Computer-aided fraud prevention and detection : a step-by-step guide / David Coderre.

Includes bibliographical references (p. 275-276) and index.

What is fraud? : Fraud: a definition ; Why fraud happens ; Who is responsible for fraud detection? ; What is a fraud awareness program? ; What is a corporate fraud policy? -- Fraud prevention and detection : Detecting fraud ; Determining the exposure to fraud ; Assessing the risk that fraud is occurring (or will occur) ; External symptoms ; Identifying areas of high risk for fraud ; Looking at the exposures from the fraudster's perspective ; Approach 1: Control weaknesses ; Approach 2: Key fields ; Being alert to the symptoms of fraud ; Building programs to look for symptoms ; Investigating and reporting instances of fraud ; Implementing controls for fraud prevention -- Why use data analysis to detect fraud? : Increased reliance on computers ; Developing CAATT's capabilities ; Integrated analysis and value-added audit ; Recognizing opportunities for CAATT's ; Developing a fraud investigation plan -- Solving the data problem : Setting audit objectives ; Defining the information requirements ; Accessing data ; Data paths ; Data file attributes and structures ; Assessing data integrity ; Overview of the application system ; Overview of the data -- Understanding the data : Computer analysis ; Analysis techniques ; Assessing the completeness of the data ; Expression/equation ; Gaps ; Statistical analysis ; Duplicates ; Sorting and indexing -- Overview of the data : Summarization ; Stratification ; Cross tabulation/pivot tables -- Working with the data : Aging ; Join/relation -- Analyzing trends in the data : Trend analysis ; Regression analysis ; Parallel simulation -- Known symptoms of fraud : Known and unknown symptoms ; Fraud in the payroll area ; Fraud in the purchasing area ; Symptoms of purchasing fraud -- Unknown symptoms of fraud (using digital analysis) : Data profiling ; Ratio / variance analysis ; Benford's law -- Automating the detection process : Fraud applications or templates ; Fraud application development -- Verifying the results : Confirmationletters ; Sampling ; Judgmental or directed sampling ; Statistical sampling ; Quality assurance ; Quality assurance methodology ; Preventive controls ; Detective controls ; Corrective controls ; Ensuring reliability ; Data analysis and prosecuting fraud -- Appendix A. Fraud investigation plans : Insurance policies: too good to be true ; Paid by the numbers -- Appendix B. Application of CAATT's by functional area -- Appendix C. ACL installation process.

This thorough and highly readable guide is filled with authoritative tips, techniques, and advice on: what fraud is really costing your organisation; why use data analysis to detect fraud? How to assess the risk that fraud is occurring and automating your corporate fraud detection process.

rpm 22/05/13

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