The Interplay of Industry Regulations, Technology Deployment Strategies, and Performance of Commercial Banks in Kenya

Abstract

Abstract Advances in technology in the banking sector have transformed the global landscape of financial services, conferring substantial benefits, including enhanced operational efficiency, improved standards of customer service, and expanded financial inclusivity. In Kenya, commercial banks face substantial challenges, including fragmented and slow adoption practices, which have affected their effectiveness in technology deployment. Kenya is a leader in digital financial innovations on the continent; however, commercial banks still face several issues, including slow and fragmented adoption practices. This raises serious questions about the effectiveness of their technology deployment strategies, so it's essential to examine how different deployment approaches impact bank performance. The general objective of this study was to assess the interplay between industry regulations, Technology Deployment Strategies, and the Performance of Commercial Banks in Kenya. Specifically, the study sought to investigate the effect of technology integration practices, scalability of technology deployment, and efficiency of technology management on the performance of commercial banks in Kenya, assess the moderating effect of industry regulations on the relationship between technology deployment strategies and performance of commercial banks in Kenya, and develop a technology deployment strategic decision-making model. The study was anchored on the Unified Theory of Acceptance and Use of Technology (UTAUT), the Theory of Planned Behavior (TPB), and the Resource-Based Theory. The target population consisted of the 39 commercial banks operating in Kenya. Data was collected using structured questionnaires. The collected data were compiled, coded, and analyzed using the Statistical Package for the Social Sciences (SPSS, version 28) and Microsoft Excel software. Descriptive statistics, including frequencies, means, and standard deviations, were used to reveal the characteristics of study variables. Additionally, inferential statistical tools, including Pearson correlation and multiple regression analyses, were applied to assess the nature of relationships between the variables of interest. This study aimed to provide commercial bank managers with a comprehensive framework and software model for optimizing performance through effective technology deployment strategies. The study has advanced the Technology Deployment Strategic Decision Model (TDSDM), which was tested using datasets from the 39 participating commercial banks in Kenya. The findings will inform decision-makers in selecting and implementing technology solutions that align with business objectives, regulatory requirements, and evolving customer expectations. Technology Integration Practices showed a statistically significant positive effect on bank performance (p = 0.023, β = 0.360), leading to the rejection of the null hypothesis (H01). This indicated that the improved integration of technologies, such as core banking systems, mobile platforms, and ERP systems, significantly contributed to better performance outcomes. The scalability of Technology Deployment exhibited a positive and statistically significant relationship with performance (p = 0.034, β = 0.451), resulting in rejection of the null hypothesis (H02). The efficiency of Technology Management also had a positive but statistically insignificant influence on performance (p = 0.078, β = 0.277); thus, the null hypothesis (H03) was not rejected. While efficient technology delivery frameworks were observed, their impact on performance was not statistically conclusive. Additionally, industry regulations were found to moderate the relationship between deployment strategies and performance negatively.