Chapter 19: Decrypting The Wealthtech Mindset

This paper’s first challenge is to encapsulate key elements of the WealthTech eco- system despite the complexity of the sector. A focal point is therefore to demystify the FinTech and WealthTech mindset arenas. The models are original and based on case studies made by the FinTechLab.ca in Canada. Ultimately, this contribution will shed new light on the future of the WealthTech industry. What exactly is WealthTech? Canada’s FinTechLab.ca defines it as follows: “Field arising from the symbiosis of digital platforms, Internet of Things (IoT) and artificial intelligence (AI) in wealth and asset management, generally at odds with traditional advisory firms in the sector” (Lacasse &Lambert 2017b). With academic knowledge on WealthTech still relatively limited, we concur with Henry Mintzberg of McGill University, who stated: “It seems far more important to research important topics with soft methodologies than marginal topics with elegant methodologies. (...) Most of the real insight has come from studies that used soft methodologies.” (Mintzberg, 1979). An exploratory and qualitative approach was selected because of the constraints of WealthTech’s exponential growth, which means that the 2013-2016 database is already obsolete. Although Canada’s FinTechLab.ca investigated the phenomenon in the United States, in China and in United Kingdom, most of the fieldwork and action-research were done in Canada. Data sources ranged from classical ethnography to state and governmental studies, documentary evidence, participant observation, semi-structured interviews, action-research and case studies (Wealthsimple, Betterment and Wealthfront). Data from research reports by the Big Four accounting firms (PWC, Deloitte, EY and KPMG) were also very useful.