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Methoden der Karteninhaber-Echtheitserkennung bei Finanztransaktionen

Author

Listed:
  • Ewald Judt

    (Wirtschaftsuniversität Wien, Geschäftsführer PayLife Bank GmbH, Marxergasse 1B, A-1030 Wien/Österreich,)

  • Monika Koller

    (Wirtschaftsuniversität Wien, Institut für Marketing-Management, Augasse 2-6, A-1090, Wien/Österreich)

Abstract

Cards are currently used by billions of customers worldwide for cashless payment transactions and for cash withdrawals and are therefore of great national economic importance. Since cardholder confidence in an orderly and proper handling of financial transactions is of utmost significance, great importance has always been attached to security when card-based payment transaction systems were designed and developed. One aspect in this regard concerns methods for verifying card-holder authenticity. Especially two methods, i. e. cardholder signature and the personal identification number (PIN), have turned out to be practicable solutions so far, although their application has not been without weaknesses. Against this background, initiatives have been under way for quite some time designed to develop alternative possibilities for verifying the authenticity of cardholders, e.g. biometrical procedures. Within the framework of the present study, the procedures currently applied such as signature and, more importantly, the PIN, as well as future alternatives such as iris recognition, finger print and face recognition, have been evaluated in terms of their acceptability for customers. Based on the results so obtained, implications have been deduced for possible development scenarios as well as for consumer-side marketing methods.

Suggested Citation

  • Ewald Judt & Monika Koller, 2010. "Methoden der Karteninhaber-Echtheitserkennung bei Finanztransaktionen," Credit and Capital Markets, Credit and Capital Markets, vol. 43(4), pages 587-614.
  • Handle: RePEc:kuk:journl:v:43:y:2010:i:4:p:587-614
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    References listed on IDEAS

    as
    1. Jochen Lawrenz, 2008. "Assessing the Estimation Uncertainty of Default Probabilities," Credit and Capital Markets, Credit and Capital Markets, pages 217-238.
    2. Hamerle, Alfred & Knapp, Michael & Liebig, Thilo & Wildenauer, Nicole, 2005. "Incorporating prediction and estimation risk in point-in-time credit portfolio models," Discussion Paper Series 2: Banking and Financial Studies 2005,13, Deutsche Bundesbank, Research Centre.
    3. Christensen, Jens H.E. & Hansen, Ernst & Lando, David, 2004. "Confidence sets for continuous-time rating transition probabilities," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2575-2602, November.
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    More about this item

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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