The Role of Artificial Intelligence in Enhancing Fraud Detection During Audits: A Case Study of Deloitte Nigeria
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- NGN 5000
Background of the Study
Artificial intelligence (AI) is revolutionizing the auditing landscape by enabling more efficient fraud detection through predictive analytics, anomaly detection, and automation of repetitive tasks. AI systems can process vast amounts of data in real-time, identifying irregularities that may indicate fraud (Adebayo & Oladipo, 2023).
In Nigeria, Deloitte has been a leader in adopting AI-driven audit solutions to address the increasing complexity of financial fraud. This study investigates the role of AI in enhancing fraud detection during audits conducted by Deloitte Nigeria, highlighting its benefits, challenges, and implications for the auditing profession.
Statement of the Problem
Fraud remains a significant challenge in Nigeria's financial sector, undermining public trust and corporate accountability. Traditional audit methods often fail to detect sophisticated fraud schemes, necessitating the adoption of advanced technologies like AI (Ibrahim & Yusuf, 2024).
This study examines how AI enhances fraud detection during audits, focusing on Deloitte Nigeria as a case study. It also explores the challenges associated with AI adoption in the Nigerian auditing context.
Objectives of the Study
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To assess the use of AI in fraud detection during audits at Deloitte Nigeria.
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To evaluate the impact of AI on the efficiency and accuracy of fraud detection.
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To identify challenges and propose solutions for integrating AI into audit practices.
Research Questions
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How is AI used in fraud detection during audits at Deloitte Nigeria?
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What is the impact of AI on the efficiency and accuracy of fraud detection?
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What challenges are associated with integrating AI into audit practices?
Research Hypotheses
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AI significantly enhances fraud detection during audits.
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The use of AI improves the efficiency and accuracy of fraud detection.
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Challenges such as high costs and lack of expertise hinder the effective adoption of AI in auditing.
Scope and Limitations of the Study
The study focuses on Deloitte Nigeria and explores the role of AI in fraud detection during audits. Limitations include restricted access to proprietary tools and potential biases in qualitative responses.
Definitions of Terms
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Artificial Intelligence (AI): Computer systems capable of performing tasks that typically require human intelligence, such as decision-making and problem-solving.
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Fraud Detection: The process of identifying and preventing fraudulent activities within financial systems.
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Audit Efficiency: The effectiveness of the auditing process in achieving its objectives within a given timeframe and resources.
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