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Section 1: WHY
Section 1: WHY
Fraud prevention
https://cyvatar.ai/fraud-detection-prevention-banking/
Heterogeneous and large-scale data process
https://www.automationanywhere.com/products/iq-bot
WHAT
WHAT
Get data, build a data model, and analysis
https://neo4j.com/whitepapers/graph-data-science-use-cases-fraud-anomaly-detection/
How
How
ML Tools: Data fetch, Data visualization tool, and Google ML model
Auditing case Study
ML & Auditing project application
Section 2: ReQUIREMENT
Section 2: ReQUIREMENT
• Homework, class participation: 40%
Pre-Class 15%
In-Class 25%
• Midterm report & presentation ( Personal): 30%
• Final project (Group): 30%
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