Fraud Analytics for Internal Auditors Certificate
With the rise in synthetic identifies, deep fakes, intelligent bots, and the worldwide increase in scams, internal audit’s ability to participate in the identification, detection, and determent of fraud is critical. A recent FICO blog, went so far as to proclaim we now live in a “Scamdemic.” Today’s internal auditors need to understand the part data analytics play in the fraud arena.
Achieving a certificate in “Fraud Analytics for Internal Auditing” is an excellent way to demonstrate your fraud analytics capabilities. This certificate is designed to ensure all internal auditors have technical expertise to perform their role in fraud identification, detection, deterrence, and investigation. The program assists the internal auditor in gaining a fundamental understanding of fraud and fraud analytics.
Participants who complete the course are eligible to sit for the certificate exam which is administered on The IIA’s LMS platform.
Who will benefit from this program?
This program is for internal auditors who want to gain recognition of their application of data literacy knowledge to fraud risks. Upon completion of the program, participants will be eligible to sit for the assessment in order to earn the certificate.
Certificate Objectives
- Recognize the types of fraudsters, the types of crimes they are likely to commit, and what clues can be revealed through data analytics.
- Recognize fraud data analytics methodologies and how to apply them within the role of the internal auditor.
- Investigate common business processes and external events that could lead to the use of Fraud data analytics including insider threats and cybercrimes.
- Associate descriptive, predictive, and social techniques used in fraud data analytics.
- Identify fraud data analytics opportunities.
Certificate Topics
Fraud Data Analysis Fundamentals
- Fraud data analytics fundamentals.
- How to use the fraud risk statement approach.
- The fraud data analytics methodology.
- The three critical considerations for your fraud data analytics plan.
- The false positive conundrum.
- Axioms and methodologies of fraud data analytics.
Data Mining Strategies
- Four strategies for building a sound data analytics plan.
- How the sophistication for concealment impacts the fraud data analytics plan.
- Understand how strategy impacts the fraud data analytics plan.
- Practical use of pattern and frequency analysis.
- How to identify the critical data elements.
How to Build a Data Mining Plan
- Building a sound fraud data mining and analytics plan.
- Data issues: availability, reliability, and usability.
- Creating a data interrogation plan.
- Common mistakes and misconceptions in building a fraud data mining and analytics plan.
Data Analytics in Planning the Audit
- Defining the scope of the fraud data analytics plan.
- Different ways to use fraud data analytics.
- Key work papers in data mining.
- Creating planning reports.
Data Mining for Shell Companies
- Fundamental attributes of a shell company.
- How to use data to identify shell companies.
- How to build search routines to locate shell companies.
- How to interrogate master file data.
- How to use transactional data.
Data Mining for Fraudulent Disbursements
- Understanding fraudulent disbursements and their cycles.
- False billing schemes.
- Passthrough schemes.
- Vendor overbilling.
- Disguised purchase schemes.
Data Mining for Corruption in Procurement Function
- Identification of bid avoidance and favoritism schemes.
- Retrospective analysis of contracts.
- Targeted expenditure reviews.
- How to gather evidence of corrupted documents versus poor management practices.
Data Mining for Payroll Fraud
- Ghost employee schemes.
- Overtime fraud schemes.
- Payroll adjustments schemes.
- Bonuses and commission schemes.
- Disguised compensation schemes.
- Theft of payroll payments.
Summary Information
NASBA Knowledge Level: Intermediate
NASBA Delivery Method: Group Live, Group Internet Based
NASBA Field of Study: Auditing
Competency Level: Applied Knowledge
Prerequisites: Data Literate with basic understanding of data analytics techniques and fraud from the auditing perspective.
Advance Preparation: None
Topic(s): Data Analytics
Location: The venue will be decided prior to the course date
