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Machine Learning For Auditors
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Book Synopsis Machine Learning for Auditors by : Maris Sekar
Download or read book Machine Learning for Auditors written by Maris Sekar and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 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.
Book Synopsis Machine Learning for Auditors by : Maris Sekar
Download or read book Machine Learning for Auditors written by Maris Sekar and published by Apress. This book was released on 2022-02-27 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 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.
Book Synopsis Machine Learning Applications for Accounting Disclosure and Fraud Detection by : Papadakis, Stylianos
Download or read book Machine Learning Applications for Accounting Disclosure and Fraud Detection written by Papadakis, Stylianos and published by IGI Global. This book was released on 2020-10-02 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.
Book Synopsis Audit Analytics in the Financial Industry by : Jun Dai
Download or read book Audit Analytics in the Financial Industry written by Jun Dai and published by Emerald Group Publishing. This book was released on 2019-10-28 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Split into six parts, contributors explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry. Chapters include topics such as fraud risks in the credit card sector, clustering techniques, fraud and anomaly detection, and using Audit Analytics to assess risk in the lawsuit and payment processes.
Book Synopsis The Essentials of Machine Learning in Finance and Accounting by : Mohammad Zoynul Abedin
Download or read book The Essentials of Machine Learning in Finance and Accounting written by Mohammad Zoynul Abedin and published by Routledge. This book was released on 2021-06-20 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Book Synopsis The Data-Confident Internal Auditor by : Yusuf Moolla
Download or read book The Data-Confident Internal Auditor written by Yusuf Moolla and published by Lioncrest Publishing. This book was released on 2021-12-07 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: For internal auditors, developing trends in data analysis and data science can feel less like a wealth of information and more like an avalanche. Still, better use of data provides an opportunity to advance your career by adopting new, invaluable skills. The missing link? Jargon-free guidance that cuts through the hype. The Data-Confident Internal Auditor demystifies the use of data in internal audits through practical, step-by-step guidance. With concepts and tools that are easy to understand and apply, this comprehensive guide shows you how to approach data yourself, without having to wait on data scientists or technical experts. Developed over the course of hundreds of actual audits, these real-world approaches and practices are distilled into a simple sequence of steps that will leave you feeling confident and even eager to apply them for yourself. Pick up The Data-Confident Internal Auditor and start building your data skills today.
Book Synopsis Artificial Intelligence in Accounting by : Cory Ng
Download or read book Artificial Intelligence in Accounting written by Cory Ng and published by Taylor & Francis. This book was released on 2020-12-08 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the intersection of AI and the accounting profession. This innovative book also explores the challenges and ethical considerations of AI. It will be of great interest to accounting practitioners, researchers, educators, and students.
Book Synopsis University Auditing in the Digital Era by : Sezer Bozkus Kahyaoglu
Download or read book University Auditing in the Digital Era written by Sezer Bozkus Kahyaoglu and published by CRC Press. This book was released on 2022-04-05 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores how digital transformation is reshaping the manner in which higher education sectors emerge, work, and evolve and how auditors should respond to this challenging and risky digital audit universe in transforming the higher education system. It serves to help professionals to understand the reality of performing the Chief Audit Executive (CAE) role in today’s evolving business economy, specifically in the higher education sector. It compares and contrasts the stated IIA standards with the challenges and realities auditors may face and provides alternative scenarios to gaining a "seat at the table." This book also provides insight into critical lessons learned when executing the CAE role relevant for digitally transforming universities. The main purpose of this study is to rethink the audit culture in the digital era and reveal the key characteristics that are open for improvement so that digitally transforming universities can be audited according to the higher education standards with a digitally supported value-added audit approach. Based on this approach, the audit culture is reassessed considering the digital university conceptual framework and business model. There are two main points to consider for the digital university work environment: traceability and auditability. In this respect, policy recommendations are made for best practices to achieve value-added digital audits in transforming universities. The book has been written from both the reality and academic perspectives of two experienced authors. Sezer is a past CAE, CEO, and long-term senior internal auditor who has worked in the internal audit role for various listed companies, financial institutions, and government entities. Erman has extensive information technology and university accreditation knowledge in the global higher education sector. This brings a blend of value-added approaches to the readers and speaks to issues about understanding and dealing with audit culture and business evolution in digitally transforming organizations along with the requirements for upholding IIA standards. Geared toward the experienced or new CAE, University Auditing in the Digital Era: Challenges and Lessons for Higher Education Professionals and CAEs can be a tool for all auditors to understand some of the challenges, issues, and potential alternative solutions when executing the role of university auditing. In addition, it can be a valuable reference for university administrators and CIOs, as well as academics and all stakeholders related to the higher education sector.
Book Synopsis Auditing the Risk Management Process by : K. H. Spencer Pickett
Download or read book Auditing the Risk Management Process written by K. H. Spencer Pickett and published by John Wiley & Sons. This book was released on 2005-07-29 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk management is a part of mainstream corporate life that touches all aspects of every type of organization. Auditors must focus firmly on risk: risk to the business, the executives, and the stakeholders. Auditing the Risk Management Process incorporates all the latest developments in risk management as it applies to auditors, including the new Committee of Sponsoring Organizations of the Treadway Commission (COSO) enterprise risk paper. Auditing the Risk Management Process includes original risk maps and process models developed by the author, explaining where and how topics fit within an overall audit framework, all the latest developments in risk management as it applies to auditors, and insight into how enterprise risk management affects the responsibilities of both internal and external auditors.
Download or read book Agile Auditing written by Raven Catlin and published by John Wiley & Sons. This book was released on 2021-07-21 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master new, disruptive technologies in the field of auditing Agile Auditing: Fundamentals and Applications introduces readers to the applications and techniques unlocked by tested and proven agile project management principles. This book educates readers on an approach to auditing that emphasizes risk-based auditing, collaboration, and speedy delivery of meaningful assurance assessments while ensuring quality results and a focus on the areas that pose the greatest material risks to the business under audit. The discipline of auditing has been forever changed via the introduction of new technologies, including: Machine learning Virtual Conferencing Process automation Data analytics Hugely popular in software development, the agile approach is just making its way into the field of audit. This book provides concrete examples and practical solutions for auditors who seek to implement agile techniques and methods. Agile Auditing is perfect for educators, practitioners, and students in the auditing field who are looking for ways to introduce greater levels of efficiency and effectiveness to their discipline.
Book Synopsis The Essentials of Machine Learning in Finance and Accounting by : Mohammad Zoynul Abedin
Download or read book The Essentials of Machine Learning in Finance and Accounting written by Mohammad Zoynul Abedin and published by Routledge. This book was released on 2021-06-20 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: • A useful guide to financial product modeling and to minimizing business risk and uncertainty • Looks at wide range of financial assets and markets and correlates them with enterprises’ profitability • Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets • Real world applicable examples to further understanding
Book Synopsis Auditing Information Systems by : Jack J. Champlain
Download or read book Auditing Information Systems written by Jack J. Champlain and published by John Wiley & Sons. This book was released on 2003-04-01 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you been asked to perform an information systems audit and don't know where to start? Examine a company's hardware, software, and data organization and processing methods to ensure quality control and security with this easy, practical guide to auditing computer systems--the tools necessary to implement an effective IS audit. In nontechnical language and following the format of an IS audit program, you'll gain insight into new types of security certifications (e.g., TruSecure, CAP SysTrust, CPA WebTrust) as well as the importance of physical security controls, adequate insurance, and digital surveillance systems. Order your copy today!
Book Synopsis Data Analytics for Intelligent Transportation Systems by : Mashrur Chowdhury
Download or read book Data Analytics for Intelligent Transportation Systems written by Mashrur Chowdhury and published by Elsevier. This book was released on 2017-04-05 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Includes case studies in each chapter that illustrate the application of concepts covered Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies Contains contributors from both leading academic and commercial researchers Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications
Book Synopsis Audit Analytics by : J. Christopher Westland
Download or read book Audit Analytics written by J. Christopher Westland and published by Springer. This book was released on 2024-03-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, using R and RStudio, demonstrates how to render an audit opinion that is legally and statistically defensible; analyze, extract, and manipulate accounting data; build a risk assessment matrix to inform the conduct of a cost-effective audit program; and more. Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control. Additionally, a firm’s data—particularly in the case of finance, software, insurance and biotech firms—comprises most of the audited value of the firm. Financial audits are critical mechanisms for ensuring the integrity of information systems and the reporting of organizational finances. They help avoid the abuses that led to passage of legislation such as the Foreign Corrupt Practices Act (1977), and the Sarbanes-Oxley Act (2002). Audit effectiveness has declined over the past two decades, as auditor skillsets have failed to keep up with advances in information technology. Information and communication technology lie at the core of commerce today and are integrated in business processes around the world. This book is designed to meet the increasing need of audit professionals to understand information technology and the controls required to manage it. This 2nd edition includes updated code and test. Machine learning, AI, and SEC’s EDGAR data are also, improved and updated. The material included focuses on the requirements for annual Securities and Exchange Commission audits (10-K) for listed corporations. These represent the benchmark auditing procedures for specialized audits, such as internal, governmental, and attestation audits. Many examples reflect the focus of the 2024 CPA exam, and the data analytics-machine learning approach will be central to the AICPA’s programs, in the near future.
Book Synopsis Ensemble Machine Learning by : Cha Zhang
Download or read book Ensemble Machine Learning written by Cha Zhang and published by Springer Science & Business Media. This book was released on 2012-02-17 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
Book Synopsis A Human's Guide to Machine Intelligence by : Kartik Hosanagar
Download or read book A Human's Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.
Book Synopsis Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 by : D. Jude Hemanth
Download or read book Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 written by D. Jude Hemanth and published by Springer Nature. This book was released on with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt:
