IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v28y2018i3d10.1007_s12525-017-0275-0.html
   My bibliography  Save this article

Understanding FinTech start-ups – a taxonomy of consumer-oriented service offerings

Author

Listed:
  • Henner Gimpel

    (University of Augsburg)

  • Daniel Rau

    (University of Augsburg)

  • Maximilian Röglinger

    (University of Augsburg)

Abstract

The financial sector is facing radical transformation. Leveraging digital technologies to offer innovative services, FinTech start-ups are emerging in domains such as asset management, lending, or insurance. Despite increasing investments, the FinTech phenomenon is low on theoretical insights. So far, the offerings of FinTech start-ups have been predominantly investigated from a functional perspective. As a functional perspective does not suffice to fully understand the offerings of FinTech start-ups, we propose a taxonomy of non-functional characteristics. Thereby, we restrict our analysis to consumer-oriented FinTech start-ups. Our taxonomy includes 15 dimensions structured along the perspectives interaction, data, and monetization. We demonstrate the applicability of our taxonomy by classifying the offerings of 227 FinTech start-ups and by identifying archetypes via a cluster analysis. Our taxonomy contributes to the descriptive knowledge on FinTech start-ups, enabling researchers and practitioners to analyze the service offerings of FinTech start-up in a structured manner.

Suggested Citation

  • Henner Gimpel & Daniel Rau & Maximilian Röglinger, 2018. "Understanding FinTech start-ups – a taxonomy of consumer-oriented service offerings," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 245-264, August.
    • Handle: RePEc:spr:elmark:v:28:y:2018:i:3:d:10.1007_s12525-017-0275-0
    DOI: 10.1007/s12525-017-0275-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-017-0275-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12525-017-0275-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Glenn Milligan & Martha Cooper, 1988. "A study of standardization of variables in cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 181-204, September.
    2. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    3. Marc Rysman, 2009. "The Economics of Two-Sided Markets," Journal of Economic Perspectives, American Economic Association, vol. 23(3), pages 125-143, Summer.
    4. Gulamhuseinwala, Imran & Bull, Thomas & Lewis, Steven, 2015. "FinTech is gaining traction and young, high-income users are the early adopters," Journal of Financial Perspectives, EY Global FS Institute, vol. 3(3), pages 16-23.
    5. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    6. Fraley C. & Raftery A.E., 2002. "Model-Based Clustering, Discriminant Analysis, and Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 611-631, June.
    7. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 325-342, September.
    8. Peter C. Fishburn & Andrew M. Odlyzko, 1999. "Competitive pricing of information goods: Subscription pricing versus pay-per-use," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 13(2), pages 447-470.
    9. Kuo Chuen, David LEE & Teo, Ernie G.S., 2015. "Emergence of FinTech and the LASIC principles," Journal of Financial Perspectives, EY Global FS Institute, vol. 3(3), pages 24-36.
    10. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weinand, J.M. & McKenna, R. & Fichtner, W., 2019. "Developing a municipality typology for modelling decentralised energy systems," Utilities Policy, Elsevier, vol. 57(C), pages 75-96.
    2. Julian Rossbroich & Jeffrey Durieux & Tom F. Wilderjans, 2022. "Model Selection Strategies for Determining the Optimal Number of Overlapping Clusters in Additive Overlapping Partitional Clustering," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 264-301, July.
    3. Ertl, Antal & Horn, Dániel & Kiss, Hubert János, 2024. "Economic Preferences across Generations and Family Clusters: A Comment," I4R Discussion Paper Series 105, The Institute for Replication (I4R).
    4. Douglas Steinley, 2007. "Validating Clusters with the Lower Bound for Sum-of-Squares Error," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 93-106, March.
    5. Bauer, Hans H. & Fischer, Marc, 2000. "Product life cycle patterns for pharmaceuticals and their impact on R&D profitability of late mover products," International Business Review, Elsevier, vol. 9(6), pages 703-725, December.
    6. Cyril Atkinson-Clement & Eléonore Pigalle, 2021. "What can we learn from Covid-19 pandemic’s impact on human behaviour? The case of France’s lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    7. Dario Bruzzese & Domenico Vistocco, 2015. "DESPOTA: DEndrogram Slicing through a PemutatiOn Test Approach," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 285-304, July.
    8. Mark Chiang & Boris Mirkin, 2010. "Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 3-40, March.
    9. Gallegos, María Teresa & Ritter, Gunter, 2010. "Using combinatorial optimization in model-based trimmed clustering with cardinality constraints," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 637-654, March.
    10. Li, Pai-Ling & Chiou, Jeng-Min, 2011. "Identifying cluster number for subspace projected functional data clustering," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2090-2103, June.
    11. Goethner, Maximilian & Hornuf, Lars & Regner, Tobias, 2021. "Protecting investors in equity crowdfunding: An empirical analysis of the small investor protection act," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    12. Laurent Lesnard, 2010. "Setting Cost in Optimal Matching to Uncover Contemporaneous Socio-Temporal Patterns," Sociological Methods & Research, , vol. 38(3), pages 389-419, February.
    13. J. Fernando Vera & Rodrigo Macías, 2021. "On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 489-513, June.
    14. Michael Brusco & Douglas Steinley, 2015. "Affinity Propagation and Uncapacitated Facility Location Problems," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 443-480, October.
    15. Peña-Malavera Andrea & Bruno Cecilia & Fernandez Elmer & Balzarini Monica, 2014. "Comparison of algorithms to infer genetic population structure from unlinked molecular markers," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(4), pages 391-402, August.
    16. Massimiliano Agovino & Maria Ferrara & Antonio Garofalo, 2017. "The driving factors of separate waste collection in Italy: a multidimensional analysis at provincial level," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(6), pages 2297-2316, December.
    17. Zhiguang Huo & Li Zhu & Tianzhou Ma & Hongcheng Liu & Song Han & Daiqing Liao & Jinying Zhao & George Tseng, 2020. "Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 1-22, April.
    18. P. (Sundar) Balakrishnan & Martha Cooper & Varghese Jacob & Phillip Lewis, 1994. "A study of the classification capabilities of neural networks using unsupervised learning: A comparison withK-means clustering," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 509-525, December.
    19. Guidi, Lionel & Ibanez, Frédéric & Calcagno, Vincent & Beaugrand, Grégory, 2009. "A new procedure to optimize the selection of groups in a classification tree: Applications for ecological data," Ecological Modelling, Elsevier, vol. 220(4), pages 451-461.
    20. Martin Christian Höcker & Yassien Bachtal & Andreas Pfnür, 2022. "Work from home: bane or blessing? Implications for corporate real estate strategies [Work from Home: Fluch oder Segen? Implikationen für das betriebliche Immobilienmanagement]," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 8(2), pages 101-137, October.

    More about this item

    Keywords

    Financial services; Financial technology; FinTech; Business model; Services; Taxonomy;
    All these keywords.

    JEL classification:

    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • N2 - Economic History - - Financial Markets and Institutions
    • N7 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:elmark:v:28:y:2018:i:3:d:10.1007_s12525-017-0275-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.