counter create hit Fraud and Fraud Detection, + Website: A Data Analytics Approach - Download Free eBook
Ads Banner
Hot Best Seller

Fraud and Fraud Detection, + Website: A Data Analytics Approach

Availability: Ready to download

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 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.


Compare
Ads Banner

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 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.

31 review for Fraud and Fraud Detection, + Website: A Data Analytics Approach

  1. 4 out of 5

    ☘Misericordia☘ ~ The Serendipity Aegis ~ ⚡ϟ⚡ϟ⚡⛈ ✺❂❤❣

    Most of the ideas explored in here have their merits. I'm gonna harp on just 2 things: both too much technical stuff (cocerning the IDEA, I couldn't have been any less interested in it) and too little (only the IDEA and no other technical venues have been explored). Anyway, the lot of practical considerations in here could be of value to a practitioner or a student willing to learn how it all winds up being practice-wise.

  2. 5 out of 5

    Martin

  3. 4 out of 5

    Brian

  4. 4 out of 5

    Randall Schwantes

  5. 4 out of 5

    Michal

  6. 4 out of 5

    Edwin Tunggawan

  7. 4 out of 5

    Virginia Collins

  8. 4 out of 5

    Kevin Lo

  9. 4 out of 5

    Dimitri

  10. 4 out of 5

    Ana

  11. 4 out of 5

    mukul sarkar

  12. 4 out of 5

    Kim Em

  13. 5 out of 5

    Juan Manuel Sotelo

  14. 5 out of 5

    Joel Salazar

  15. 5 out of 5

    Debbie

  16. 5 out of 5

    Ramona

  17. 5 out of 5

    Dropkick Jersey

  18. 5 out of 5

    Nyai

  19. 4 out of 5

    Mayur Rathod

  20. 5 out of 5

    Bernoulli

  21. 5 out of 5

    Ken

  22. 5 out of 5

    Christina

  23. 5 out of 5

    Oksana Alheim

  24. 4 out of 5

    Zasterd

  25. 4 out of 5

    Hai Nguyen

  26. 4 out of 5

    Sanjiv V. Pilgaonkar

  27. 4 out of 5

    Elizabeth Branney

  28. 4 out of 5

    Sapphire Ng

  29. 4 out of 5

    Allison Clift

  30. 4 out of 5

    Kyle

  31. 4 out of 5

    Nico Anandito

Add a review

Your email address will not be published. Required fields are marked *

Loading...
We use cookies to give you the best online experience. By using our website you agree to our use of cookies in accordance with our cookie policy.