Course Details

Objective

By the end of the course, participants will be able to understand

• Understand the fundamentals of fraud detection and its importance in business.
• Learn how to apply data analytics techniques to detect and investigate fraud.
• Gain proficiency in using statistical tools and software to identify suspicious transactions and patterns.
• Learn about common types of fraud and how data can reveal them.
• Develop skills to create fraud detection models and dashboards for real-time monitoring.
• Understand how to interpret data analytics results to make informed decisions.

Content

Day 1: Introduction to Fraud Detection and Data Analytics

• Overview of fraud detection in business environments
• The role of data analytics in fraud prevention
• Types of fraud: financial, procurement, asset misappropriation, etc.
• Key fraud detection principles and techniques
• Introduction to data analytics tools and platforms

Day 2: Identifying Fraud Patterns and Red Flags

• Common indicators of fraudulent activity
• Techniques for identifying unusual patterns in financial data
• Analyzing transactional data for signs of fraud
• Data preparation and cleansing for fraud analysis

Day 3: Statistical Techniques for Fraud Detection

• Introduction to statistical methods used in fraud detection
• Descriptive statistics: averages, trends, and outliers
• Predictive analytics: using historical data to forecast and detect fraud
• Anomaly detection techniques: z-scores, clustering, and regression analysis

Day 4: Building Fraud Detection Models

• Developing fraud detection algorithms using data analytics
• Using machine learning models for fraud detection
• Implementing real-time fraud detection systems and dashboards
• Evaluating and improving the effectiveness of fraud detection models

Day 5: Fraud Detection Reporting and Continuous Monitoring

• Creating effective fraud detection reports and visualizations
• Communicating findings to stakeholders
• Best practices for continuous fraud monitoring using data analytics
• Legal and ethical considerations in fraud detection
• Developing an action plan for ongoing fraud prevention and detection

NOTE:

Pre-& Post Tests will be conducted.

Case Studies, Group Exercises, Group Discussions, Last Day reviews, and assessments will be carried out.

Methodology

A highly interactive combination of lectures and discussion sessions will be managed to maximize the amount and quality of information and knowledge transfer. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. You will also be encouraged to raise your own questions and to share in the development of the right answers using your own analysis and experiences.  Tests of multiple-choice type will be made available on daily basis to examine the effectiveness of delivering the course.

Very useful Course Materials will be given.

• 30% Lectures
• 30% Workshops and work presentation
• 20% Group Work& Practical Exercises
• 20% Videos& General Discussions