The Impact of Data Analytics on Decision-Making Processes in Islamic Banking
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- NGN 5000
Background of the Study
Data analytics plays a pivotal role in transforming decision-making processes in modern banking. In Islamic finance, the application of advanced analytics is crucial for managing risk, optimizing asset allocation, and improving customer service while ensuring Shariah compliance. Islamic financial institutions (IFIs) are increasingly leveraging big data, machine learning, and predictive modeling to analyze market trends, customer behavior, and operational performance (Nasir & Karim, 2024). These tools enable more informed and timely decisions, which are essential in a competitive and rapidly evolving environment. Enhanced data analytics supports the development of tailored financial products, risk management frameworks, and efficient resource allocation strategies that align with Islamic ethical standards (Farooq & Javed, 2023).
By integrating digital data from various sources, IFIs can achieve a holistic view of their performance, leading to better strategic planning and improved financial outcomes. However, the adoption of data analytics in Islamic banking is challenged by issues related to data quality, legacy system integration, and the need for specialized analytical skills. This study investigates how data analytics influences decision-making processes within IFIs, examining the tools and techniques employed, the challenges faced, and the resultant impact on financial performance and Shariah compliance (Rahim & Sultan, 2023).
Statement of the Problem
Despite its potential to transform decision-making, data analytics adoption in Islamic banking is hindered by several challenges. One significant problem is the fragmentation of data due to outdated legacy systems, which impedes the ability to generate accurate and comprehensive insights (Nasir & Karim, 2024). Additionally, the lack of skilled personnel proficient in both advanced analytics and Islamic finance further limits the effective use of data-driven decision-making. Regulatory uncertainties and concerns over data privacy compound these issues, leading to inconsistent analytical practices and suboptimal strategic outcomes (Farooq & Javed, 2023). Consequently, IFIs may struggle to fully harness the benefits of data analytics, resulting in slower response times, inefficient resource allocation, and reduced competitiveness.
Objectives of the Study
• Examine the current use of data analytics in IFI decision-making.
• Identify challenges in data integration and analysis.
• Propose strategies to optimize data-driven decision-making while ensuring Shariah compliance.
Research Questions
• How do IFIs currently utilize data analytics in decision-making?
• What are the main challenges in integrating data analytics with legacy systems?
• What strategies can improve the accuracy and effectiveness of data-driven decisions?
Research Hypotheses
• H1: Advanced data analytics improves decision-making speed and accuracy in IFIs.
• H2: Integration of modern analytical tools with legacy systems enhances strategic outcomes.
• H3: Investment in data analytics training correlates with improved financial performance.
Scope and Limitations of the Study
Focus on IFIs in regions with emerging digital infrastructures, such as the Middle East and Southeast Asia. Limitations include variability in data quality and rapid technological evolution.
Definitions of Terms
• Data Analytics: The process of examining data sets to draw conclusions about the information they contain.
• Decision-Making Processes: Methods used by organizations to choose among alternatives.
• Big Data: Large and complex data sets that require advanced analytical techniques.
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