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 Forensic Auditing Anticorruption A1600 QR Code
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Forensic Auditing - Anticorruption



This forensic auditing training course is for those who want to learn about one of the most important and fastest-growing industries in the world: fraud. Last year, this mostly invisible and poorly understood danger cost the global economy more than $4 trillion (according to the Association of Certified Fraud Examiners)

This training course will focus on how to establish an effective fraud detection strategy using case studies and the trainer's extensive experience. This session will demonstrate fraud detection methods and strategies, including the use of big data and data analytics.

Course Objectives:

At the end of this course the participants will be able to:

  • Think like a fraudster – the only way to detect complex frauds
  • Understand the techniques of data mining as a fraud detection tool
  • Appreciate the key aspects of fraud profiling
  • Use continuous auditing and continuous monitoring to uncover unusual patterns
  • Understand when it seems ‘too good to be true it usually will be

Targeted Audience:

  • Internal auditors in organizations without a dedicated fraud team, as they are having to take a much more significant role in the detection and investigation of fraud
  • Audit Managers and Lead Auditors who need to learn about the most modern approaches to fraud detection
  • Fraud specialists who need more appreciation of how to detect fraud
  • Certified Fraud Examiners
  • Accountants who need an understanding of forensics
  • Managers needing a broader understanding of how to prevent and detect fraud

Course Outlines:

Unit 1: Anatomy of Fraud

  • The power of Fraud Profiling
  • Who are the fraudsters – internal and external
  • ACFE fraud survey results
  • Identity fraud
  • Corruption – the most difficult fraud to detect
  • 15 case studies and the key lessons 

Unit 2: The Key Fraud Indicators

  • Why controls may not protect you
  • Putting yourself in the mind of the fraudster
  • The 50 key indicators – and how to use them
  • Developing a forensic audit toolkit
  • The need for a cost-effective balance between prevention and detection
  • Identifying vulnerabilities

Unit 3: Data Mining – The Key Forensic Tool

  • Use of Computer-assisted audit techniques (CAAT’s)
  • Data mining techniques
  • Fraud risk prioritization
  • Benford’s law
  • Use on Monte Carlo simulations and Markov chains
  • Forensic auditing of big data

Unit 4: Forensic Techniques

  • Automated fraud detection
  • The control weakness and the key field approaches
  • The association rules in fraud detection
  • Use of fuzzy logic
  • Neural networks
  • Data visualization and pattern recognition

Unit 5: Using the Information Identified

  • What to do when potential fraud is detected
  • The legal aspects of the use of forensic data
  • Using external and internal databases
  • Integrating the information/ identifiers in audits – to avoid bringing attention
  • Reporting the results
  • When to inform external bodies

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