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Abstract
The emergence of financial technology around the globe is driven by efforts to deconstruct and reimagine business models embedded within financial services. Entrepreneurial endeavours to this end are diverse. Indeed, the propensity toward complexity is considerable, bridging a range of financial services, markets, innovations, industry participants, infrastructures, and technologies. This study aims to improve comprehension of the global fintech landscape. It is based on the analysis of start-ups that participated in SWIFT's Innotribe competition. We used cluster analysis to group 402 fintech start-up firms, and then selected representative cases to create a foundational understanding of the structure of the fintech landscape. The main findings of this work are: (1) the development of fintech clusters to classify core services, business infrastructures, and underlying component technologies, which characterize fintech; (2) an analysis of how fintechs synthesize different technologies to restructure flows of financial information through competitive and cooperative mechanisms of disinter-mediation, extension of access, financialization, hybridization, and personalization; (3) an analysis of related strategies for value creation connected with the competitive and cooperative mechanisms that were identified. Collectively, our results offer new insights into the diversity and range of emergent innovations and technologies that are transforming the financial services industry worldwide.
Acknowledgments
We thank the SWIFT Institute for the collaborative efforts of its team toward data collection. We are also grateful to Rob Kauffman, Chris Parker, Peter Gomber, and Bruce Weber, as well as the anonymous reviewers and editorial assistant for their guidance and assistance in refining our work.
Notes
1. Fintech, for this study, refers to the new wave of start-ups that have emerged in the wake of the financial crises, and have focused on reinterpreting and transforming traditional financial services through new forms of technological innovation.
2. The term “financial technology” refers to all technologies that underpin financial activities.
3. From 2016 the Innotribe competition focused on specific geographical areas and thus became less global.
4. Society for Worldwide Interbank Financial Telecommunication (SWIFT) is a global financial messaging infrastructure provider, founded in 1973 and headquartered in Brussels. SWIFT operates the primary digital communications channel for financial institutions engaged in correspondent banking.
5. We view payments as a service innovation that operates at the consumer/corporate/merchant levels. We distinguish fintechs focused on payments services from payment markets infrastructure providers such as Target 2, which is operated by the European Central Bank and, at the time of writing, 19 national central banks within the European Union.
6. The reader should note the difference between classifications, which were directly obtained from SWIFT, and clusters, which were the outcome of cluster analysis that we conducted on the basis of the SWIFT classification data. The terms are not interchangeable, and we have been careful to ensure that the remainder of this article adheres to this difference.
7. Ultimately, a model-based approach was chosen as we found that is provides a more stable and consistent interpretation of scaled and categorical variables (the classifications) and is less sensitive to noise and outliers in the data set. This approach allows cases (individual fintech firms) to be classified into clusters using model-based posterior membership probabilities estimated by maximum likelihood methods [Citation18].
Additional information
Notes on contributors
Daniel Gozman
Daniel Gozman is a senior lecturer at the University of Sydney and a visiting academic at Henley Business School at the University of Reading, UK. He holds a Ph.D. in information systems and innovation from the London School of Economics. He is a member of the British Standard Institute UK mirror committee to ISO for blockchain and distributed ledgers. His research has appeared in the Journal of Information Technology, Journal of Enterprise Information Management, and European Journal of E-Practice, among others. He has presented at conferences on fintech, policy and the law, and contributed to articles in the Sunday Times and other media outlets.
Jonathan Liebenau
Jonathan Liebenau is associate professor (reader) in technology management at the London School of Economics, and an associate of the Columbia Institute for Tele-Information, Columbia University. He earned his Ph.D. from the University of Pennsylvania. His research focuses on blockchain, fintech, and regulation, digital economy in China, and competition in operating systems—all with grant funding. He has consulted and conducted research for leading ICT companies, and has been engaged with the European Union and the OECD, among others.He is the author or editor of twelve books and many articles on innovation studies, Internet policy, and the history of technology. His research work has appeared in Decision Support Systems, Journal of Information Policy, Information Systems Journal, Accounting, Science and Public Policy, and other outlets.
Jonathan Mangan
Jonathan Mangan has had a career as an engineer and product life-cycle management consultant. His work with industry innovators and start-up companies has resulted in published patents and collaborations for medical Ph.D. research and product designs. His experience includes chairing a public/private start-up support organization that provided mentoring for SMEs and achieved two successful rounds of government funding. In addition to his business activities, he is completing a doctorate at the Henley Business School, UK, on the new technologies that are behind the recent rise of high-reliability organizations such as fintech firms.