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Record Nr. |
UNINA9910548176803321 |
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Autore |
Sekar Maris |
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Titolo |
Machine learning for auditors : automating fraud investigations through artificial intelligence / / Maris Sekar |
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Pubbl/distr/stampa |
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New York, New York : , : Apress Media LLC, , [2022] |
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©2022 |
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ISBN |
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Edizione |
[[First edition].] |
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Descrizione fisica |
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1 online resource (241 pages) |
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Disciplina |
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Soggetti |
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Auditing, Internal - Data processing |
Corporations - Accounting - Data processing |
Fraud - Prevention |
Machine learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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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Sommario/riassunto |
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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 |
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you gain insights into your data and become a better data storyteller. The guidance in this book around applying artificial intelligence in support of audit investigations helps you gain credibility and trust with your internal and external clients. A systematic process to verify your findings is also discussed to ensure the accuracy of your findings. Machine Learning for Auditors provides an emphasis on domain knowledge over complex data science know how that enables you to think like a data scientist. The book helps you achieve the objectives of safeguarding the confidentiality, integrity, and availability of your organizational assets. Data science does not need to be an intimidating concept for audit managers and directors. With the knowledge in this book, you can leverage simple concepts that are beyond mere buzz words to practice innovation in your team. You can build your credibility and trust with your internal and external clients by understanding the data that drives your organization. What You Will Learn Understand the role of auditors as trusted advisors Perform exploratory data analysis to gain a deeper understanding of your organization Build machine learning predictive models that detect fraudulent vendor payments and expenses Integrate data analytics with existing and new technologies Leverage storytelling to communicate and validate your findings effectively Apply practical implementation use cases within your organization Who This Book Is For AI Auditing is for internal auditors who are looking to use data analytics and data science to better understand their organizational data. It is for auditors interested in implementing predictive and prescriptive analytics in support of better decision making and risk-based testing of your organizational processes. |
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2. |
Record Nr. |
UNINA9910955733103321 |
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Autore |
Di Maio Irene Stocksieker |
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Titolo |
The multiple perspective : Wilhelm Raabe's third-person narratives of the Braunschweig period / / Irene Stocksieker Di Maio |
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Pubbl/distr/stampa |
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Amsterdam : , : J. Benjamins, , 1981 |
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ISBN |
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1-283-42477-0 |
9786613424778 |
90-272-8092-4 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (158 pages) |
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Collana |
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German language and literature monographs, , 0378-4150 ; ; v. 11 |
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Disciplina |
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Soggetti |
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Point of view (Literature) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Revised version of author's thesis (Ph.D)--Louisiana State University, [1976]. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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THE MULTIPLE PERSPECTIVE WILHELMRAABE'S THIRD-PERSON NARRATIVES OF THE BRAUNSCHWEIG PERIOD; Editorial page; Title page; Copyright page; ACKNOWLEDGMENTS; Table of Contents; INTRODUCTION; CHAPTER I. DEFINING THE MULTIPLE PERSPECTIVE; Point of View Theory; Theory on Multiple Point of View; The Multiple Perspective; Comparison of the Multiple Perspective in First-person and Third-person Narration; CHAPTER II. MULTIPLE PERSPECTIVE IN THIRD-PERSON NARRATIVES. RAABE'S BRAUNSCHWEIG WORKS; I. Structural Devices; II. Narrative Devices; A. Narrator; CHAPTER III. RELATIVITY IN THREE BRAUNSCHWEIG WORKS |
Der DräumlingI. Structural Devices; II. Narrative Devices; A. Narrator; B. Characters; Conclusion; Das Horn von Wanza; I. Structural Devices; II. Narrator and Characters; A. Narrator; B. Characters; Conclusion; Kloster Lugau; I. Structural Devices; II. Narrative Devices; Conclusion; CONCLUSION; BIBLIOGRAPHY; A. GENERAL THEORETICAL WORKS; B. PRIMARY SOURCES; C. SECONDARY SOURCES ON RAABE |
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Sommario/riassunto |
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In this study the works of Wilhelm Raabe (1831 - 1910) are being discussed, taking into account the emerge of the perspectival narration, culminating in the Braunschweig period (1870-1920). The book starts with a survey of the point of view theory, including the concept of multiple perspective, and then focusses on the works of Raabe in which |
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these various techniques will be demonstrated. Special attention is paid to three works of the Braunschweig period; Der Dräumling, Das Horn von Wanza and Kloster Lugau. |
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