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Artificial Intelligence for the Financial Services Industry: What Challenges Organizations to Succeed?

  • Luisa Kruse
    ,
  • Nico Wunderlich
    ,
  • Roman Beck
  • Goethe University Frankfurt
Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 6408-6417 (10 pages)

Journal (Volume, Issue Number)

Proceedings of the Annual Hawaii International Conference on System Sciences

Publication milestones

  • Accepted/In press - 2019
  • Published - 2019

Publication status

Published - 2019

ISSN

1060-3425

Publication IDs

  • Scopus: 85100649992

Abstract

As a research field, artificial intelligence (AI) exists for several years. More recently, technological breakthroughs, coupled with the fast availability of data, have brought AI closer to commercial use. Internet giants such as Google, Amazon, Apple or Facebook invest significantly into AI, thereby underlining its relevance for business models worldwide. For the highly data driven finance industry, AI is of intensive interest within pilot projects, still, few AI applications have been implemented so far. This study analyzes drivers and inhibitors of a successful AI application in the finance industry based on panel data comprising 22 semi-structured interviews with experts in AI in finance. As theoretical lens, we structured our results using the TOE framework. Guidelines for applying AI successfully reveal AI-specific role models and process competencies as crucial, before trained algorithms will have reached a quality level on which AI applications will operate without human intervention and moral concerns.

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