THE ROLE OF AI IN FRAUD DETECTION AND PREVENTION IN ACCOUNTING: A CASE STUDY OF FINANCIAL INSTITUTIONS IN ABUJA, FCT
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CHAPTER ONE
1.1 Background of the Study
Fraudulent activities within financial institutions are a significant concern for regulators, investors, and clients. Fraud detection and prevention have traditionally relied on manual auditing processes, which are time-consuming and often ineffective against increasingly sophisticated fraud schemes. The need for more advanced, real-time solutions has led to the adoption of Artificial Intelligence (AI) technologies in the fight against fraud.
AI systems, particularly machine learning models, can analyze large volumes of transactional data to identify unusual patterns, flagging potential fraudulent activities before they escalate. These systems can learn from historical data, adapt to new fraud tactics, and provide a more proactive approach to fraud prevention than traditional methods.
This study investigates the role of AI in detecting and preventing fraud within financial institutions in Abuja, FCT, and how AI technologies contribute to enhancing the security and integrity of financial operations.
1.2 Statement of the Problem
Financial institutions in Abuja face growing concerns over fraud, with manual detection methods often failing to catch advanced fraud schemes in time. While AI has been proposed as a solution, there is limited understanding of how AI-based fraud detection systems perform in the context of Nigerian financial institutions.
1.3 Aim and Objectives of the Study
The aim of this study is to assess the role of AI in fraud detection and prevention in financial institutions in Abuja. The specific objectives are:
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To evaluate the effectiveness of AI systems in identifying and preventing fraudulent transactions.
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To analyze the impact of AI-driven fraud prevention on financial security in institutions.
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To explore the challenges financial institutions face when adopting AI for fraud detection.
1.4 Research Questions
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How effective are AI systems in detecting and preventing fraud in financial institutions?
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What are the challenges faced by financial institutions in implementing AI-based fraud detection systems?
1.5 Research Hypotheses
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AI systems significantly improve the detection and prevention of fraudulent activities in financial institutions.
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The adoption of AI-driven fraud detection enhances the overall financial security of institutions.
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Financial institutions encounter significant barriers to AI adoption, such as technical and resource limitations.
1.6 Significance of the Study
This study provides insights into how AI can revolutionize fraud detection and prevention within financial institutions, helping stakeholders mitigate risk and protect financial assets. It contributes to the literature on AI’s role in enhancing financial security and guides policymakers and institutions in the adoption process.
1.7 Scope and Limitation of the Study
The study focuses on the role of AI in fraud detection in financial institutions in Abuja, FCT. It excludes other sectors, such as retail or governmental fraud detection. Limitations include access to proprietary fraud detection systems and potential resistance to new technology adoption.
1.8 Definition of Terms
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Artificial Intelligence (AI): The ability of machines to perform tasks that require human-like intelligence, such as identifying fraud patterns.
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Fraud Detection: The process of identifying activities that involve dishonesty or misrepresentation, often involving financial transactions.
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Financial Institutions: Organizations that manage money, including banks, insurance companies, and investment firms.
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