EBOOK

About
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.
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.