Continuous auditing is a novel emerging technology in academia and practice. The concept of continuous auditing was conceived over two decades ago in academia and we are now at a junction where the auditing profession recognizes the implement-ability and value of a continuous audit. The book's purpose is twofold. First, the book aims to provide academics and practitioners with a compilation of select continuous auditing design science research that can be used as a springboard to future research and development. Second, the book aims to provide readers with an understand 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.

Continuous auditing is a novel emerging technology in academia and practice. The concept of continuous auditing was conceived over two decades ago in academia and we are now at a junction where the auditing profession recognizes the implement-ability and value of a continuous audit. The book's purpose is twofold. First, the book aims to provide academics and practitioners with a compilation of select continuous auditing design science research that can be used as a springboard to future research and development. Second, the book aims to provide readers with an understand 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.

In Audit Analytics in the Financial Industry, editors Jun Dai, Miklos A. Vasarhelyi and Ann F. Medinets bring together a cast of expert contributors to explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry. Separated into six parts, the contributors take a variety of approaches to this exploration. In Part One, the contributors present two articles illustrating the process of applying Audit Analytics to solving audit problems. Part Two contains four studies that use various Audit Analytics techniques to discover fraud risks and potential frauds in the credit card sector. In Part Three, the chapter focus on the insurance sector and show the application of clustering techniques in auditing. Part Four includes two chapters on how to employ Audit Analytics in the transitory system for fraud/anomaly detection. Finally, Parts Five and Six illustrate the use of Audit Analytics to assess risk in the lawsuit and payment processes. For students, researchers, and professionals in the accounting sector, this is an unmissable read exploring the latest research in Audit Analytics.

The aim of this volume is to provide an international perspective of the types of artificial intelligence research being undertaken in accounting and finance. It contains a collection of papers which were presented at the 2nd and 3rd International Meetings on Artificial Intelligence in Accounting, Finance and Tax, held in Punta Umbria, Spain, in 1996 and 1997, as mid-year international conferences of the AI/ES Section of the American Accounting Association. Most of the above paradigms, as well as fuzzy logic, intelligent agents, and natural language understanding applications, are represented here. The book is divided into four parts: 1. Introduction 2. Accounting Applications 3. Finance Applications 4. Case-Based Reasoning