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Fraud is changing. It is becoming more complex, more expensive, and harder to detect with traditional methods. As organizations deal with more data and face greater regulatory and reputational pressures, fraud analytics has become a key tool for maintaining financial integrity and operational trust.
This five-day training course provides professionals with the skills to use data analytics for identifying, preventing, and managing fraud effectively.
Throughout the course, participants will explore the basics of fraud analytics. They will learn about fraud patterns, how to prepare data, and how to apply statistical methods, machine learning, and anomaly detection techniques. Practical sessions will focus on building and assessing detection models, interpreting results, and integrating analytics into broader risk management practices.
The course will also tackle real-world challenges, such as data quality, model accuracy, ethical issues, and regulatory compliance. With case studies, hands-on exercises, and expert advice, attendees will gain practical skills to strengthen their organization's fraud defenses and make informed, data-driven choices.
Foundations of Fraud Analytics