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Computer-Aided Fraud Prevention and Detection: A Step-by-Step Guide details an automated approach to using data analysis techniques to prevent and detect fraud. New and revised case studies include an expanded emphasis on the challenges of data access, data integrity and sampling. Examples are illustrated using ACL and other software.
Advanced techniques help auditors to detect both known and unknown symptoms of fraud in the data. From Ratio analysis, data profiling and Benford’s Law to more than 60 lively cases, this book is a must read for auditors and fraud investigators.
The text includes an Educational version of ACL software as well as data files allowing you to practices the techniques described in the book.