Detecting Fraud with Data Analytics Workshop
- Feb 26-27, 2025 9:00 a.m.
- Central Time (CT)
According to the ACFE’s Occupational Fraud 2024: A Report to the Nations, proactive data monitoring and analysis are 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 Virtual Workshop will teach you how to plan, design and apply numerous data analytics tests and examine and interpret the results of those tests to identify the red flags of various fraud schemes.
Working knowledge of basic functions in one or more of the following software programs: Microsoft Excel, Galvanize, IDEA, Tableau, PowerBI.
Provide a solid foundation on which to build data analytics initiatives.
Understand the types of tests that can be used.
Tie tests to the fraud risk assessments.
Properly prepare and normalize data for testing.
Effectively communicate the results of the analysis.
CPE Credit: | 12 |
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Advanced Preparation: | None |
Delivery Method: | Group Internet Based |
Auditing: | 12 |
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Registration Fee:
ACFE Members: $779
Non-Members: $879
Early Registration Deadline: January 27, 2025
Register by the Early Registration Deadline to SAVE $125!
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.
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.
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.
Lunch Break
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.
This session explores specific data tests that participants can use to spot red flags of fraud in the customer sales cycle in their organizations. Participants will learn to identify red flags of theft of inventory and incoming cash receipts that appear in the data. In addition, attendees will apply the discussed data analytics techniques to a case study involving cash receipts 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.
This session explores specific tests that participants can use to uncover fraud schemes within the accounts payable and cash disbursements 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. In addition, attendees will apply the data analytics techniques by working on a hands-on case study involving billing fraud.
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.
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. Attendees will then apply the data analytics techniques by working on a hands-on case study involving payroll fraud.
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. In addition, attendees will work on a hands-on case study involving payroll fraud.
Lunch Break
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.
Bringing together all of the concepts discussed previously in this course, this session will explore the intersection of data analytics and ethics. What ethical considerations should anti-fraud professionals keep in mind with obtaining and analyzing data in order to detect fraud? How should the present their findings to ensure they are interpreted and used in an ethical manner?
Speaker/Advisor
Payment must be received by January 27, 2025 to receive early registration discount.
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 30 calendar days prior to an event start date are subject to a $300 administrative fee. Event transfers received less than 30 calendar days prior to an event start date are subject to a $100 transfer 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. For more information regarding refunds or other concerns, please contact Member Services at (800) 245-3321 / +1 (512) 478-9000.
ACFE events are unmatched in scope and effectiveness and backed by our unconditional satisfaction guarantee. If you attend an ACFE event and are not completely satisfied, please contact an ACFE Member Services Representative at MemberServices@ACFE.com or call (800) 245-3321 / +1 (512) 478-9000.
Terms and Conditions
The Association of Certified Fraud Examiners, Inc. 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.