An investigation of big data utilization in corporate banking: A case study of Union Bank Nigeria, Lagos
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Background of the Study
Big data utilization has become a cornerstone in modern corporate banking, enabling banks to harness vast amounts of information to drive strategic decision-making. Union Bank Nigeria in Lagos has implemented big data analytics to enhance its corporate banking operations by extracting actionable insights from complex datasets. These insights support improved risk management, customer segmentation, and personalized product offerings, ultimately boosting operational efficiency and profitability (Adenola, 2023; Oluwaseun, 2024). By leveraging big data, the bank can analyze trends in credit performance, detect fraudulent activities, and predict market shifts, thereby enabling proactive risk mitigation and tailored service delivery. The integration of big data analytics into corporate banking also facilitates real-time decision-making, which is crucial in a rapidly evolving financial environment. However, challenges such as data quality issues, integration with legacy systems, and the need for skilled data analysts persist, limiting the full potential of big data initiatives. This study investigates the current state of big data utilization at Union Bank, examining its impact on corporate banking performance and identifying strategies for optimizing data management and analytical processes.
Statement of the Problem
Union Bank Nigeria faces challenges in fully leveraging big data to enhance corporate banking operations. Inconsistencies in data quality, stemming from disparate sources and legacy systems, hinder the extraction of reliable insights. Additionally, the high costs associated with advanced big data analytics infrastructure and the shortage of skilled personnel limit the bank’s ability to maximize the benefits of big data. Regulatory concerns related to data privacy and security further complicate data utilization. These challenges collectively impede the bank’s ability to implement a comprehensive big data strategy, thereby affecting risk management, customer targeting, and overall operational performance (Adenola, 2023; Oluwaseun, 2024; Chukwu, 2025).
Objectives of the Study
- To assess the current utilization of big data in Union Bank’s corporate banking division.
- To identify challenges related to data quality, integration, and skills.
- To recommend strategies for optimizing big data analytics for improved decision-making.
Research Questions
- How is big data currently utilized in corporate banking at Union Bank?
- What challenges affect the quality and integration of big data?
- What measures can enhance big data utilization and analytical effectiveness?
Research Hypotheses
- H₁: Effective big data analytics significantly improve risk management and decision-making in corporate banking.
- H₂: Data quality and integration issues negatively impact big data outcomes.
- H₃: Targeted training and infrastructure investments enhance the benefits of big data utilization.
Scope and Limitations of the Study
The study focuses on Union Bank’s corporate banking division in Lagos, reviewing big data initiatives over recent years. Limitations include potential data inconsistencies and evolving data privacy regulations.
Definitions of Terms
- Big Data Utilization: The process of analyzing large datasets to extract actionable insights.
- Corporate Banking: Banking services provided to large business entities.
- Data Analytics: Techniques used to process and analyze data for decision-making.
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