Detect fraud faster--no matter how well hidden--with IDEA automation 'Fraud and Fraud Detection' 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. 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 'Fraud and Fraud Detection' 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: Understand the different areas of fraud and their specific detection methods Identify anomalies and risk areas using computerized techniques Develop a step-by-step plan for detecting fraud through data analytics Utilize IDEA software to automate detection and identification procedures 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. 'Fraud and Fraud Detection' is a guide to more efficient, more effective fraud identification. Big data and other emerging technologies can be a fraudster's dream come true. It's a cinch to hide a few fraudulent transactions within enormous, difficult-to-manage databases. And tech-savvy fraudsters can use new software to automate their risky activities. Unhappily for them, big data can also simplify the process of fraud detection. That's where 'Fraud and Fraud Detection' comes in, showing auditors, investigators, and risk professionals how to use big data analytics to stay one step ahead of cyber criminals. Only a tiny fraction of businesses worldwide are using big data technologies to aid in fraud detection. Why? One reason could be the lack of clear resources supporting the implementation of a fraud mitigation approach that is still on the cutting-edge. 'Fraud and Fraud Detection' goes a very long way toward removing this obstacle. This hands-on book addresses all the major types of employee fraud, including cash skimming, billing schemes, payroll fraud, and many more. For each fraud type, author Sunder Gee provides tests that can be customized and automated, even for millions of transactions per day. Data analytics software is a crucial element in bringing fraud detection into the 21st century. The techniques in 'Fraud and Fraud Detection' can be used with any analytics software, and there is enough information here to develop a step-by-step plan for designing and implementing automated detection programs. Users of CaseWare's IDEA software will especially appreciate the downloadable IDEAScripts that can speed the process of making fraud detection automatic. On the companion website included with 'Fraud and Fraud Detection,' readers have access to a fully functional version of IDEA. A certain amount of fraud risk is acceptable in any organization--and Sunder Gee demonstrates this point artfully in 'Fraud and Fraud Detection.' Still, fraudsters are evolving with the times, and fraud mitigation professionals need to keep up. Right now, there is enormous potential to improve the efficiency of fraud detection through big data analytics, but almost no one is taking advantage of this opportunity. 'Fraud and Fraud Detection' opens up a clear path for accessing this untapped value. THE MUST-HAVE GUIDE TO USING BIG DATA AND AUTOMATION TO DETECT FRAUD FASTER Sooner or later, every fraudster makes a mistake. 'Fraud and Fraud Detection: A Data Analytics Approach' will show you how to automate statistical and data analytical tests to catch those mistakes, identify criminals, and 'eliminate' the fraud. With big data analytics, you can find and stop fraudulent transactions much more efficiently than ever before. Detecting a few tiny abnormalities among thousands or millions of legitimate transactions has become a simple matter thanks to big data analytics, and 'Fraud and Fraud Detection' explains how you can use these new techniques to mitigate losses and stop valuable resources from seeping through the cracks. 'Fraud and Fraud Detection' will help you reach the next phase in fraud mitigation so you can keep up with the latest challenges. You'll learn how to 'automatically' apply key tests, including variability from the center, Benford's Law, the number duplication test, the relevant size factor test, and many more, to all the major types of fraud. Starting with how to identify important data sets and ending with implementing a well-designed, automated fraud detection plan, this book covers every step of the process. 'Fraud and Fraud Detection' explains what you need to understand about big data and provides a step-by-step guide to implementing the most important tools and techniques--including templates, downloadable automation scripts, and access to the CaseWare IDEA software. This approach has been ready to go for 'years,' and it's time you took advantage of big data to uncover needless losses.