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Artificial intelligence for audit, forensic accounting, and valuation : a strategic perspective /
"With significant and disruptive automation underway, accounting and auditing professions must rediscover themselves. The automation is permanently changing how services are developed and delivered. Due to the advent of highly cost-effective automated models that greatly outperform traditional...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons, Inc.,
[2020]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright
- Contents
- Preface
- Acknowledgments
- Part I Foundations for AI and Audit
- Chapter 1 Introduction: Staying Ahead of the Emergent Risk
- Killer Robots and Audit
- Building the Audit Function Around AI
- Staying Ahead of the Emergent Risk
- The Much-Needed Evolution of the Audit Firm
- The Claustrophobic Mini Universe of Audit
- The Problems with Today's Approach
- Enabling New Thinking in Audit
- Reinventing the Legacy Firm
- The Universe of Accounting
- The Game Plan
- References
- Chapter 2 Fourth Industrial Revolution and Its Impact on Audit
- Fourth Industrial Revolution
- How Is the Cognitive Revolution Different from Previous Revolutions?
- You and the New Era
- Opportunities and Perils of the Fourth Industrial Revolution
- Sources of Competitive Advantage in the Fourth Revolution
- Audit Magnification
- Automation & equals
- 3 As (Audit, Activism, Assurance)
- References
- Chapter 3 What Is Artificial Intelligence?
- A Brief History of AI
- Launchpad Factors
- Data Science, Machine Learning, AI, and Everything Else
- Definition of AI
- Turing Test
- Narrow VERSUS General AI
- View of the Enterprise
- Toolkit for Intelligent Audit Automation
- References
- Chapter 4 Rise of Machine Learning
- Power of Patterns
- What Is Machine Learning?
- Machine Learning Is Really Scientific Process on Steroids
- The Learning Machine
- Algorithms
- Accumulating Experience
- Techniques of Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Chapter 5 Machine Learning
- Models
- Features and Targets
- Model Induction
- Data
- Stop and Think!
- Supervised: Classification with Trees
- Classification Using Mathematical Functions
- Supervised: Simple Linear Classifier
- Supervised: Support Vector Machine
- Supervised: Naïve Bayes
- Supervised: Bayesian Belief Networks
- Supervised: k-Nearest Neighbor
- Supervised: Regression
- Supervised: Multidimensional Regression
- Unsupervised
- Neural Networks
- Preprocessing the Data
- References
- Chapter 6 Building an IAA Audit Firm: The Planning Toolkit
- Why Plan and Design?
- Studying Agents
- Conclusion to Part One
- References
- Part II Building the Automated Audit Function in the Enterprise
- Chapter 7 Obtain, Retain, and Preplan with AI
- Solving the Behavioral Problems in Audit
- Automated Preplanning Subprocesses
- Automated Pre-Engagement
- Automated Audit Planning
- Automated Pre-Engagement Activities and Work Tasks
- Pre-Engagement SADAL
- Examples of Machine Learning to Identify Deception
- Automated Audit Planning Activities and Work Tasks
- Automated Audit Planning SADALS
- Client Business Strategy Agents
- References
- Chapter 8 Automated Inherent Risk Assessment
- Total Audit Risk
- Inherent Risk
- Understanding the Business Problem