• Lecture time: Tuesday: 12:30:00 - 13:20:00 ET
  • Lab time: Thursday: 11:30:00 - 13:20:00 ET
  • Domain: Insurance
  • Keywords: Data Engineering, Fraud, Imbalanced Classification, Parameter Selection, Security
  • Tools: Jupyter, Machine Learning, Python, SQL
  • Citizenship: Open to all students

Using security-oriented telemetry, find actionable instances of fraud in near real-time. Determine the probability that a transaction constitutes fraud and begin workflow.


Please see the PDF for a detailed project description. When registering for this project in UniTime, look for 'Elevance - Digital Fraud' in the Note section, and select the appropriate CRN. **CIT Majors preferred on this project**