Big data has become one of the most important resources in modern banking. Banks generate and receive enormous volumes of information from card payments, mobile applications, online transfers, credit applications, customer service interactions, market feeds, and regulatory reports. Big data refers not merely to a large quantity of records, but to data environments whose volume, velocity, and variety require advanced storage, processing, and analytical methods. Big data in banking is the large scale integration and analysis of transactional, behavioral, financial, demographic, operational, and external information to improve decisions, automate processes, control risk, and create customer value. The importance of big data therefore lies in its conversion of raw information into timely decisions. From processing millions of daily transactions to predicting customer needs, big data analytics is transforming the banking sector into a data driven powerhouse. In this paper, we will explore what big data analytics in banking really means, explore its applications, benefits, and challenges. big data, big data analytics, banking, banker, banking industry. 43-53 Issue-5 Volume-10 Matthew N. O. Sadiku | Paul A. Adekunte | Janet O. Sadiku