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Statistical Techniques for Forensic Accounting Understanding the Theory and Application of Data Analysis

ISBN-10: 0133133818

ISBN-13: 9780133133813

Edition: 2013

Authors: Saurav K. Dutta

List price: $89.99
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Master powerful statistical techniques for uncovering fraud or misrepresentation in complex financial data.The discipline of statistics has developed sophisticated, well-accepted approaches for identifying financial fraud and demonstrating that it is deliberate.Statistical Techniques for Forensic Accountingis the first comprehensive guide to these tools and techniques. Leading expert Dr. Saurav Dutta explains their mathematical underpinnings, shows how to use them properly, and guides you in communicating your findings to other interested and knowledgeable parties, or assessing others' analyses. Dutta is singularly well-qualified to write this book: he has been engaged as an expert in many of the world's highest-profile financial fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Here, he covers everything professionals need to know to construct and conduct valid and defensible statistical tests, perform analyses, and interpret others' analyses. Coverage includes: exploratory data analysis to identify the "Fraud Triangle" and other red flags… data mining tools, usage, and limitations… statistical terms and methods applicable to forensic accounting… relevant uncertainty and probability concepts… Bayesian analysis and networks… statistical inference, sampling, sample size, estimation, regression, correlation, classification, prediction, and much more.For all forensic accountants, auditors, investigators, and litigators involved with corporate financial reporting; and for all students interested in forensic accounting and related fields.
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Book details

List price: $89.99
Copyright year: 2013
Publisher: FT Press
Publication date: 6/18/2013
Binding: Hardcover
Pages: 288
Size: 7.50" wide x 9.50" long x 1.00" tall
Weight: 1.364

Introduction: The Challenges in Forensic Accounting
Characteristics and Types of Fraud
Management Fraud Schemes
Employee Fraud Schemes
Chapter Summary
Legislation, Regulation, and Guidance Impacting Forensic Accounting
U.S. Legislative Response to Fraudulent Financial Reporting.
The Emphasis on Prosecution of Fraud at the Department of Justice
The Role of the FBI in Detecting Corporate Fraud
Professional Guidance in SAS 99
Chapter Summary
Preventive Measures: Corporate Governance and Internal Controls
Corporate Governance Issues in Developed Economies
Emerging Economies and Their Unique Corporate Governance Issues
Organizational Controls
A System of Internal Controls
The COSO Framework on Internal Controls
Benefits, Costs, and Limitations of Internal Controls
Incorporation of Fraud Risk in the Design of Internal Controls
Legislation on Internal Controls
Chapter Summary
Detection of Fraud: Shared Responsibility
Expectations Gap in the Accounting Profession
Responsibility of the External Auditor
Responsibility of the Board of Directors
Role of the Audit Committee
Managements Role and Responsibilities in the Financial Reporting Process
The Role of the Internal Auditor
Who Blows the Whistle
Chapter Summary
Data Mining.
Data Classification
Association Analysis
Cluster Analysis
Outlier Analysis
Data Mining to Detect Money Laundering
Chapter Summary
Transitioning to Evidence
Probability Concepts and Terminology
Schematic Representation of Evidence
Information and Evidence
Mathematical Definitions of Prior, Conditional, and Posterior Probability
The Probative Value of Evidence
Bayes� Rule
Chapter Summary
Discrete Probability Distributions
Generic Definitions and Notations
The Binomial Distribution
Poisson Probability Distribution
Hypergeometric Distribution
Chapter Summary
Continuous Probability Distributions
Conceptual Development of Probability Framework
Uniform Probability Distribution
Normal Probability Distribution
Testing for Normality
Chebycheff's Inequality
Binomial Distribution Expressed as a Normal Distribution
The Exponential Distribution
Joint Distribution of Continuous Random Variables
Chapter Summary
Sampling Theory and Techniques
Motivation for Sampling
Theory Behind Sampling
Statistical Sampling Techniques
Nonstatistical Sampling Techniques
Sampling Approaches in Auditing
Chapter Summary
Statistical Inference from Sample Information
The Ability to Generalize Sample Data to Population Parameters
Central Limit Theorem and non-Normal Distributions
Estimation of Population Parameter
Confidence Intervals
Confidence Interval for a Large Sample When Population Standard Deviation Is Known
Confidence Interval for a Large Sample When Population Standard Deviation Is Unknown
Confidence Intervals for Small Samples
Confidence Intervals for Proportions
Chapter Summary
Determining Sample Size
Computing Sample Size When Population Deviation Is Known
Sample Size Estimation when Population Deviation Is Unknown
Sample Size Estimation for Proportions
Chapter Summary
Regression and Correlation
Probabilistic Linear Models
Least Squares Regression
Coefficient of Determination
Test of Significance and p-Values
Prediction Using Regression
Caveats and Limitations of Regression Models
Other Regression Models
Chapter Summary