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Detecting Fraud Using Data Analysis (OFFERED VIRTUALLY)

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Date(s): Aug 18, 2020 - Aug 19, 2020
Time: 8:15AM - 12:00PM
Registration Fee: $229.00
Cancellation Date: Aug 12, 2020
Location: Online

Course Description



Massive data sets within the organization’s systems can hide symptoms of fraud and waste from auditors and control personnel. This tactical session delves into specific methods for auditors, investigators, and finance professionals to highlight symptoms of problems across all organization processes. Learn how to apply data analysis skills to effectively test one hundred percent of a transaction population and achieve a positive return-on-investment for your organization.


This workshop is not about what buttons to click; it is about strategies employed through the use of data analysis. The workshop is software-neutral, meaning participants will benefit whether they use IDEA, ACL, SQL queries, or simply Excel and Access. The instructor will demonstrate techniques that can be handled by all of the programs.

Potential CPE Credits: 8.0
Govt Hours: This class meets 8.0 hours of the 24-hour requirement for governmental CPE under Government Auditing Standards (yellow book), in most cases.
Technical Hours: This class meets 8.0 CPE credits of technical training in compliance with Texas Admin. Code Rule 523.102.

Instruction Type: Live
Experience Level: BEGINNING
Category: 02 Auditing

Course Objectives

Upon completion of this course, participants will be able to:

  • Overcome mindsets that prevent us from properly addressing fraud.
  • Apply a consistent methodology for fraud detection.
  • Employ data analysis techniques used to successfully detect fraud.
  • Blend traditional methods of auditing with data analysis techniques.
  • Incorporate data analysis techniques into routine daily activities to improve detective controls.
  • Avoid common pitfalls related to data analysis.
  • Apply data analysis to audits of process areas common to all organizations.
  • Use data analysis to test 100% of a population instead of a sample.
  • Apply lessons from case studies to your own unique environment.


Preparing to Detect Fraud

Overcoming beliefs that hinder our ability to achieve results

How much fraud is out there?

Our role in fraud detection

Evaluating your environment

Assessing Fraud Policy

Importance of early detection

A method for fraud detection

Data analysis in perspective


Fundamental Data Analysis Techniques

Importing preferences

Using control totals to detect manipulation of reconciliations and spreadsheets

Sorting data to highlight key missing fields, stale transactions, odd dates, and unusually large/small items

Detecting anomalies through statistical analysis

Effective use of extractions, using logic operators to highlight odd transactions

How to spot patterns with summarizations and pivot tables

Application of fundamental techniques to case studies


Beyond Fundamentals

Traps to avoid

Searching for descriptors symptomatic of earnings management, fictitious payments, and corruption

Effective uses of field manipulation

Duplicate key detection & exclusion

Date stratification to detect spikes in activity around a period end, symptomatic of earnings management

Numeric stratification and the circumvention of approval authority

Joining databases to detect false vendors, ghosts on the payroll, and revenue loss

Time block comparisons to detect escalating activity symptomatic of false vendors, cash misappropriation, and ‘black hole’ accounts

Benford's Law and its application

Where to look for problems in your environment

What can go wrong and common symptoms of fraud

Putting it all together into a plan



No prerequisites required.

[GAGAS, 4.23(p)]

Participants will need an internet connection, computer/tablet, speakers and microphone to participate in the course.


Scott Langlinais

Scott Langlinais delivers training seminars worldwide on properly addressing fraud, waste and abuse.  He has worked with leaders of Fortune 500 companies, top public accounting firms, and government entities to design and implement strategies for establishing an environment hostile to fraud.  On a tactical level he teaches concepts such as data analysis techniques and a five-step approach to fraud detection that finance professionals, auditors, and investigators have used to successfully prevent, detect and respond to wrongdoing.

Scott is affiliated with Courtenay Thompson & Associates for the purpose of developing and providing training on fraud-related topics.  He is the developer and instructor of Using Data Analysis to Detect Fraud & Error, Detecting Fraud Using IDEA, and Fraud Risk Workshop.  He speaks at conferences hosted by the Institute of Internal Auditors, the American Institute of Certified Public Accountants and the Association of Certified Fraud Examiners.  The International Risk Management Institute has published several of his articles in relation to fraud prevention and response.

Prior to starting his own practice in 2003, Mr. Langlinais held public accounting and internal audit leadership positions, most recently serving as Director of Internal Audit and Security for a NASDAQ 100 software company.  His investigations of fraud and gross negligence have resulted in removal of perpetrators, successful litigation, and recovery of millions of dollars.

Mr. Langlinais has served as the Founder and Director of the Dallas Tax Assistance Program, a not-for-profit organization that assists low-income families with federal tax return preparation.  He received a BBA degree from the University of Notre Dame and is a Certified Public Accountant.

Additional Information

TAC Rule 523.142(g) requires the CPE Sponsor to monitor individual attendance and assign the correct number of CPE credits. Participants will be asked to document their time of arrival and departure in compliance with this Rule. Additionally, attendance will be monitored throughout the day and CPE certificates will reflect actual attendance of each participant.

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