An evaluation of data management practices in business banking: A case study of Wema Bank, Lagos
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Background of the Study
Data management is critical to the success of business banking, as it underpins effective decision-making, risk management, and customer service. Wema Bank in Lagos has adopted advanced data management practices to ensure the accuracy, security, and accessibility of financial information. By integrating data warehousing, real-time analytics, and robust data governance frameworks, the bank has streamlined its operations and improved the overall quality of its services (Ogunleye, 2023). These practices enable Wema Bank to extract actionable insights from large datasets, which support strategic planning, customer segmentation, and personalized service delivery. Efficient data management also plays a vital role in regulatory compliance, helping the bank meet stringent reporting requirements and mitigate risks associated with data breaches (Adenola, 2024). However, challenges such as data silos, integration issues with legacy systems, and rapidly evolving technology standards can impede the effectiveness of these practices. This study examines the data management practices employed by Wema Bank, evaluating their impact on business banking performance and identifying areas for further improvement (Chukwu, 2025).
Statement of the Problem
Despite robust data management initiatives, Wema Bank faces challenges in achieving a seamless data integration framework that fully supports business banking operations. Data inconsistencies and siloed information across different departments hinder the bank’s ability to provide a unified view of customer profiles and operational performance (Ogunleye, 2023). Moreover, the integration of modern data management systems with legacy infrastructures poses significant challenges, leading to delays in data processing and potential inaccuracies. High maintenance costs and the need for continuous staff training further complicate the effective use of data analytics. Additionally, cybersecurity concerns related to data storage and transmission expose the bank to risks that can compromise sensitive financial information (Adenola, 2024). These issues collectively impair decision-making processes and reduce operational efficiency, affecting customer satisfaction and profitability. This study aims to identify these challenges and propose strategies to optimize data management practices in business banking.
Objectives of the Study
- To evaluate the effectiveness of current data management practices at Wema Bank.
- To identify challenges related to data integration and cybersecurity.
- To recommend strategies for enhancing data quality and accessibility in business banking.
Research Questions
- How effective are Wema Bank’s data management practices in supporting business banking operations?
- What challenges affect the integration of data across various systems?
- What measures can improve data quality and security?
Research Hypotheses
- H₁: Robust data management practices significantly enhance operational efficiency in business banking.
- H₂: Data integration challenges negatively impact decision-making and service delivery.
- H₃: Enhanced cybersecurity measures and continuous training improve overall data management performance.
Scope and Limitations of the Study
This study focuses on Wema Bank’s business banking division in Lagos, reviewing data management practices over recent years. Limitations include evolving technology standards and potential access restrictions to internal data.
Definitions of Terms
- Data Management Practices: The processes and policies used to collect, store, manage, and analyze data.
- Business Banking: Financial services provided to corporate and commercial clients.
- Data Warehousing: The storage of large volumes of structured data for analysis and reporting.
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