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FinTech

Where are the best FinTech centers?

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New research by the Institute of Financial Services Zug (IFZ) evaluates the performance of FinTech ecosystem centers on a global scale by deriving a ranking of multiple FinTech hubs.

The ranking is led by Singapore, with its outstanding political and legal environment. However, the technological dimension is also an important driver of Singapore’s success. The two Swiss cities Zurich and Geneva rank two and three, respectively.

Toronto, New York City, San Francisco, Amsterdam, London, Hong Kong and Stockholm complete the top 10 of the overall hub ranking. The political and legal framework generally seems to be the dimension that manifests the greatest differences among the 27 cities, followed by the technological, economic and social aspects.

How the rankings are derived

FinTech Hub Ranking

Best FinTech Hub ranking chart shows Singapore, Zurich / Switzerland, Geneva / Switzerland, Toronto / Canada and Hong Kong at the top of the list.
Source: 2017 IFZ Global FinTech Rankings

The ranking methodology is based on the PESTapproach, which includes political/legal, economic, social and technological dimensions. In the new research, 68 factors are categorized into one of the four PEST-dimensions according to their affiliation, as listed below.

Classification of the indicators (bold factors on a city level)

Political/Legal

  • Political stability
  • Government effectiveness
  • Ease of paying taxes
  • Global peace
  • Regulatory quality
  • Visa restriction
  • Corruption perception
  • Costs of redundancy dismissal

Economic

  • Ease of getting credit
  • Credit to private sector
  • Ease of protecting minority investors
  • Market capitalization
  • Value of stocks traded
  • VC deals
  • Applied tariff rate
  • Domestic market size
  • Joint venture deals
  • Foreign direct investment
  • Starting a business
  • Resolving insolvency
  • Financial secrecy
  • Entrepreneurship Index
  • Purchasing power
  • Global financial centers
  • Cities competitive
  • Cost of living

Technological

  • ICT access
  • ICT use
  • ICT services imports
  • Government online services
  • L-participation
  • University-industry research collaboration
  • Researchers
  • Patents in at least two offices
  • IP payments
  • High-tech imports
  • Research in at least two offices
  • IP payments
  • High-tech imports
  • Research talents in businesses
  • Mobile cellular subscriptions
  • R&D expenditures
  • Innovation cities

Social

  • Number of students from abroad
  • Graduates in science and engineering
  • Expenditure on education
  • Government expenditure on education per pupil
  • School life expectancy
  • PISA ranking
  • Pupil-teacher ratio
  • Tertiary enrollment
  • University ranking
 

  • Knowledge-intense employment
  • Female employment advanced degree
  • Labor force quality
  • University education
  • Talent environment
  • Demographics
  • Compulsory education quality
  • Openness
  • Proclivity to attracting talent
 

  • Human capital
  • Global skills
  • World talent
  • Cluster development
  • Infrastructure quality
  • Logistics performance
  • Expat ranking
  • Quality of life
  • Global Cities Report
  • Wage level

Note that while the data for the eight indicators in bold font has been collected on a city level, the data for the 60 indicators in normal font has been collected on a countrywide level. All indicators adopt the form of a ranking of the included regions. Since not every in-scope region of this study is incorporated in every indicator, missing values occur. These missing values are replaced by the average indicator rank of the relevant region in the respective PEST-dimensions. In what follows, the three steps necessary to derive the overall hub ranking are explained and shows an overview of our methodology.

Hub ranking methodology

FinTech Hub Rankings methodology includes normalized scores based on political / legal indicators, economic indicators, social indicators and technological indicators.
Source: 2017 IFZ Global FinTech Rankings

First, each indicator is transformed into a ranking of the in-scope regions based on their individual performance. Since this analysis includes 27 different cities, every indicator ends up as a ranking of the cities from 1 (worst performance) to 27 (best performance). This procedure corrects for the different number of considered regions across the original indicators.

Second, the four PEST-dimension scores of all cities are derived. This is achieved by averaging the ranks of the underlying indicators of the respective PEST-dimension for every city. As a consequence, dimensional scores again are bound between 1 and 27, with the higher the score, the better the performance. Due to this proceeding, the relative differences in the performance of the cities in the individual PEST-dimensions are retained.

Third, the overall hub ranking is created by aggregating the dimension scores for each in-scope region and sorting the resulting values in descending order. The region with the highest aggregated PEST-dimension score ranks first, the one with the lowest on the last position. Due to the derivation of the overall scores by aggregation, the four PEST-dimensions are equally weighted in the overall hub ranking.

How can the FinTech rankings be used?

In assessing the most attractive centers for locating FinTech businesses, factors may be of varying importance to different entrepreneurs and start-ups. For this reason Thomson Reuters has partnered with the IFZ research team to produce an interactive data tool which allows factor weightings to be adjusted according to individual specific criteria.


Meet the authors

Thomas AnkenbrandThomas Ankenbrand holds a master’s degree from the University of St. Gallen and a Ph.D. from the University of Lausanne. He founded several companies and has broad experience as CEO and board member of various companies in the financial industry. Ankenbrand is currently engaged in FinTech research at the Lucerne University of Applied Sciences and Arts. In addition, he is a board member of different companies and lecturing at the University of Zurich.
Denis BieriDenis Bieri works as a scientific associate at the Institute of Financial Services Zug of the Lucerne University of Applied Sciences and Arts. In this position Bieri supports various courses and projects, especially in the field of financial services and with a specific focus on financial technology (FinTech). Simultaneously, he is pursuing a doctoral degree in economics at the University of Basel.

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