course | Detecting Fraud with Data Analytics
Join the Detecting Fraud... course taught in English
ARG-3016 | Detecting Fraud with Data Analytics
Course Sector : Audit, Risk and Governance
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 19/10/2026 | 23/10/2026 | Abu Dhabi | $4,250 | Book now |
| 5 Days | 05/04/2027 | 09/04/2027 | Geneva | $5,950 | Book now |
| 5 Days | 07/06/2027 | 11/06/2027 | Dubai | $4,250 | Book now |
| 5 Days | 26/07/2027 | 30/07/2027 | Abu Dhabi | $4,250 | Book now |
Course Introduction
Fraud continues to pose a significant threat to organizations across all sectors, impacting financial performance, reputation, and stakeholder trust. As fraud schemes become more complex and data volumes continue to grow, traditional detection methods alone are no longer sufficient. Organizations increasingly rely on data analytics to identify unusual patterns, detect anomalies, and uncover potential fraud risks proactively.
The Detecting Fraud with Data Analytics course is designed for professionals who have foundational knowledge of fraud, audit, or data concepts and are seeking to enhance their capabilities through analytical approaches.
Within BOOST, this program focuses on equipping participants with the skills to apply data analytics techniques to support fraud detection, prevention, and investigation activities.
The course emphasizes practical understanding of how data can be used to identify red flags, analyze transactions, and support evidence-based conclusions. Participants explore common fraud schemes, relevant data sources, analytical methods, and the interpretation of results within audit, compliance, and investigative contexts.
By combining fraud risk knowledge with applied analytics concepts, this program enables participants to move from reactive detection toward proactive, data-driven fraud risk management.
Course objective
- Understand the role of data analytics in fraud detection
- Identify common fraud schemes and related data indicators
- Use analytical techniques to detect anomalies and red flags
- Select appropriate data sources for fraud analysis
- Apply basic and intermediate analytics methods in fraud scenarios
- Interpret analytical results to support fraud conclusions
- Integrate data analytics into audit and investigation processes
- Strengthen fraud prevention and detection capabilities
Course audience
- Internal auditors and audit supervisors
- Fraud examiners and investigators
- Risk management and compliance professionals
- Finance and accounting professionals
- Data analysts supporting audit or compliance functions
- Governance and assurance professionals
- Public and private sector professionals involved in fraud detection
Course Outline | DAY 01
Fraud Fundamentals and the Role of Data Analytics
- Overview of fraud types and schemes
- Fraud risk factors and red flags
- Limitations of traditional fraud detection methods
- Role of data analytics in fraud prevention and detection
- Fraud detection versus fraud investigation
- Ethical and legal considerations
Course Outline | Day 02
Data Sources and Preparation for Fraud Analysis
- Identifying relevant data for fraud detection
- Financial, operational, and transactional data sources
- Data quality, integrity, and reliability considerations
- Data extraction and preparation concepts
- Understanding data relationships and structures
- Common data challenges in fraud analytics
Course Outline | Day 03
Analytical Techniques for Fraud Detection
- Descriptive analytics and trend analysis
- Exception and threshold analysis
- Benford’s Law and statistical indicators
- Duplicate and gap analysis
- Pattern recognition and outlier detection
- Applying analytics to common fraud scenarios
Course Outline | Day 04
Interpreting Results and Supporting Investigations
- Interpreting analytical outputs responsibly
- Distinguishing anomalies from confirmed fraud
- Documenting analytical procedures and findings
- Using analytics to support investigations
- Communicating results to stakeholders
- Managing false positives and investigation risks
Course Outline | Day 05
Integrating Fraud Analytics into Organizational Practice
- Embedding analytics into audit and fraud programs
- Continuous monitoring and fraud risk assessment
- Collaboration between audit, compliance, and data teams
- Governance and oversight of fraud analytics
- Lessons learned from fraud analytics cases
- Developing a fraud analytics action plan
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
Since 2001, we’ve been at the forefront of professional training in the Middle East — shaping the future of learning and development one success story at a time. With a vision rooted in innovation and excellence, we help individuals, teams, and organizations reach their highest potential through integrated, future-ready training solutions. Our comprehensive programs combine global best practices with local insights, empowering people to grow, lead, and make a lasting impact in their industries.
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