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Course Navigation
Introduction
Course Glossary
What digital fraud looks like in practice
Who commits digital fraud and why
How fraudsters attack users
Tools and technologies used by fraudsters
Module 1 Quiz
Module 1 Highlights
Module 1 Additional Materials
Fraud lifecycle
Core entities
Key fraud signals
How fraud entities and data are linked in Sumsub
Module 2 Quiz
Module 2 Highlights
Module 2 Additional Materials
Common fraud signals in product data
Building rules and risk scores for fraud detection
Graphs and machine learning for fraud detection
Fraud rules and scoring in Sumsub
Advanced fraud tools in Sumsub
Module 3 Quiz
Module 3 Highlights
Synthetic identities
Deepfakes and document spoofing
Automated attacks and bot-driven abuse
Money mules and cash-out networks
Module 4 Quiz
Module 4 Highlights
Module 4 Additional Materials
Fraud in Financial Services
Fraud in Crypto
Fraud in iGaming
Fraud in Marketplaces & E-commerce
Module 5 Quiz
Module 5 Highlights
Module 5 Additional Materials
Building and structuring a fraud prevention team
Alert management, case management and investigation workflows
Fraud strategy, risk matrix and technology stack
Measuring fraud performance and continuous improvement
Module 6 Quiz
Module 6 Highlights
Course review
Learning Experience Survey
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