In-Person Seminar

Detecting Fraud with Data Analytics Workshop

  • Nov 13-15, 2024
  • Phoenix, AZ
Course Level
Delivered via


According to the ACFE's Occupational Fraud 2024: A Report to the Nations, proactive data monitoring and analysis is among the most effective anti-fraud controls. Organizations that undertake proactive data analysis techniques experience frauds that are 50% less costly and detect frauds 2 times as quickly as organizations that do not monitor and analyze data for signs of fraud. 

The Detecting Fraud with Data Analytics Workshop will teach you how to plan, design, and apply numerous data analytics tests in order to detect various fraud schemes. You will also discover how to examine and interpret the results of those tests to identify the red flags of fraud.

You will have the opportunity to use new knowledge of analytical tests, data sources and fraud schemes while applying data analysis techniques to real datasets and scenarios. Bring your own laptop and the software you are most comfortable with,* and practice using data analytics to uncover the red flags of fraud. You will work through cases covering a variety of fraud schemes, including purchasing fraud, payroll manipulation and financial statement fraud.

*Practical exercises can be conducted in Microsoft Excel, ACL, IDEA or Tableau. To participate in this workshop, you will need to bring one or more of these software programs fully installed and ready to use on your own laptop. Technical support for installing and running these programs will NOT be provided.


Working knowledge of basic functions in one or more of the following software programs: Microsoft Excel, Galvanize, IDEA, Tableau, PowerBI

You Will Learn How To:

Determine the use of data analytics in detecting fraud.

Navigate the full data analytics process, from collecting data to communicating results.

Recognize fundamental and advanced analytical functions and their applications in the data analytics process.

Analyze non-numeric data, such as emails and social media posts.

Identify red flags of financial statement fraud.

Apply data analytics tests to detect numerous fraud schemes.

Location & Venue

Event Venue

Hyatt Place Phoenix / Downtown
150 W. Adams Street, Phoenix, AZ 85003

Hotel Information

Hotel Phone: 602-388-4888
Room Rate: $229 single/double
Hotel Cut-Off: October 13, 2024

*To make a reservation, please contact the hotel directly or click here.

CPE Information

CPE Credit: 24
Advanced Preparation: None
Delivery Method: Group-Live

Credit by Field of Study

Auditing: 24

Registration & Fees

Registration Fee:
Members: $1269
Non-Members: $1569
Early Registration Deadline: October 14, 2024
Register by the Early Registration Deadline to SAVE $150!

Course Outline

Day 1

  • 8:00 – 9:20 a.m. Introduction to Data Analytics and the Data Analysis Process

    This session will introduce participants to the uses, benefits, and challenges of data analytics techniques, as well as the types of data that can be analyzed and some software options for performing data analysis tests. Participants will also learn how to formulate and apply an overarching methodology for building a data analytics program and how to tie the process to the organization’s fraud risk assessment to most effectively detect fraud.

  • 9:35 – 10:55 a.m. Prepping, Normalizing, and Harmonizing Data

    The results of any data analysis technique are only as good as the underlying data that is examined. One of the most important steps—and often one of the biggest challenges—in data analytics initiatives involves preparing and normalizing the data for analysis. In this session, participants will explore common issues and effective solutions for ensuring the data they have obtained is properly prepared, normalized and harmonized before they begin their testing.

  • 11:10 a.m. – 12:30 p.m. Fundamental Data Analysis Techniques

    In this session, participants will discuss many of the most common data analysis techniques—such as duplicate testing, matching, gap testing, and compliance verification—that can be used to comb through the data and identify anomalies and red flags of fraud.

  • 1:30 – 2:50 p.m. Other Data Analysis Techniques

    There are numerous sophisticated analysis techniques that can be particularly useful in analyzing datasets for symptoms of fraud. This session includes discussions of Benford’s Law analysis, regression analysis, reasonableness testing, and several other tools that data analysts can use to take their fraud detection efforts to the next level. Participants will also earn about non-traditional data analysis tests that identify the red flags of fraud, such as textual, visual, and timeline analytics, as well as transactional risk-ranking techniques.

  • 3:05 – 4:25 p.m. Effectively Communicating the Results of the Data Analytics

    Once the data has been analyzed and conclusions drawn, the fraud examiner often must convey what has been learned. However, effectively communicating those results can be a challenge for many examiners, both experienced and novice. This session will discuss how to effectively communicate the results of data analytics to both internal and external audiences.

Day 2

  • 11:10 a.m. – 12:30 p.m. Data Analysis Test for Detecting Financial Statement Fraud

    This session focuses on targeted data analysis tests to identify various financial statement fraud schemes. By using these techniques to analyze the financial statements, the related disclosures, and the underlying data, fraud examiners can identify anomalies and uncover financial statement manipulation. Attendees will then apply these techniques to data to assess whether and how an organization’s reported financial results have been manipulated.

Day 3

  • 8:00 – 9:20 a.m. Data Analysis Tests for Detecting Payroll Schemes

    This session highlights data analysis techniques that participants can use to uncover particular fraud schemes within the payroll function of their organizations. Using discussion scenarios to walk through data analytics techniques, participants will learn to identify red flags of these types of fraud that appear in the data.

  • 11:10 a.m. – 12:30 p.m. Data Analysis Tests for Detecting Corruption

    Corruption schemes can be particularly difficult to detect, as so many clues for these schemes fall outside the company’s financial records—and thus outside the traditional realm of data analytics. This session provides participants with numerous techniques that can be used to analyze the structured and unstructured data in which warning signs of corruption schemes are often found.

  • 1:30 – 2:50 p.m. Data Analysis Tests for Detecting Expense Reimbursement and P-Card Schemes

    This session focuses on data analysis techniques that participants can use to uncover particular fraud schemes within the expense reimbursement and purchasing card (or p-card) functions of their organizations. Using discussion scenarios to walk through data analytics techniques, participants will learn to identify red flags of these types of fraud that appear in the data.


Bethmara Kessler, CFE - Speaker

Bethmara Kessler Headshot



Payment must be received by October 14, 2024 to receive early registration discount. 

Event Cancellation Policy

Our cancellation policy is intended to keep costs low for attendees. Due to financial obligations incurred by ACFE, Inc., you must cancel your registration prior to the start of the event. Cancellations received less than 14 calendar days prior to an event start date are subject to a $100 administrative fee. No refunds or credits will be given for cancellations received on or after the start date of the event. Those who do not cancel and do not attend are responsible for the full registration fee. Should an event be cancelled or postponed by the ACFE due to unforeseen circumstances, the ACFE will process a full refund of registration fees within 30 days of such circumstances becoming known. The ACFE will attempt to notify affected customers by phone and email after it determines cancellation is necessary.

Satisfaction Guarantee

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Terms and Conditions


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