Machine Learning for Auditors

Automating Fraud Investigations Through Artificial Intelligence

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Éditeur :

Apress


Paru le : 2022-02-26



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Description
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 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 advisorsPerform exploratory data analysis to gain a deeper understanding of your organizationBuild machine learning predictive models that detect fraudulent vendor payments and expensesIntegrate data analytics with existing and new technologiesLeverage storytelling to communicate and validate your findings effectivelyApply 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. 
Pages
242 pages
Collection
n.c
Parution
2022-02-26
Marque
Apress
EAN papier
9781484280508
EAN PDF
9781484280515

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
24
Taille du fichier
7823 Ko
Prix
62,11 €
EAN EPUB
9781484280515

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
24
Taille du fichier
9349 Ko
Prix
62,11 €

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