Together, Reducing Fraud Worldwide

Using Data Analytics to Detect Fraud


Share |

  CPE Credit: 16
Course Level: Basic
Prerequisite: None


 

According to the ACFE's 2014 Report to the Nations on Occupational Fraud and Abuse, proactive data monitoring and analysis is among the most effective anti-fraud controls. Organizations who undertake proactive data analysis techniques experience frauds that are 60% less costly and 50% shorter than organizations who do not monitor and analyze data for signs of fraud.

Using Data Analytics to Detect Fraud will introduce you to the basic techniques of uncovering fraud through data analysis. Taking a software-independent approach, this two-day course provides numerous data analytics tests that can be used 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. 

 

Upcoming Courses   

Las Vegas, NV | December 18-19, 2014   

Melbourne, Australia | April 9-10, 2015   

Frankfurt, Germany | April 20-21, 2015   

New York, NY | May 6-7, 2015 
 

You Will Learn How To:  

Recognize the types of data and available tools that can be used to look for signs of fraud

Implement the full data analytics process from determining which data to acquire to evaluating the results

Apply numerous fundamental, advanced and non-traditional data analysis techniques

Analyze non-numeric data, such as text and timelines, for signs of fraud

Identify anomalies and recognize common red flags of fraud that appear in the data

Use data analytics tests to detect various asset misappropriation, corruption and financial statement fraud schemes


Who Should Attend:  

Controllers and corporate managers

Forensic and management accountants, accounts payable and financial analysts

Internal and external auditors, CPAs and CAs

IT professionals

Certified Fraud Examiners and other anti-fraud professionals 

Fees* 

Members: $695
Non-Members: $845

 

CPE Credit 

16

 

Field of Study
Auditing 

 

Course Level
Basic 

 

Prerequisite
None 


Advanced Preparation 

None

  

Delivery Method 

Group-Live

 

*Pricing listed is for U.S. events. International event pricing may vary by location. Please view the individual event page for International pricing. 

*Please note: Schedule listed is for U.S. events. All events outside of the U.S. are pushed back 30 minutes with registration beginning at 8:00 a.m. and the last session ending at 4:55 p.m. 

 

  Day One  
7:30-8:00 a.m.   Registration & Continental Breakfast   
8:00-9:20 a.m. 

Introduction to Data Analytics 

This session will introduce participants to the uses, benefits, and challenges of data analytics techniques. Participants will also learn about the types of data that can be analyzed and will discuss some software options for performing data analysis tests.

9:20-9:35 a.m.  Break 
9:35-10:55 a.m. 

The Data Analysis Process 

The results of any data analysis technique are only as good as the underlying data that is examined. Participants will learn how to formulate an overarching methodology for building a data analytics program—from data identification and acquisition through reporting the analysis results—and how to tie the process to the organization’s fraud risk assessment to most effectively detect fraud.

10:55-11:10 a.m.  Break  
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.

12:30-1:30 p.m.  Group Lunch  
1:30-2:50 p.m. 

Advanced 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.

2:50-3:05 p.m.  Break  
3:05-4:25 p.m.  

Other Data Analysis Techniques 

In this session, participants will learn about non-traditional data analysis tests that identify the red flags of fraud, such as textual, visual, and timeline analytics. They will also discuss methods for ranking particular transactions and individuals based on a composite of red flags identified through data analysis techniques.

 

 

  Day Two  
7:30-8:00 a.m.   Registration & Continental Breakfast   
8:00-9:20 a.m. 

Data Analysis Tests for Detecting Billing and Check Tampering Schemes 

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.

9:20-9:35 a.m.  Break 
9:35-10:55 a.m. 

Data Analysis Tests for Detecting Payroll and Expense Reimbursement Schemes 

This session highlights data analysis techniques that participants can use to uncover particular fraud schemes within the payroll and expense reimbursement 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.

10:55-11:10 a.m.  Break  
11:10 a.m.-12:30 p.m. 

Data Analysis Tests for Detecting Theft of Cash Receipts and Inventory 

This session explores specific data tests that participants can use to spot red flags of the theft of incoming cash receipts and of inventory in 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.

12:30-1:30 p.m.  Group Lunch  
1:30-2:50 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.

2:50-3:05 p.m.  Break  
3:05-4:25 p.m.  

Data Analysis Tests 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.

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.

 

Satisfaction Guarantee 

ACFE seminars 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.

 

NASBA CPEThe 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.learningmarket.org 
 

 

If you would like to begin receiving email notifications from the ACFE, please click here to subscribe.



Reviews
We welcome your reviews and feedback on ACFE Events, Training & Products. If you have questions or need assistance, please contact an ACFE Member Services Representative.

 

  You must be logged in to leave a review....

0 Comments

Add Comment

Text Only 2000 character limit

Page 1 of 1

Related Information

Calendar of Events