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Facilitating Informed Decision-Making in Financial Service Encounters

Author

Listed:
  • Peter Heinrich

    (University of Zurich)

  • Gerhard Schwabe

    (University of Zurich)

Abstract

While advice-giving encounters form an integral part of banks’ services, clients often buy inappropriate products and face financial consequences. Legislators have started to put banks under pressure to ensure that clients are properly educated. However, the literature describes barriers due to which client education is doomed to fail applying current advice-giving practices. Practicable alternatives to the predominant perfect agent style of advice-giving are dismissed, mainly with the argument of client-side cognitive limitations. This paper challenges this assumption by suggesting a decision-making process that seamlessly integrates educational interventions, thus supporting informed client decision-making. In the spirit of design science research, the authors take a fresh look at the problems of client education in cooperation with a large Swiss retail bank to derive generalizable requirements, and design a novel IT-supported advice-giving process. An evaluation demonstrates the design’s utility in significantly improving client learning, compared to traditional service encounters. This research extends the current discourse on service encounter design, and seeks to help practitioners to design the financial service encounters of tomorrow.

Suggested Citation

  • Peter Heinrich & Gerhard Schwabe, 2018. "Facilitating Informed Decision-Making in Financial Service Encounters," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(4), pages 317-329, August.
    • Handle: RePEc:spr:binfse:v:60:y:2018:i:4:d:10.1007_s12599-017-0501-5
    DOI: 10.1007/s12599-017-0501-5
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    References listed on IDEAS

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    Cited by:

    1. Jinjiang Wang & Yulin Ma & Zuguang Huang & Ruijuan Xue & Rui Zhao, 2019. "Performance Analysis and Enhancement of Deep Convolutional Neural Network," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 311-326, June.

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