RegTech: Analysis of the aggregators in the Swiss startups’ ecosystem during the pandemic

Author:

Battanta Luca1,Magli Francesca2ORCID

Affiliation:

1. IULM University

2. University of Milano-Bicocca

Abstract

Following the Great Financial Crisis, the emergence of digital technologies and the end of banking secrecy (“Swiss say goodbye to banking secrecy”, 2017), financial technology (FinTech) and regulatory technology (RegTech) startups have been offering products in the financial regulatory sector. This trend has increased since the outbreak of COVID-19. Most of the studies on RegTech have focused on reviewing the literature on the macro context and the issues of vast amount of regulation (Arner et al., 2017). Today the academic literature about case studies in regulatory technology is not proposing any solution of cooperation or aggregation of RegTech’s startups in Switzerland. Due to the lack of papers about RegTech in Switzerland, we adopt an approach already used for case studies in the FinTech area (Foster & Heeks, 2013; Burtch et al., 2013) through exploratory investigation through interviews and literature review. The findings of our article have allowed us to analyse the topics and the applications in the RegTech ecosystem provided by startups to Swiss banks. We examine also the aggregations, incubators, and associations active in Switzerland Swisscom, International RegTech Association (IRTA), and F10 (a Swiss FinTech incubator based in Zurich) to examine how they can bring RegTech solutions of the RegTech startups into the banks.

Publisher

Virtus Interpress

Subject

Strategy and Management,Economics and Econometrics,Finance

Reference58 articles.

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2. Anagnostopoulos, I. (2018). Fintech and regtech: Impact on regulators and banks. Journal of Economics and Business, 100, 7–25. https://doi.org/10.1016/j.jeconbus.2018.07.003

3. Arner, D. W., Barberis, J., & Buckey, R. P. (2017). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37(3), 371–413. https://scholarlycommons.law.northwestern.edu/njilb/vol37/iss3/2

4. Aziz, S., & Dowling, M. (2019). Machine learning and AI for risk management. In T. Lynn, J. G. Mooney, P. Rosati, & M. Cummins (Eds.), Disrupting finance: FinTech and strategy in the 21st century (pp. 33–50). Palgrave Pivot. https://doi.org/10.1007/978-3-030-02330-0_3

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