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.

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.

Continuous Auditing provides academics and practitioners with a compilation of select continuous auditing design science research, and it provides readers with an understanding of the underlying theoretical concepts of a continuous audit, ideas on how continuous audit can be applied in practice, and what has and has not worked in research.

The explosion of data analytics in the auditing profession demands a different kind of auditor. Auditing: A Practical Approach with Data Analytics prepares students for the rapidly changing demands of the auditing profession by meeting the data-driven requirements of today's workforce. Because no two audits are alike, this course uses a practical, case-based approach to help students develop professional judgement, think critically about the auditing process, and develop the decision-making skills necessary to perform a real-world audit. To further prepare students for the profession, this course integrates seamless exam review for successful completion of the CPA Exam.

Designed to facilitate the use of audit data analytics (ADAs) in the financial statement audit, this title was developed by leading experts across the profession and academia. The guide defines audit data analytics as “the science and art of discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling, and visualization for planning or performing the audit.” Simply put, ADAs can be used to perform a variety of procedures to gather audit evidence. Each chapter focuses on an audit area and includes step-by-step guidance illustrating how ADAs can be used throughout the financial statement audit. Suggested considerations for assessing the reliability of data are also included in a separate appendix.

​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics.

Myth-busting guidance for fraud preventionin a practical workbook format An excellent primer for developing and implementing an anti-fraud program that works, Financial Services Anti-Fraud Risk and Control Workbook engages readers in an absorbing self-paced learning experience to develop familiarity with the practical aspects of fraud detection and prevention at banks, investment firms, credit unions, insurance companies, and other financial services providers. Whether you are a bank executive, auditor, accountant, senior financial executive, financial services operations manager, loan officer, regulator, or examiner, this invaluable resource provides you with essential coverage of: How fraudsters exploit weaknesses in financial services organizations How fraudsters think and operate The tell-tale signs of different types of internal and external fraud against financial services companies Detecting corruption schemes such as bribery, kickbacks, and conflicts of interest, and the many innovative forms of financial records manipulation Conducting a successful fraud risk assessment Basic fraud detection tools and techniques for financial services companies, auditors, and investigators Fraud prevention lessons from the financial meltdown of 2007-2008 Written by a recognized expert in the field of fraud detection and prevention, this effective workbook is filled with interactive exercises, case studies, and chapter quizzes, and shares industry-tested methods for detecting, preventing, and reporting fraud. Discover how to mitigate fraud risks in your organization with the myth-busting techniques and tools in Financial Services Anti-Fraud Risk and Control Workbook.