Using AI and Machine Learning to Edify HRM's Operational Efficiency: Insights from London-Based Fintech Companies

ABSTRACT: Thriving in the fintech world where usage of more advanced Fourth Industrial Revolution (4IR) technologies is increasingly becoming the norm requires Fintech Companies to explore all the best possible ways of attaining superior competitive advantage. As part of such quest, this study used a qualitative research approach to examine how usage of AI and machine learning technologies by most of the selected London-based Fintech Companies would enhance HRM operational efficiency. Insights from managers purposively sampled from a cross-section of Fintech Companies operating across the thirty-two London Boroughs indicated AI and machine learning usage to bolster a firm’s HRM operational efficiency. This unlocks cost and differentiation advantages to spawn the fintech’s overall competitiveness. In the increasingly disruptive 4IR Era, this improves a firm’s capability to excel and achieve the best. However, even though fintech companies are known for using more advanced 4IR technologies, findings indicated most London-based Fintech companies had not yet embraced the full use of AI and machine learning applications in their daily HR management activities. There is still a strong belief that, as compared to HR management, which requires manual processes, usage of AI and machine learning tends to be more suitable for just automating marketing, operational and other management processes. When it comes to personnel recruitment, usage of manual approach is construed as more suitable. By directly engaging with potential candidates on a one-on-one physical basis, some fintech executives feel that they can recruit and deploy the best. Such unsupportive business philosophy was found to be further exacerbated by lack of an appropriate strategy for AI and ML usage in HRM, and poor investment in proper AI, big data and machine learning technologies. To respond such challenges, findings imply that if fintech companies and other forms of businesses are to thrive, it is essential to adopt a framework analogous to Leeway-Hertz’s “Model for AI usage in HRM.”

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.15775235
Primary Topic
Language Development and Disorders
Type
article
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article

Using AI and Machine Learning to Edify HRM's Operational Efficiency: Insights from London-Based Fintech Companies

Zenodo (CERN European Organization for Nuclear Research)
Language Development and Disorders
article

Using AI and Machine Learning to Edify HRM's Operational Efficiency: Insights from London-Based Fintech Companies

article en

Abstract

ABSTRACT: Thriving in the fintech world where usage of more advanced Fourth Industrial Revolution (4IR) technologies is increasingly becoming the norm requires Fintech Companies to explore all the best possible ways of attaining superior competitive advantage. As part of such quest, this study used a qualitative research approach to examine how usage of AI and machine learning technologies by most of the selected London-based Fintech Companies would enhance HRM operational efficiency. Insights from managers purposively sampled from a cross-section of Fintech Companies operating across the thirty-two London Boroughs indicated AI and machine learning usage to bolster a firm’s HRM operational efficiency. This unlocks cost and differentiation advantages to spawn the fintech’s overall competitiveness. In the increasingly disruptive 4IR Era, this improves a firm’s capability to excel and achieve the best. However, even though fintech companies are known for using more advanced 4IR technologies, findings indicated most London-based Fintech companies had not yet embraced the full use of AI and machine learning applications in their daily HR management activities. There is still a strong belief that, as compared to HR management, which requires manual processes, usage of AI and machine learning tends to be more suitable for just automating marketing, operational and other management processes. When it comes to personnel recruitment, usage of manual approach is construed as more suitable. By directly engaging with potential candidates on a one-on-one physical basis, some fintech executives feel that they can recruit and deploy the best. Such unsupportive business philosophy was found to be further exacerbated by lack of an appropriate strategy for AI and ML usage in HRM, and poor investment in proper AI, big data and machine learning technologies. To respond such challenges, findings imply that if fintech companies and other forms of businesses are to thrive, it is essential to adopt a framework analogous to Leeway-Hertz’s “Model for AI usage in HRM.”

Zenodo (CERN European Organization for Nuclear Research)
Edinburgh Napier University (GB), Systems Analytics (United States) (US), University of the West Indies (BB)
Openalex Percentile: Top 48%
Language Development and Disorders
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