TABLE OF CONTENTS Case Studies. Preface. CHAPTER 1: What Is Fraud? CHAPTER 2: Fraud Prevention and Detection. CHAPTER 3: Why Use Data Analysis to Detect Fraud? CHAPTER 4: Solving the Data Problem. CHAPTER 5: Understanding the Data. CHAPTER 6: Overview of the Data. CHAPTER 7: Working with the Data. CHAPTER 8: Analyzing Trends in the Data. CHAPTER 9: Known Symptoms of Fraud. CHAPTER 10: Unknown Symptoms of Fraud. CHAPTER 11: Automating the Detection Process. CHAPTER 12: Verifying the Results. APPENDIX 1: Fraud Investigation Plans. APPENDIX 2: Application of CAATTs by Functional Area. APPENDIX 3: ACL Installation Process. Epilogue. References. Index

Mode of access: World Wide Web