eWorkshop: Fundamentals of Data Integrity, Mining, and Analysis for Auditors

8/14/2017 1:00 PM
8/23/2017 3:00 PM
Eastern Time (ET)
3/28/2017 12:00 AM

Registration will close 24 hours prior to the beginning of the webinar start time listed.

Session 1: August 14, 2017 (1:00–3:00 p.m. EST)

Session 2: August 16, 2017 (1:00–3:00 p.m. EST)

Session 3: August 21, 2017 (1:00–3:00 p.m. EST)

Session 4: August 23, 2017 (1:00–3:00 p.m. EST)

GIGO. We’ve heard it for decades. But limited time and resources often force us to start the audit without really knowing if our data source is garbage or good-to-go. Sometimes the effect is just lingering doubt. At other times, such doubts become tangible in terms of poor analysis, costly rework, and blown schedules.  

Besides covering the legal and professional standards for data integrity in auditing, this course demonstrates, exemplifies, and provides field-ready tools for quickly and thoroughly determining and documenting the results of fundamental and often standards-required data integrity tests.

We also give you “load-and-go” automated data mining tools for assessing the normality of, summarizing, describing, graphing, and comparing quantitative data sets.  Finally, we explore the relationship between what good, well-mined data looks like and the amount of work required to service different types of audit objectives, especially compliance, control, fiscal risk, and monetary misstatement.

The key characteristics of this course are:

  1. Sessions focus on the standards and basic methods and tools that auditors, investigators, and evaluators actually use to ensure the integrity of, describe, and display data. There is little theoretical content.
  2. Instruction includes numerous real-world audit examples of the most common data integrity errors, along with computer applications to detect them.
  3. The instructor combines automation, statistical theory, evaluation methodology, and applied statistics into a single, easy-to-understand curriculum.

NOTE: A practice data set will be made available for participants who wish to "follow along." Those choosing to do so must a licensed version of Microsoft Excel loaded on their computers. Excel MUST have its Data Analysis ToolPak installed and ready to use. Procedures for doing this and for other course-related, step-by-step processes will be made available one week prior to class start.

Learning Objectives

This course teaches participants how to:​​​​

  • Integrate audit standards, data integrity, data analysis methods, and audit objectives.
  • Find and correct common data integrity errors.
  • Distinguish variable types and identify their most appropriate analytical metrics.
  • Derive, construct, interpret, and use descriptive statistics and graphs.
  • Mine data using norms, trends, relationships, filters, formulas, and comparative metrics.
  • Quantify and control outliers and data abnormality and how they affect sampling.
  • Use probability and data distribution to detect possible fraud, waste, and abuse.
  • Establish the advantages and limitations of basic statistical and graphic analytic techniques and identify means to ensure that data analysis stays within such limitations.
  • Explore how the output of data integrity and data mining affect the scope of audit sampling and testing.​

Presenter/Facilitator

Bruce Truitt has more than 25 years of experience in the design and delivery of applied statistics and auditing curricula, consultations, methodologies, and tools in local, state, national, and international settings. His areas of expertise include sampling, data analysis, statistical process control, performance measurement, quantitative risk assessment, and empirical and comparative analyses of the efficiency and effectiveness of organizational culture and development. Truitt has worked more than 15 years in government auditing, focused on health and human services, with emphasis on fraud, waste, and abuse. He served on the Medicaid Fraud and the Medicaid Payment Error Rate Measurement Joint Federal-State Technical Advisory Groups, a combined effort of four high-powered organizations.

Truitt is a former professor of quantitative methods in Saint Edward's University's Graduate School of Business and presently teaches "Practical Statistical Sampling for Auditors," an online course for the United States Government Auditor's Training Institute. He also serves as an instructor for the United States Department of Justice Medicaid Integrity Institute at the University of South Carolina. Truitt served as guest lecturer in Management and Auditing at the Kiev (Ukraine) School of Management and received the 2004 National State Auditors Association Award for Excellence in Accountability. He also developed the SAO Statistical Tool Box, a sampling, testing, analysis, and reporting tool used by thousands of public and private entities in all 50 states and 33 foreign countries.

Pricing

Register by Aug. 13 to save 20%. Use Promo Code ACGA20AUG.

ACGA Member: $249
Public: $299​

Event Information

Course Duration: 4 days
CPE Hours: 8
Knowledge Level: Intermediate
Field of Study: Auditing
Prerequisites:

​None

Advance Preparation:

​None

Delivery Method: Group Internet based
eWorkshop

The IIA is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.NASBARegistry.org.