Data Mining Application and Competitive Advantage of Commercial Banks in Kenya

Abstract

Nowadays, banks strive to gain a competitive edge in the marketplace thanks to globalization and cut-throat competition. Except for business processes, creating and applying a knowledge base has become a strategic tool to compete. The volatile progression of transient and stored data in financial institutions has stirred the need for new systems and computerized techniques to scrutinize vast amounts of data to find implicit and potentially insightful information. Commercial banks have discerned the value of data mining in building a knowledge base and utilizing it in strategic planning to survive and thrive in today’s highly competitive market. This study aimed to examine the correlation between data mining application and competitive advantage in the banking sector in Kenya. The objectives of the study were to determine the relationship between data mining application and competitive advantage; to establish the extent of data mining espousal; to examine the drivers of data mining adoption, and to investigate the challenges facing the implementation of data mining. The study applied the descriptive cross-sectional research design, conducted a census survey on the 38 commercial banks in the country, and used structured questionnaires in data collection. The data was analyzed using regression analysis and descriptive statistics. The results reveal that commercial banks in Kenya use data mining for deviation detection, predictive modelling, database segmentation, and link analysis in different functional areas. The application helps banks unravel hidden knowledge from vast volumes of data to realize such competitive advantages as cost leadership, customer focus, channel optimization, and informed decision-making. Thus, the application of data mining leads to considerable realization of competitive advantage. The study also found successful management of information systems, ICT advances, operational necessity, and cost reduction to be critical drivers of data mining adoption. Moreover, the findings show that data security and privacy concerns are key challenges facing data mining application in the Kenyan banking sector. Further research should be conducted on other financial institutions to look into the bearing of data mining usage on performance and competitive advantage.