "Algorithm Aversion"?

Algorithm aversion describes the phenomenon where humans tend to trust inferior human judgments over superior but imperfect algorithmic predictions, especially after witnessing the algorithm make a mistake.

How can robo advisors overcome trust barriers?

Robo advisors can mitigate distrust by providing transparent processes, enabling user control (e.g., manual rebalancing), and maintaining high information quality to ensure investors understand the rationale behind automated decisions.