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Artificial intelligence and resource optimization: A study of Fintech start-ups

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  • Almansour, Mohammed

Abstract

FinTechs have transformed financial service delivery by leveraging technology to execute many traditional banking functions in a superior manner. Within technology usage, the adoption of disruptive technologies such as Artificial Intelligence (AI) has been the most discussed in the FinTech space. However, the entire discussion has been either from the perspective of the use of data-driven driven algorithms, the benefits of AI, or the effect of AI on the labor market. Very few studies have focussed on examining how implementing disruptive technologies such as AI can affect FinTech start-ups’ internal organizational resources and external natural resources including minerals and the allied industries. The present study addresses this gap by collecting qualitative data from 25 employees of FinTech start-ups in the United Kingdom to understand their impact on resources, particularly the natural ones including minerals. The collected data was analyzed to uncover how the implementation of disruptive digital technologies such as AI in day-to-day operations and digital marketing of FinTech start-ups impacted the internal organizational resources, including employees. The study also sought to uncover the impact of the same on the external resources – customers, and the environment including mineral resources and the allied industry. The study's findings provide valuable insights into how FinTech start-ups can gain from AI implementation in their operations, digital marketing, and resource use optimization.

Suggested Citation

  • Almansour, Mohammed, 2023. "Artificial intelligence and resource optimization: A study of Fintech start-ups," Resources Policy, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722006936
    DOI: 10.1016/j.resourpol.2022.103250
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    References listed on IDEAS

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    1. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.

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