Effect of Emerging Technologies on Operational Efficiency of Commercial Banks in Kenya
Keywords:
Integrated Payment Technology, Predictive Data Analytics, Artificial intelligence, Crypto Assets, Operational EfficiencyAbstract
This paper examines how emerging technologies impact operational efficiency and long-term sustainability in Kenyan commercial banks. It utilizes Schumpeter's innovation theory, the Diffusion of Innovation theory, and the Technology Acceptance Model to assess the implementation of integrated payment technologies, predictive data analytics, generative artificial intelligence, and cryptocurrency in banking. While some banks have modernized their systems, many Tier II and III banks still face operational inefficiencies and rising non- performing loans. The study, involving 190 participants from 38 banks. Purposive sampling identified five respondents from each bank, specifically targeting individuals with pertinent knowledge in technology adoption and operational practices and found that adopting these technologies is crucial for enhancing operational performance. Inferential analysis revealed a strong positive relationship between emerging financial technologies and operational efficiency in Kenyan commercial banks (R = 0.836, R² = 0.699, Adj. R² = 0.683, SE = 0.3271). The model was statistically significant (F = 9.684, p < 0.05), indicating that the predictors jointly explain 69.9% of the variation in operational efficiency. All variables had significant positive effects: Integrated Payment Technology (B = 0.5294, p = 0.000), Predictive Data Analytics (B = 0.4447, p = 0.001), Generative AI (B = 0.3816, p = 0.004), and Crypto Assets Technology (B = 0.2951, p = 0.009). It concludes that the efficiency of Kenyan banks increasingly relies on effective technology integration and recommends investing in staff training, improving customer awareness, and establishing strong governance frameworks to adapt to the evolving financial landscape.
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