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Fraud is a pervasive issue that transcends industries, with notorious cases like Satyam, Enron, and Lehman Brothers highlighting its costly consequences. Detecting and preventing fraud is crucial for safeguarding an organization’s financial health. While banking and online transactions often draw significant attention due to their high visibility, fraud can occur in any industry and process area.
Regardless of your industry or specific processes, prioritizing prevention is key, as recovering costs from fraudsters can be extremely challenging. This program is designed to address both aspects of fraud—detection and prevention—by providing insights from both operational and technological perspectives.
Course Content
Overview of Fraud Analytics
Fraud Analytics
2 Chapters
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Types of Frauds
2 Chapters
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Type of Data
2 Chapters
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Building Scenario
Fraud Scenario Identification
12 Chapters
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Fraud Risk Indicators Analytics
2 Chapters
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Fraud Risk Indicators Revenue Recognition
2 Chapters
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Fraud Analytics Tools, Techniques
Tools and Techniques
2 Chapters
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Anomaly Detection
2 Chapters
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Behavioral Patterns
2 Chapters
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Social Network Analysis
2 Chapters
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Application of Artificial Intelligence
Generative AI
15 Chapters
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Case Studies
1 Chapter
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Uniform Examination for Certification in Fraud Analytics
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