Based on the continuing success of STAR, the computer-based auditing system first pioneered by Deloitte & Touche LLP almost 25 years ago, Statistical Techniques for Analytical Review in Auditing, Second Edition builds on its original text to provide a comprehensive, up-to-date, and practical guide to using this highly effective and efficient system for planning, performing, and evaluating analytical procedures. The first edition of this unrivaled work was published in 1986, following 15 years and thousands of effective applications of the STAR Program worldwide. This Second Edition has been thoroughly updated to reflect the changes required by SAS 56, and features additional practical examples and all new graphics and printouts. Without using complicated mathematics, the authors take the reader through the understanding and implementation of STAR in four stages: Beginning with a description of the audit philosophy behind its success, they provide an overview of STAR's role in analytical procedures. They then cover the basic statistical concepts of regression analysis and other statistical techniques utilized by STAR. The authors then explain the practical aspects of designing and improving STAR models and of interpreting and evaluating their results. Finally, they describe in detail the statistical tests and transformations performed by STAR and explain the mathematics behind multivariate regression. Pertinent examples are used throughout to illustrate both theory and practice. The only text currently available on this successful and widely used auditing program, Statistical Techniques for Analytical Review in Auditing, Second Edition is designed to be an invaluable resource for external as well as internal auditors involved in business, government, and nonprofit organizations. A new and updated edition of a classic text for the auditing professional STAR, the premier computer-based auditing system for performing statistical procedures, has been successfully implemented in thousands of worldwide audits. Developed by Deloitte & Touche LLP, STAR is designed to integrate statistical modeling techniques and professional judgments in a manner that is optimized for auditors. Statistical Techniques for Analytical Review in Auditing was written to explain the concepts and techniques implemented through STAR and to encourage their use by other auditors. In this new and thoroughly updated Second Edition, the authors continue to provide the audit marketplace with an important and far-reaching resource. Written from the perspective of the practitioner, Statistical Techniques for Analytical Review in Auditing, Second Edition features: An overview of the auditing environment and the role of analytical procedures Intuitively appealing, nontechnical coverage of regression analysis and other statistical techniques used in STAR Practical guidance on building and evaluating STAR applications Details of mathematical and computational technology in STAR Many practice-based examples

The technique enables the independent auditor to integrate the concepts of materiality and audit risk as set out in SAS 47 and permits effective use of sophisticated techniques without requiring a mathematics background. It is easy-to-use, includes extra math and graphics functions and can be interfaced with the Lotus 1-2-3.

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. 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. Using R and RStudio, the book 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.

Based on the International Auditing Standards (IAS) established by the International Federation of Accountants (IFAC), this text presents a step-by-step chapter format on how to perform an audit.

Fraud or misrepresentation often creates patterns of error within complex financial data. The discipline of statistics has developed sophisticated techniques and well-accepted tools for uncovering these patterns and demonstrating that they are the result of deliberate malfeasance. Statistical Techniques for Forensic Accounting is the first comprehensive guide to these tools and techniques: understanding their mathematical underpinnings, using them properly, and effectively communicating findings to non-experts. Dr. Saurav Dutta, one of the field's leading experts, has been engaged as an expert in many of the world's highest-profile fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Now, he covers everything forensic accountants, auditors, investigators, and litigators need to know to use these tools and interpret others' use of them. Coverage includes: Exploratory data analysis: identifying the "Fraud Triangle" and other red flags Data mining: tools, usage, and limitations Traditional statistical terms and methods applicable to forensic accounting Uncertainty and probability theories and their forensic implications Bayesian analysis and networks Statistical inference, sampling, sample size, estimation, regression, correlation, classification, and prediction How to construct and conduct valid and defensible statistical tests How to articulate and effectively communicate findings to other interested and knowledgeable parties

Discover how to detect fraud, biases, or errors in your data using Access or Excel With over 300 images, Forensic Analytics reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related. Demonstrates how to use Access, Excel, and PowerPoint in a forensic setting Explores use of statistical techniques such as Benford's Law, descriptive statistics, correlation, and time-series analysis to detect fraud and errors Discusses the detection of financial statement fraud using various statistical approaches Explains how to score locations, agents, customers, or employees for fraud risk Shows you how to become the data analytics expert in your organization Forensic Analytics shows how you can use Microsoft Access and Excel as your primary data interrogation tools to find exceptional, irregular, and anomalous records.