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.

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.

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.

The authors, Arslan Khan and Edward Zimmer, demystify any perceived complexities in establishing a robust analytics control function. They provide a simple process to develop and implement an audit analytics strategy to meet the specific needs of organizations. This book provides practical approaches to using data analytics to enable continuous auditing to monitor the effectiveness of business controls. The authors' experience in developing data analytics that support an Internal Audit function can also be leveraged in other areas of the organization. Through the use of simple examples and practical tips, a framework for developing a sustainable audit analytics strategy is provided. Specific guidance is also provided regarding the talent, processes, and technology needed to move from your current state to the target environment. The business case has moved from "can the organization afford an audit analytics function" to "can an organization afford NOT to have an audit analytics function."

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.

There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitioner’s viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting Data Analytics. The spread of IT systems makes it necessary that auditors as well as management have the ability to examine high volumes of data and transactions to determine patterns and trends. The increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools. This book takes an auditor from a zero base to an ability to professionally analyze corporate data seeking anomalies.

The integrated meta-model for organizational resource audit is a consistent and comprehensive instrument for auditing intangible resources and their relations and associations from the network perspective. This book undertakes a critically important problem of management sciences, poorly recognized in literature although determining the current and future competitiveness of enterprises, sectors and economies. The author notes the need to introduce a theoretical input, which is manifested by the meta-model. An expression of this treatment is the inclusion of the network as a structure of activities, further knowledge as an activity, and intangible assets as intellectual capital characterized by a structure of connections. The case study presented is an illustration of the use of network analysis tools and other instruments to identify not only the most important resources, tasks or actors, as well as their effectiveness, but also to connect the identified networks with each other. The author opens the field for applying her methodology, revealing the structural and dynamic features of the intangible resources of the organization. The novelty of the proposed meta-model shows the way to in-depth applications of network analysis techniques in an intra-organizational environment. Organizational Network Analysis makes a significant contribution to the development of management sciences, in terms of strategic management and more strictly resource approach to the company through structural definition of knowledge; application of the concept of improvement-oriented audit abandoning a narrow understanding of this technique in terms of compliance; reliable presentation of audits available in the literature; rigorous reasoning leading to the development of a meta-model; close linking of knowledge and resources with the strategy at the design stage of the developed audit model, including the analysis of link dynamics and networks together with an extensive metrics proposal; an interesting illustration of the application with the use of metrics, tables and charts. It will be of value to researchers, academics, managers, and students in the fields of strategic management, organizational studies, social network analysis in management, knowledge management, and auditing knowledge resources in organizations.

Tired of performing an audit manually? This module provides a useful step-by-step approach to perform an audit using ACL. Easy to understand and follow. No such module in the market so far. This module is designed to assist users on how to use ACL as a powerful tool to audit. The module is divided into 8 Chapters. Chapter 1 introduces audit and information technology (IT) audit, audit assertions, audit procedures, and the relationship between audit assertions and audit procedures. Chapter 2 explains ACL in the audit, describing in brief its advantages and disadvantages. Chapter 3 assists users with using ACL. In this chapter, users will learn how to install ACL (version 9), and get familiar with the ACL menus and user interfaces. This module uses a step-by-step approach to guide users from creating a new project from ACL to viewing and modifying the table in ACL. Chapter 4 elaborates how to use ACL commands for data integrity verification. For this purpose, users will learn how to count records, total numeric fields or expression, and check for validity errors. Chapter 5 shows users how to analyse their data using the ACL command. The analyse include statistics, stratify, classify, examine the sequence, check for gaps, check for duplicates, ageing, and summarise commands. The remaining chapters cover three main accounting information systems (AIS) cycles, namely, sales and cash receipts (Chapter 6), purchase and cash payments (Chapter 7), and human resource (Chapter 8). For each cycle, cases are given for better assimilation.