Inhalt
<b>Detect fraud faster—no matter how well hidden—with IDEA automation</b> <p><i>Fraud and Fraud Detection</i> takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book.</p> <p>Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but <i>Fraud and Fraud Detection</i> helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers will learn to:</p> <ul> <li>Understand the different areas of fraud and their specific detection methods</li> <li>Identify anomalies and risk areas using computerized techniques</li> <li>Develop a step-by-step plan for detecting fraud through data analytics</li> <li>Utilize IDEA software to automate detection and identification procedures</li> </ul> <p>The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. <i>Fraud and Fraud Detection</i> is a guide to more efficient, more effective fraud identification.</p>