ARTIFICIAL INTELLIGENCE TECHNOLOGIES AND BUSINESS PROCESS OPTIMISATION OF COMMERCIAL BANKS IN NASARAWA STATE, NIGERIA

Abstract

The adoption of Artificial Intelligence (AI) technologies has transformed the banking sector in various aspects, including operational efficiency. This study aims to investigate the impact of AI technologies on business process optimization in commercial banks in Nasarawa State. A descriptive research design was employed, with a population of 1,399 managerial staff, IT personnel, and operational staff directly involved in the implementation and use of AI technologies and business processes. A sample of 311 staff was obtained using the Taro Yamani formula. Data were collected using a structured questionnaire, which were analysed using frequency, percentages, mean, standard deviation and regression analysis. The results showed a significant positive effect of machine learning algorithms, natural language processing, robotic process automation, virtual assistants, and decision support systems on the efficiency of operations in commercial banks. Specifically, the regression analysis revealed that: Machine learning algorithms accounted for 23% of the variations in operational efficiency. Natural language processing contributed 18.8%. Robotic process automation contributed 26.3%. Virtual assistants accounted for 21% while Decision support systems contributed 24.5%. These findings suggest that commercial banks can significantly improve their operational efficiency by adopting and integrating AI technologies. The study thus concludes that AI technologies have a significant positive effect on business process optimization in commercial banks in Nasarawa State. The study recommends among others that management of commercial banks in Nasarawa State should invest in high-quality datasets and skilled AI professionals to develop robust machine learning models that can analyse vast amounts of data, detect patterns, and make accurate predictions. This is to improve risk management and operational efficiency and that management should deploy natural language processing-powered chatbots and virtual assistants to enhance customer service by providing real-time responses to inquiries, processing transactions, and assisting with complaints. This will reduce the workload on human agents, minimize response times and improve customer satisfaction.