Publication Type

PhD Dissertation

Version

publishedVersion

Publication Date

5-2023

Abstract

As technology rapidly permeates all aspects of our lives, it is not unusual to question and even challenge the rationale on why certain industries are slower to adapt to the new digital age. Insurance is a business that is under scrutiny given its traditional ways of selling and legacy challenges. Why is technology investment in insurance companies lagging others? One emerging technological disruption is artificial intelligence (AI). It is the science of designing and building intelligent systems that can complete tasks traditionally performed by humans. AI is expected to fundamentally transform today’s marketplace, for businesses and consumers alike. However, because AI is a new technology that differs from prior technology in scale, performance, and sophistication, there is relatively limited understanding to how key stakeholders in the market—managers and consumers—respond to this new technology. Moreover, even less is known about the implications of AI technology for the insurance market in Singapore. In this dissertation, I explore the considerations and reactions of managers and consumers for AI in marketing applications for insurance in Singapore. To understand management’s perspective for insurance companies, the paper included a qualitative study based on in-depth interviews with prominent leaders like Chief Executive Officers (CEOs) and industry veterans on technology investment appetite into insurance operations. This allows a better understanding of the school of thoughts when it comes to technology investments in insurance and how it potentially shapes the future of digitalization in insurance. To understand consumer perspective with users of emerging technology, the core of the paper includes a field study approach on consumer responses toward Artificial Intelligence Chatbot (AIC) in consumers’ purchase journey for insurance products in Singapore. I propose that AIC as a technology, when applied to the distribution of General Insurance (GI) products, specifically Motor Insurance (MI), is a better channel than via humans or the internet. The approach is based on the actual distribution of MI via a licensed broker in Singapore to consumers. The interactive nature of AIC suggests that it mimics the human sales process of insurance products to consumers and in addition, performs better than humans in various aspects. The findings show that consumers are more responsive in earlier as well as later parts of their purchase journey for insurance in Singapore, compared to typical responses in other sales channels (e.g., human agents) for insurance. Overall, the results suggest that AIC technology can be applied to other insurance products and potentially other financial products and services. AIC is an emerging area, and its application presents plenty of research opportunities, particularly in the field of financial services. Currently, there are limited actual field studies on AIC on its effort as a channel and mode for marketing and sale of financial services products. It also predicts what the future holds for AIC in financial services.

In addition to the data collected for AIC on MI, the research also included survey questions to better understand consumer behavior. The field study is a descriptive research that supported the fact that AIC is indeed a technology that perform better than any other remote tools in the market for MI and that there are various similarities of AIC to an actual insurance sales process that makes it well positioned to be the distribution channel for the future for insurance products.

Keywords

Insurance, Chatbot, General Insurance, Motor insurance, Technology investments

Degree Awarded

PhD in Business (General Management)

Discipline

Artificial Intelligence and Robotics | Finance | Technology and Innovation

Supervisor(s)

CHANG, Han-Wen Hannah

First Page

1

Last Page

138

Publisher

Singapore Management University

City or Country

Singapore

Copyright Owner and License

Author

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