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Harnessing Artificial Intelligence and Machine Learning for Advanced Fraud Detection and Prevention
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With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting. <iframe src="https://publications.waset.org/abstracts/165809.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI" title="AI">AI</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=forensic%20accounting%20%26%20fraud%20detection" title=" forensic accounting & fraud detection"> forensic accounting & fraud detection</a>, <a href="https://publications.waset.org/abstracts/search?q=anti%20money%20laundering" title=" anti money laundering"> anti money laundering</a>, <a href="https://publications.waset.org/abstracts/search?q=Benford%27s%20law" title=" Benford's law"> Benford's law</a>, <a href="https://publications.waset.org/abstracts/search?q=fraud%20triangle%20theory" title=" fraud triangle theory"> fraud triangle theory</a> </p> <a href="https://publications.waset.org/abstracts/165809/harnessing-artificial-intelligence-and-machine-learning-for-advanced-fraud-detection-and-prevention" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">93</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" 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