Course Description
If robust data analytics programs had been the norm twenty years ago, would Enron, WorldCom or the countless other major corporate fraud scandals have every reached the magnitude they did? Or even have occurred at all? All organizations are subject to fraud risk. ACFE studies show that on average 5% of revenue is lost to internal fraud schemes within an organization…every year. Utilizing effective data analytics as part of an organization’s fraud management program can reduce the average fraud scheme’s duration from 18 months down to mere weeks, or almost eliminate it. More importantly a robust fraud data analytics program can be the strongest deterrent in an organization.
This course is designed to introduce the participants to the techniques currently being used by leading data analytics programs through the use of case studies, best practices and interactive exercises. Participants will gain a basic understand of fraud and how it occurs in organizations and the specific techniques used to identify and quantify fraud.
Learning Objectives
- Understand how data analytics can be used in a fraud management program
- Understand Fraud basics and assessing fraud risk
- Learn techniques for detecting and preventing fraud in your organization
- Understand professional standards regarding the use of data analytics in fraud management
- Learn how to start a fraud data analytics program
Course Outline
Understanding Fraud
- The Fraud Triangle
- ACFE 2018 Report to the Nation – Fraud Trends
- Fraudsters – characteristics and behaviors
- Fraud Schemes and Scenarios
- Management override
- Corruption
- Financial Statement
- Asset Misappropriation
Principals for Fighting Fraud in an Organization
- Governance
- Fraud Risk Assessment
- Prevention
- Detection
- Reporting
Using Data Analytics for Fraud Management
- Detection
- Using Analytics in Detection of Fraud
- Fraud Focused Continuous Auditing and Monitoring
- Fraud Investigations
- Prevention
- Deterrence
New IIA and ISACA Fraud-Detection Standards
- IIA GTAG #13 and GTAG #16
- ISACA “Data Analytics: A Practical Approach”
- Survey results on data analytics for fraud among auditors
Getting Started with Data Analytics/CAATs
- Data Analytics Terminology
- Continuous Auditing vs. Continuous Monitoring
- CAAT’s vs Data Analytics
- Big Data
Fundamental Data Analysis Techniques
- Duplicates
- Matching
- “Like” attributes and transitions
- Gap Testing
- Compliance testing & verification
- Red Flag attributes
Understanding Trends and Patterns in Data
- How to spot them
- Understanding what the data is telling you
- Red Flags versus changes in the business
Specific Data Analytics techniques for:
- Fraudulent disbursements
- Payroll/li>
- Cash
- Inventory and fixed asset theft
- Corruption
- Financial statement over and under misstatement
Additional Information
Who Should Attend
- Internal and external auditors
- Internal control professionals
Learning Level
Intermediate
Delivery
Group Live or Group Internet-Based
Field
Auditing
Advanced Preparation
None
Recommended Prerequisites
General understanding of fraud schemes, fraud auditing techniques and computer-based auditing.
Session Duration
On Site: 2 days
CPE Credits: 16