Why Choose Forensic Accounting and Fraud Control Training Course?

Forensic accounting and fraud control is one of the most technically demanding disciplines in audit and finance — and this course gives professionals the structured knowledge and applied toolkit to detect, investigate, and respond to fraud with confidence.

The course covers the full forensic accounting scope: fraud profiling, internal and external fraudster behaviour, identity fraud, corruption detection, and 15 real case studies with key lessons drawn from actual fraud scenarios.

Fraud indicators are addressed in depth, covering 50 key fraud indicators, vulnerability identification, forensic audit toolkit development, and the balance between prevention and detection in a cost-effective control environment.

Data mining is treated as the primary forensic tool, covering CAATs, Benford's Law, Monte Carlo simulations, Markov chains, and forensic auditing of big data alongside advanced techniques including neural networks, fuzzy logic, and association rules.

The course closes with the legal aspects of forensic data, investigation reporting, database integration, and the protocols for informing external bodies — giving delegates a complete end-to-end forensic capability.

What are the Goals?

This forensic accounting and fraud control course is designed to give delegates a working command of fraud detection, forensic investigation techniques, data analytics, and the legal and reporting frameworks that govern how forensic findings are handled and communicated.

By the end of this course, delegates will be able to:

  • Apply fraud profiling techniques: Identify the characteristics and behaviour patterns of internal and external fraudsters using established profiling frameworks.
  • Use key fraud indicators: Apply the 50 key fraud indicators to identify vulnerabilities and prioritise forensic audit activity effectively.
  • Develop a forensic audit toolkit: Build a cost-effective toolkit that balances fraud prevention and detection across different control environments.
  • Apply data mining techniques: Use CAATs, Benford's Law, Monte Carlo simulations, Markov chains, and big data forensic auditing to identify anomalies and fraud patterns.
  • Apply advanced forensic techniques: Use automated fraud detection, association rules, fuzzy logic, neural networks, and data visualisation for pattern recognition within forensic investigations.
  • Handle detected fraud correctly: Apply the correct legal, investigative, and reporting protocols when potential fraud is identified, including when and how to inform external bodies.
  • Integrate forensic indicators into audits: Embed fraud identifiers into routine audit activity without alerting potential fraudsters to the investigation.

Who is this Training Course for?

This forensic accounting and fraud control course is designed for audit, finance, and compliance professionals who need to develop or strengthen their capability to detect, investigate, and respond to fraud within their organisations.

This course is suitable for:

  • Internal Auditors: Those conducting financial and operational audits who need to embed forensic techniques and fraud indicators into their regular audit practice.
  • Forensic Accountants: Those specialising in or moving into forensic accounting who need a complete technical grounding across data mining, advanced detection techniques, and investigation protocols.
  • External Auditors: Those reviewing financial statements who need to strengthen their ability to identify fraud indicators and apply forensic procedures within their audit engagements.
  • Fraud Investigators: Those conducting fraud investigations who need structured technical capability across data mining, forensic toolkits, and legal reporting requirements.
  • Compliance and Risk Officers: Those overseeing anti-fraud frameworks and control environments who need a deeper understanding of how fraud is identified and investigated in practice.
  • Finance Managers and Controllers: Those with financial oversight responsibilities who need to understand fraud vulnerabilities and how to recognise the indicators that controls may not be providing adequate protection.
  • IT Audit and Data Analytics Professionals: Those applying CAATs, data analytics, and automated detection tools within audit and forensic contexts who need stronger forensic methodology alongside their technical skills.

How will this Training Course be Presented?

This Forensic Accounting and Fraud Control Training Course is designed using engaging, practical learning techniques to ensure a comprehensive understanding of fraud prevention and detection. The course incorporates:

  • Interactive Exercises – Hands-on application of forensic accounting and fraud detection techniques.
  • Case Studies – Real-world fraud investigations to reinforce practical learning.
  • Electronic Resources – Downloadable tools, templates, and checklists for immediate use post-course.
  • Dynamic Discussions – Trainer-led and peer-driven discussions on fraud risk management.

Participants will leave this course with a solid foundation in forensic accounting, enhanced investigative skills, and actionable strategies to protect their organisations from financial fraud.

The Course Content

  • 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 
  • 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
  • Use of Computer assisted audit techniques (CAAT’s)
  • Data mining techniques
  • Fraud risk prioritisation
  • Benford’s law
  • Use on Monte Carlo simulations and Markov chains
  • Forensic auditing of big data
  • Automated fraud detection
  • The control weakness and the key fields approaches
  • The association rules in fraud detection
  • Use of fuzzy logic
  • Neural networks
  • Data visualisation and pattern recognition
  • What to do when potential fraud is detected
  • The legal aspects of 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

Certificate

  • AZTech Certificate of Completion for delegates who attend and complete the training course

In Partnership With

Anderson Copex Coventry

Do you want to learn more about this course?

Register now or contact our team to discuss schedules, delivery formats, and customised options.

Related Courses

Check out other training courses might interest you

Frequently Asked Questions

Common questions about our training courses

The case studies are drawn from actual fraud scenarios spanning identity fraud, corruption, internal fraud, and external fraud, and are used throughout the foundational content to extract practical lessons about how fraud occurs, how it goes undetected, and what control failures enabled it. Each case study is used to reinforce specific fraud profiling and detection principles rather than as standalone examples, giving delegates a rich bank of reference scenarios they can draw on when assessing fraud risk in their own environments.  

Corruption is addressed as a distinct and particularly challenging fraud category because it typically involves collusion, does not leave the same transactional footprint as asset misappropriation, and often exploits relationships and processes that function normally in legitimate contexts. The course examines what makes corruption difficult to detect using conventional controls and audit approaches, and how forensic techniques including data pattern analysis, association rules, and relationship mapping are applied to identify corruption indicators within complex transaction environments.  

The legal framework governing the use of forensic data is covered as a core component of the investigation protocol content, addressing how forensic evidence is collected, preserved, and used in a way that maintains its legal admissibility. Delegates learn what the legal constraints on forensic data use are, how internal and external databases can be used within those constraints, and what the consequences are of mishandling forensic evidence in a way that compromises its use in legal proceedings or regulatory referrals.  

The 50 key fraud indicators are covered as a structured detection framework, addressing what each indicator signals, how it is identified within financial data and operational processes, and how indicators are prioritised based on the vulnerability profile of the organisation. Delegates learn how to use the indicators as a proactive forensic audit tool rather than a reactive checklist, building them into their regular audit planning and fieldwork to maximise detection effectiveness without alerting potential fraudsters.  

Benford's Law is covered as a data mining tool for identifying statistical anomalies in financial datasets that may indicate manipulation or fraud. Delegates learn the mathematical principle underlying the law, how it is applied to different types of financial data, and what the limitations of the technique are in practice. It is taught alongside other data mining techniques including Monte Carlo simulations and Markov chains as part of a connected forensic analytical toolkit rather than as an isolated method.  

The protocols for informing external bodies — including regulators, law enforcement, and professional bodies — are addressed within the investigation reporting content, covering the circumstances in which external notification is mandatory, when it is discretionary, and what the legal and organisational considerations are in making that determination. Delegates gain a working understanding of how to navigate the decision to escalate externally, what information needs to be prepared, and how reporting to external bodies affects the ongoing investigation and any subsequent legal proceedings.  

Related Categories

Related Articles