An Appraisal of Real-Time Analytics in Fraud Detection for Mobile Banking Applications: A Study of Fintech Companies in Yobe State
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Background of the Study
The rapid adoption of mobile banking has revolutionized the financial sector in Nigeria, making banking services more accessible and convenient. However, this shift has also led to an increase in digital fraud, such as account hacking, phishing attacks, and fraudulent transactions. To combat these threats, fintech companies have turned to real-time analytics, which allow for the immediate detection and prevention of suspicious activities (Olowoselu & Abiola, 2025).
Fintech companies in Yobe State, like their counterparts across the country, are integrating advanced fraud detection systems that utilize real-time data analytics to monitor transactions and flag potential fraud as it occurs. This study evaluates the effectiveness of real-time analytics in fraud detection within mobile banking applications used by fintech companies in Yobe State. The research aims to assess how well these technologies are mitigating fraud and identify areas where further improvements are needed.
Statement of the Problem
Despite the adoption of real-time fraud detection systems, fintech companies in Yobe State continue to face challenges in accurately identifying and preventing fraud due to the complexity of fraudulent schemes and the volume of transactions being processed. Additionally, limited resources, lack of skilled personnel, and data privacy concerns have hindered the full integration of real-time analytics in some fintech applications (Sulaimon & Tijjani, 2025). This study aims to investigate the effectiveness of these systems and provide recommendations for improvement.
Objectives of the Study
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To assess the effectiveness of real-time analytics in fraud detection within mobile banking applications in Yobe State.
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To identify the challenges faced by fintech companies in implementing real-time analytics for fraud detection.
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To propose strategies for enhancing the use of real-time analytics in fraud detection for mobile banking applications.
Research Questions
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How effective is real-time analytics in detecting fraud in mobile banking applications in Yobe State?
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What challenges do fintech companies face in implementing real-time analytics for fraud detection?
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What strategies can be implemented to enhance the effectiveness of real-time fraud detection in mobile banking applications?
Research Hypotheses
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Real-time analytics have no significant effect on reducing fraud in mobile banking applications in Yobe State.
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Challenges such as inadequate data integration and lack of skilled personnel do not significantly affect the effectiveness of real-time fraud detection systems.
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Strategies for improving the use of real-time analytics in fraud detection have no significant impact on reducing fraud rates in mobile banking.
Scope and Limitations of the Study
This study focuses on fintech companies in Yobe State that use real-time analytics for fraud detection within mobile banking applications. Limitations include difficulties in accessing proprietary data, variations in technological infrastructure across companies, and possible reluctance to disclose fraud-related information.
Definitions of Terms
Real-Time Analytics: The process of analyzing data as it is generated or received, often used to identify trends, detect anomalies, or make immediate decisions.
Fraud Detection: The process of identifying fraudulent activities, such as unauthorized transactions or account manipulation, within financial systems.
Mobile Banking Applications: Software applications that allow users to access and manage their bank accounts via mobile devices, including smartphones and tablets.
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Chapter One: Introduction
