Machine learning for auditors : automating fraud investigations through artificial intelligence /

Use artificial intelligence (AI) techniques to build tools for auditing your organization. This is a practical book with implementation recipes that demystify AI, ML, and data science and their roles as applied to auditing. You will learn about data analysis techniques that will help you gain insigh...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sekar, Maris (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Apress, [2022]
Edición:[First edition].
Temas:
Auditing, Internal > Data processing.
Corporations > Accounting > Data processing.
Fraud > Prevention.
Machine learning.
Vérification interne > Informatique.
Apprentissage automatique.
Auditing, Internal > Data processing
Corporations > Accounting > Data processing
Fraud > Prevention
Machine learning
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Part I. Trusted Advisors
  • 1. Three Lines of Defense
  • 2. Common Audit Challenges
  • 3. Existing Solutions
  • 4. Data Analytics
  • 5. Analytics Structure & Environment
  • Part II. Understanding Artificial Intelligence
  • 6. Introduction to AI, Data Science, and Machine Learning
  • 7. Myths and Misconceptions
  • 8. Trust, but Verify
  • 9. Machine Learning Fundamentals
  • 10. Data Lakes
  • 11. Leveraging the Cloud
  • 12. SCADA and Operational Technology
  • Part III. Storytelling
  • 13. What is Storytelling?
  • 14. Why Storytelling?
  • 15. When to Use Storytelling
  • 16. Types of Visualizations
  • 17. Effective Stories
  • 18. Storytelling Tools
  • 19. Storytelling in Auditing
  • Part IV. Implementation Recipes
  • 20. How to Use the Recipes
  • 21. Fraud and Anomaly Detection
  • 22. Access Management
  • 23. Project Management
  • 24. Data Exploration
  • 25. Vendor Duplicate Payments
  • 26. CAATs 2.0
  • 27. Log Analysis
  • 28. Concluding Remarks.

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