BIG DATA COMPLEXITY AND PERFORMANCE OF COMMERCIAL BANKS IN KENYA

Abstract

The banking industry is fast moving away from the traditional manual methods to sophisticated digital methods of doing business that is leading to production of large quantities of customer data. Despite the migration to digital era, commercial banks are still struggling to remain a float with some of them having been placed under receivership due to deteriorating performance. This study sought to determine the effect of big data complexity on performance of commercial banks in Kenya. The study used an explanatory research approach. The target group consisted of all 39 commercial banks that were registered as of December 31, 2020. Descriptive statistics was used to explain the nature of the study variables through the use of inferential statistics. Linear regression was used to determine the relationship between the study variables. The results showed that big data complexity had a significant effect on performance According to the study, management of Kenyan commercial banks should make sure that big data capabilities are user-friendly when used, employ enough human resources to effectively integrate big data capabilities into operations, ensure that staff members have no trouble using big data capabilities, and make sure that staff members have no trouble understanding or interpreting the information in big data technologies to improve performance. The research also recommends that commercial banks in Kenya should ensure that it is simple to test out big data capabilities to see if customer expectations are met and be able to pilot big data capabilities before deciding to adopt it for performance improvement.