推薦序
This book is designed to be a comprehensive guide for learners to develop their skills in big data analysis, text mining, and machine learning using the JCAATs AI audit software。 The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions。 The book also includes simulated independent audit case exercises to help learners apply what they have learned to real-world business environments and develop their problem-solving abilities。 The operating manuals for each audit instruction enable teachers to deliver No Code courses that are more practical and aligned with real-world applications。 Overall, this book aims to provide a powerful knowledge system for smart auditing and equip learners with the knowledge and skills needed for the modern workplace。
This book provides an educational version of the JCAATs - AI audit software for trial use, with a multi-language interface。 This allows students to install the software on their personal computers for operational practice and learning。 Since the JCAATs software is based on Python, it is easier to incorporate external resources into advanced Read Code and Write Code teaching, providing students with the necessary tools to develop their skills in big data analysis, text mining, and machine learning for the future auditing。
作者序
As the world enters the AI era, auditors face new challenges and opportunities that require them to use the right tools and technologies to stay ahead。 With over 20 years of experience in audit and business data analytic, I have gained a deep understanding of the importance of transitioning from traditional audit operations to smart auditing that involves proactive warning or prediction using AI。 Smart auditing enables businesses to obtain valuable insights and identify potential risks that traditional auditing methods may not detect。 By using AI to analyze large amounts of structured and un-structured data, auditors can provide more accurate and insightful audits, as well as assist with compliance and risk management。
JCAATs is a new audit software for smart auditing。 It utilizes AI language Python and can run on Windows and MAC operating systems。 It offers traditional computer-aided audit tools (CAATs) data analysis functions along with AI functions such as text mining, machine learning, and data crawling, resulting in smarter audit analysis。 The software allows for the analysis of large amounts of data and an open data architecture that enables interfacing with various databases, cloud data sources, and different file types, making data collection and integration more convenient and faster。 Additionally, the multiple language and visual user interface makes generating Python audit programs simple and easy, even for auditors not familiar with Python language。 Integrating with open-source Python program resources enables more scalability and openness for audit programs, eliminating the limitations of only a few software programs。
This textbook explains the use of technology such as big data analysis, text mining, and machine learning in auditing through practical cases。 Readers will gain an understanding of data analysis and smart audit and their advancements。 JCAATs, which includes data fusion technology and an OPEN DATA connector, helps auditors quickly obtain heterogeneous data for audit operations, enhancing effectiveness and efficiency。 The textbook includes exercise data for practicing with JCAATs to fully experience intelligent auditing practices。 It's suitable for professionals like accountants, auditors, legal and compliance personnel, risk management, and information security, as well as managers at all levels, college teachers, and students with data analysis needs。
Sherry Huang ICCP, CEAP, CFAP, CIA, CCSA
Jacksoft Ltd。, Taipei, Taiwan
2023/03/15