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This handbook is designed to combine academic and practitioner literature on accounting or auditing and computer science or knowledge engineering expert systems. It discusses artificial intelligence, decision support, and expert systems in accounting and auditing.
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.
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.
The articles in this volume offer an introductory overview of artificial intelligence in accounting and auditing. They seek to provide a logically arranged and usable handbook of artificial intelligence, decision support, and expert systems in accounting and auditing.
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A study of artificial intelligence in accounting and auditing, this handbook addresses knowledge representation, accounting applications and the future. Topics covered include: knowledge elicitation and representation; belief nets of Bayesian revisions; accounting applications; and more.